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© 2013 Commercial in Confidence | IBM and MSTEM

Jamaica’s Smart Grid Roadmap:

Enabling the Nation’s Smarter Energy Future Submitted to: MSTEM

Submitted By: IBM

Document Number: Final Report

Version Number: 0.3

Dated: December 26, 2013

Jamaica’s Smart Grid Roadmap: Final Report

IBM | December 26, 2013 IBM – MSTEM Confidential of 93

Table of Contents

1 Purpose of This Document 6

2 Executive Summary 7

3 Smart Grid Baseline 11

3.1 Jamaica Current Situation and Priorities 11

3.2 MSTEM Policy Overview 13

3.3 Jamaica Smart Grid Readiness and Initiatives 15

4 Smart Grid Maturity Model 19

4.1 Smart Grid Maturity Model Overview 19

4.2 Smart Grid Maturity Model Assessment 20

4.3 Smart Grid Maturity Model Aspirations 24

5 Smart Grid Roadmap 33

5.1 Information Management 34

5.2 Loss Management 36

5.3 Customer Conservation and Energy Efficiency - Prepayment 41

5.4 Customer Conservation and Energy Efficiency – Smart Buildings 43

5.5 Customer Conservation and Energy Efficiency – Smart Water 46

5.6 Customer Conservation and Energy Efficiency – Dynamic Rates 48

5.7 Asset Management 50

5.8 Grid Operations – Distribution Automation 53

5.9 Grid Operations - Renewable Generation (Utility Scale) 57

5.10 Grid Operations - Distributed Resources 59

6 Smart Grid Roadmap Benefits and Costs 62

6.1 Smarter Planet Value Quantification Model Overview 62

6.2 Smarter Planet Value Quantification Model Findings 63

7 Appendix A 66

7.1 Smart Grid Overview, Lessons Learned and Case Studies 66

8 Appendix B 75

8.1 Smart Grid Maturity Model Aspirations – Domain Detail 75

9 Appendix C 87

9.1 Smart Grid Communications Deep Dive Discussion 87

9.2 Renewable Integration Deep Dive Discussion 87

9.3 Smart Water Deep Dive Discussion 88

9.4 Customer Conservation Deep Dive Discussion 88

9.5 Asset Management Deep Dive Discussion 89

9.6 Distributed Energy Resources Deep Dive Discussion 89

9.7 Smart Buildings Deep Dive Discussion 90

10 Appendix D 92

10.1 Smarter Planet Value Quantification Model Inputs 92

.



Figures

Figure 1: Smart Grid Roadmap Overview..............................................................................................8

Figure 2: Jamaica’s Smart Grid Benefits .............................................................................................10

Figure 3: Smart Jamaica’s Current and Target Energy Supply Mix (Fitzroy Vidal’s Presentation) ....11

Figure 4: SAIDI Benchmark Levels – 2011 (KEMA Audit of the JPS Q-factor Report) ......................12

Figure 5: Jamaica Regulatory and Ministry Timeline ..........................................................................15

Figure 6: JPS Outage Metrics and Reliability Indicators (KEMA Audit of the JPS Q-factor Report) ...........................................................................................................................................15

Figure 7: JPS Smart Grid Readiness Observations ............................................................................18

Figure 8: Maturity Levels of the Smart Grid Maturity Model ................................................................19

Figure 9: Domains of the Smart Grid Maturity Model ..........................................................................20

Figure 10: July 4, 2013 SGMM Assessment Workshop Agenda ........................................................21

Figure 11: Jamaica SGMM Results .....................................................................................................22

Figure 12: JPS SGMM Assessment Results .......................................................................................23

Figure 13: Jamaica Smart Grid Future-State Aspirations....................................................................24

Figure 14: Jamaica Strategy, Management, & Regulation Domain Aspirations .................................25

Figure 15: Jamaica Organization & Structure Domain Aspirations ....................................................26

Figure 16: Jamaica Grid Operations Domain Aspirations ...................................................................27

Figure 17: Jamaica Work & Asset Management Domain Aspirations................................................28

Figure 18: Jamaica Technology Domain Aspirations ..........................................................................29

Figure 19: Jamaica Customer Domain Aspirations .............................................................................30

Figure 20: Jamaica Value Chain Integration Domain Aspirations.......................................................31

Figure 21: Jamaica Societal & Environmental Domain Aspirations ....................................................32

Figure 22: Smart Grid Roadmap Overview .........................................................................................33

Figure 23: Information Management Initiatives ...................................................................................35

Figure 24: Loss Management Approach .............................................................................................37

Figure 25: Non Technical Losses Possible Recovery Actions ............................................................38

Figure 26: Approach Adaptation ..........................................................................................................39

Figure 27: Loss Management Initiatives..............................................................................................40

Figure 28: Prepayment Program Initiatives .........................................................................................42

Figure 29: Smart Buildings Initiatives ..................................................................................................45

Figure 30: Smart Water Initiatives .......................................................................................................47

Figure 31: Power Quality Impacts on Water and Electric Networks....................................................47

Figure 32: Dynamic Rates Program Initiatives ....................................................................................49

Figure 33: Asset Management Initiatives ............................................................................................51

Figure 34: Distribution Automation Initiatives ......................................................................................55

Figure 35: Renewable Generation Initiatives.......................................................................................58

Figure 36: Distributed Resources Program Initiatives .........................................................................59

Figure 37: Smarter Energy Value Streams..........................................................................................62

Figure 38: Benefit Benchmarks............................................................................................................63

Figure 39: Current and Planned JPS Investments ..............................................................................64

Figure 40: Year 15 Estimated Benefits ................................................................................................64



Figure 41: Annual Smart Grid Benefits at Year 15 ..............................................................................65

Figure 42: Smart Grid Capability Domains ..........................................................................................66

Figure 43: Smart Grid End-to-End Components .................................................................................68

Figure 44: Ontario Regulator’s Proposed Time-of-Use Rate/Tariff Profile..........................................70

Figure 45: Eskom’s Energy Loss Management Program Structure ....................................................72

Figure 46: Sample Program Structure to Address Cross Project Interdependencies and Complexities ..................................................................................................................................74

Figure 47: Jamaica Strategy, Management, & Regulation Domain Aspirations .................................75

Figure 48: Jamaica Organization & Structure Domain Aspirations ....................................................77

Figure 49: Jamaica Grid Operations Domain Aspirations ...................................................................78

Figure 50: Jamaica Work & Asset Management Domain Aspirations................................................79

Figure 51: Jamaica Technology Domain Aspirations ..........................................................................81

Figure 52: Jamaica Customer Domain Aspirations .............................................................................82

Figure 53: Jamaica Value Chain Integration Domain Aspirations.......................................................84

Figure 54: Jamaica Societal & Environmental Domain Aspirations ....................................................85

Figure 55: Non Technical Losses Possible Recovery Actions ............................................................88

Figure 56: PV Grid Parity Arriving........................................................................................................90

Figure 57: JPS/Jamaica Value Model Inputs 1....................................................................................92

Figure 58: JPS/Jamaica Value Model Inputs 2....................................................................................93



Document Control Rev. Rev. Date Summary of Changes Author Changes

Marked?

0.1 December 13, 2013 Submitted for comment Ferris No

0.2 & 0.3 December 26, 2013 Illustration updates Ferris No

Approvals

This document requires the following Delivery approvals.

Organisation Name Title

MSTEM Fitzroy Vidal Principal Director, Energy

MSTEM Edgar Wiggins Project Manager, Energy

IBM James Strapp IBM Partner

IBM Jeffere Ferris IBM Project Manager



1 Purpose of This Document

The Jamaican Ministry of Science, Technology, Energy, and Mining (MSTEM) has initiated an Energy Security and Efficiency Enhancement Project, which has been designed to support the implementation of the Government of Jamaica’s (GoJ) National Energy Policy (NEP) covering 2009 through 2030. The project will develop a Smart Energy Roadmap, representing the key initial step in moving Jamaica’s energy objectives forward.

The Smart Energy Roadmap will address four priority areas, all of which are intended to begin to reduce Jamaica’s energy cost and consumption with the application of leading information technology and best practices implemented worldwide, within the context of the larger Smarter Energy Vision for Jamaica:

1. Smart Grid Roadmap: Identifying, prioritizing and defining initiatives to advance smart grid in Jamaica in support of the National Energy Policy

2. Smarter Buildings: Applying advanced energy management approaches for larger buildings

3. Water and Energy Efficiency: Reducing water loss in the system, resulting in lower overall energy consumption

4. Customer Conservation Programs: Introducing new tariffs and programs made possible by smart meters, such as time-of-use pricing, prepayment plans, and load control or other in-home services.

Smart grid is an electricity network that uses digital and advanced technologies to monitor and manage the transport of electricity from all generation sources efficiently by minimizing costs and environmental impacts while maximizing system reliability, resilience and stability. As part of the Smart Energy Roadmap effort, IBM was engaged to develop a Smart Grid Roadmap, which identifies, defines, and sequences smart grid initiatives to address Jamaica’s priorities and support Jamaica’s National Energy Policy. In addition, IBM was engaged to provide subject matter expertise to advance the discussions around the other priority areas, namely, smarter buildings, water, and energy efficiency and customer conservation programs.

This final report represents the results from IBM’s work on the Smart Grid Roadmap Development project. The report defines a strategic roadmap of prioritized smart grid initiatives to address Jamaica’s priorities and challenges and provides details on the project’s purpose, global references, the project’s policy alignment, Jamaica’s smart grid baseline status, and proposed target capabilities incorporating the results of Jamaica’s Smart Grid Maturity Model assessment.



2 Executive Summary

Oil imports represent over 35% of Jamaica’s annual gross domestic product. Imported oil represents approximately 91% of the country’s energy sources. The escalating cost of oil has dramatically increased the cost of living in Jamaica and reduced the nation’s international competitiveness. The cost of energy for Jamaica’s businesses and consumers is over US$ 0.40 per kWh, placing it amongst the highest of Caricom countries. This creates an unsustainable position for Jamaica’s national development and global competitiveness.

To start to address these issues, the Government of Jamaica (GoJ) has issued a National Energy Policy (NEP) 2009-2030. This policy establishes the goal of providing “affordable and accessible energy supplies with long-term energy security” and calls for development of the energy sector in the area of renewable energy. It establishes a strategic framework which sets specific goals for the policy, including creating the necessary economic, infrastructure and planning conditions; promoting renewable energy sources; enhancing technical capabilities; and promoting public awareness of renewable energy.

In support of the NEP, Jamaica’s National Renewable Energy Policy identifies several priorities to enable the country to meet the National Energy Policy goal of 20% renewable generation in the country’s energy mix. The policy increases focus on the importance of introducing flexibility and scalability to the country’s electricity network.

The Smart Grid Roadmap supports these policy goals while presenting new opportunities for customers, JPS and the nation with a coordinated approach that will increase the cost effectiveness of electricity supply and decrease reliance on petroleum-based generation. The Smart Grid Roadmap builds on Jamaica Public Service Corporation’s (JPS) smart grid investments with lessons learned from smart grid implementations around the globe, as it identifies specific initiatives for the modernization of the electric network to enable the utilization of large-scale renewable generation, the integration of distributed generation resources, more cost effective electric network operations and improved reliability.

With input from the Jamaica Public Services Company (JPS), the Office of Utilities Regulation (OUR), the Petroleum Corporation of Jamaica (PCJ), and the Ministry of Science, Technology, Energy, and Mining (MSTEM), Jamaica’s Smart Grid Roadmap has been devised to meet Jamaica’s short- and long-term goals. Short-term initiatives have been designed to address high electricity costs and reliability issues while developing the foundation for Jamaica’s long-term energy independence and sustainability goals. As the fuel cost reduction benefits of Jamaica’s generation expansion program are realized, longer-term initiatives enable Jamaica’s ability to adjust the energy supply mix while continuing to achieve performance and efficiency objectives.

Jamaica’s Smart Grid Roadmap is designed as a series of work streams supported by investment programs (See Figure 1).



Figure 1: Smart Grid Roadmap Overview

Jamaica’s Smart Grid Roadmap work streams are:

• Information Management: Data collection and management are foundational to achieving smart grid capabilities. As new higher functioning electric network devices are procured and deployed, the benefits derived from these devices are limited by current communications and ‘back-end’ information management capabilities. This work stream provides the network communication capabilities to collect data from across the network as well as the information management capabilities to aggregate, analyze, and utilize the data. Investments in this work stream will enable the progression toward near-real time operational data in the short-term and automated decision making and predictive operational data modelling in the medium and long term. These levels of information availability will enable system-wide fault location and anticipation, asset condition monitoring and maintenance, power quality monitoring, and, eventually, improved electricity usage visibility to customers.

• Loss Management: Loss management is an area of ongoing focus in Jamaica due to the high degree of energy theft. With OUR limits on the amount of loss which can be passed on to the customer rates, it’s a problem for JPS and the country. The Smart Grid Roadmap supports a systematic approach which targets different loss management strategies across JPS’s network based on cost and benefit projections. This work stream is designed to avoid large investments in single technologies and measure costs versus benefits as approaches are field tested. These findings will aid JPS in altering approaches as success is measured.

• Customer Conservation and Energy Efficiency: Smart grid technologies improve customers’ ability to manage their electricity costs while aligning consumption with the constraints of the electricity network. Smart meters allow for time-sensitive electric rates which represent the costs of delivering energy in particular time periods and encourage consumption at off-peak demand times. Smart meters also provide mechanisms for improved monitoring of customers’ usage as well as new offerings, such as prepayment for electricity. To support customer conservation and energy efficiency, this work stream includes investments in four areas:

Grid Operations

Customer Conservation and Energy Efficiency

Asset Management

Information Management

Loss Management

Work Stream 2013-2016 2017-2020 2021-2030

Grid Operations


Asset Management


Loss Management

Work Stream 2013-2016 2017-2020 2021-2030

Foundational ProgramEnhanced Program

Legend

Loss Management

Smart Water

Smart Buildings

Asset Management

Distribution Automation

Renewable Integration

Distributed Resources

Dynamic Rates


Prepayment



o Dynamic Rates Program: Time-of-use rates are an opportunity to shift demand away from the higher cost generation deployed during peak and partial-peak demand periods. Demand management through time-sensitive rates also allows JPS to avoid network augmentation at stressed points in the electric grid. In addition, opt-in curtailment (e.g., interruptable) rates for customers who agree to participate in a demand reduction scheme during times of network stress assist with avoiding network investments. This program includes investments to extend the existing demand management rate programs and prepare for additional rate programs across all customers.

o Smart Water Program: Because the National Water Commissions (NWC) is the largest aggregate electricity customer, water management is a significant influence on the electrical network. The electricity network will benefit from aligning NWC’s service requirements with JPS’s electrical network needs and costs through time-sensitive rates. In addition, aligning the infrastructure between these two service companies presents a cost-savings and customer service opportunity. Investments in this program provide for this alignment.

o Prepayment Program: Prepayment programs provide customers improved energy cost control and utilities better management of debt relating to high-risk customer usage. This program includes investments to evaluate and implement prepayment solution options.

o Smart Buildings Program: Because energy costs represent almost a quarter of total occupancy costs, improved facility energy management is a foundation to energy efficiency. Improvements in facilities maintenance and space management also generate increased returns on assets. In addition to public sector buildings, healthcare, education, and some commercial facilities are candidates for a coordinated approach across these building management tactics. The roadmap describes initiatives to advance efficient building management in the public sector and initiatives to drive these practices further into Jamaica’s buildings.

• Asset Management: Utilities are increasingly moving from reactive maintenance to condition-based asset maintenance. The collection of good field maintenance data and integrated applications are keys to improved asset decisions, productivity, and reliability. This work stream enables cross-functional asset management through system investments and initiatives to consolidate sources of asset condition data so that all asset information and events are associated with the asset. This unified approach will allow JPS to manage asset deployment, specifications, monitoring, calibration, costing and tracking to extend the life and reliability of the highest value assets with an initial focus on key value assets and metrics; expanding to a wider set of assets with additional capabilities, such as remote asset monitoring, as business value dictates.

• Grid Operations: Smart grid technologies, such as electric network sensors and remote control devices, provide for advancement in grid monitoring and control, which improves reliability and prepares for increased renewable generation penetration while operating the network more efficiently. To support grid operations, this work stream includes investments in three areas:

o Distribution Automation Program: The falling costs of sensors and supporting communications technologies, combined with the rollout of “smart” equipment (for example: smart switches, reclosers), are allowing for mainstream adoption of distribution automation capabilities. Advanced network automation, including methods of routing power, balancing loads and improving distributed generator control can be achieved through precise demand prediction, as well as parametric model-based methods of maintaining, upgrading and expanding the network based on fine-grained monitoring of both grid and device performance. This program includes investments in new systems to achieve improvements in grid management (such as Fault Detection, Isolation, Restoration, automation support, fast load flow etc) and lay the foundation for the wider range of advanced monitoring and control capabilities.



o Renewable Integration (Utility Scale) Program: To manage renewable integration, utilities are pursuing complementary approaches of improved forecasting and utility-scale electricity storage. Improved forecasting based on a wider set of data inputs can improve the utilization of renewable generation and lower the expensive requirements for additional stand-by generation and storage options. This program includes investments to develop Jamaica’s renewable forecasting capability and establish the capabilities to support a larger portfolio of centralized renewable sources.

o Distributed Resources Program: Due to high electricity costs and decreasing distributed generation system costs, such as photovoltaic (PV) installations, Jamaica will see expanding adoption of distributed generation sources. Although they present potential benefit in transmission and distribution network investment deferral, the electric network will face operational challenges caused by the clustering of distributed generation. Distributed generation intermittency will drive storage requirements and network planning considerations. Distributed generation will also challenge current rate programs and business models as customers will increasingly have other electricity supply options. This program supports the development of grid management capabilities to address distributed generation operational challenges while it promotes the evolution of electricity rates and business models around distributed generation.

The smart grid investments in each of the work streams will provide value across Jamaica. The Smart Grid Roadmap investment path builds on past investments to the end goal of improving the efficiency and effectiveness of the electric network in meeting Jamaica’s goals.

Based on the cumulative experiences of utilities in implementing smart energy investments and the specific characteristics of Jamaica’s electric network, the estimated gross benefit of Jamaica’s Smart Grid Roadmap is US$1.313 Billion over 15 years from total investments of US$144.6 Million. These benefits include US$547 Million in customer benefits from improved reliability, lower bills, and reduced energy costs. JPS’s estimated benefits of US$767 Million are driven primarily by operational and capital expenditure efficiency. The US$93 Million environment benefit from reductions in emissions is included in JPS benefits, anticipating the value of carbon emission credits (See Figure 2). These “Utility” and “Environment” benefits provide JPS an estimated 5.4 year payback period on the smart grid investments.

UtilityUS$ 674M (51%)

CustomerUS$ 547M (42%)

EnvironmentUS$ 93M (7%)

Figure 2: Jamaica’s Smart Grid Benefits



3 Smart Grid Baseline

As a starting point to establishing Jamaica’s Smart Grid Roadmap, Jamaica’s electric network is faced with a number of challenges which impact the cost of electricity and the effective operation of the electric grid. To address these challenges, the GoJ has identified seven goals in the National Energy Policy to advance energy management. Smart grid supports these policy goals while presenting new opportunities for customers, JPS and the nation.

This section reviews Jamaica’s current situation, governmental energy policies, and the smart grid readiness of Jamaica’s electric network.

3.1 Jamaica Current Situation and Priorities

The high cost of electricity in Jamaica, unreliable delivery of electricity in comparison to other island nations, significant electric losses, and growing distributed generation penetration across the electric network present immediate challenges to managing Jamaica’s electric grid. Opportunities to add renewable generation sources to the energy supply portfolio advance Jamaica’s objective to achieve energy independence and limit Jamaica’s carbon emissions, but present longer-term operational challenges to electric grid stability as intermittent renewable generation sources reach higher penetration levels.

Energy Supply Mix

To address the dependency on foreign oil and the cost impacts of oil price fluctuations, Jamaica is setting targets to diversify the energy supply mix (See Figure 3). This includes the increase of renewable energy sources, including intermittent wind and solar resources, from 5 to 20% of the total supply mix by 2030. As the percentages of intermittent renewable generation increase, the electric system will need to evolve to address the fluctuations of these supply sources.

Figure 3: Smart Jamaica’s Current and Target Energy Supply Mix (Fitzroy Vidal’s Presentation)

95

67

52

30

5

15

12.5

0.5

26

42

15

2 3

205

5

5

Jamaica's Energy Supply Matrix



Distributed Energy Resources

The installation of renewable energy sources by consumers in the distribution network is increasing as a hedge against the high cost of electricity. A penetration survey of these distributed energy resources is currently underway. The potential for fluctuations at the feeder level due to high concentration of these resources will drive further network planning and investment.

Energy Cost

The cost of energy for Jamaica’s businesses and consumers is over US$ 0.40 per kWh and is among the highest for Caricom countries according to CARILEC (Association of Electric Utilities). This creates an unsustainable position for Jamaica’s national development and global competitiveness. In addition to energy supply costs, operational and capital cost efficiencies are a priority.

Energy Losses

A significant input to the cost of electricity is the cost of energy loss across the system. According to the International Energy Agency, electric power transmission and distribution losses (% of output) in Caribbean small states were 11.60% as of 2010. In Jamaica, on average, technical losses are approximately 10% of output, while non-Technical losses (e.g., electricity theft) are a further 16% of output.

Although the Office of Utilities Regulation (OUR) only allows JPS to pass losses of 17.5% onto the rate base, the reduction of losses presents an ongoing challenge for the country.

Energy Conservation and Efficiency

Due to high oil prices, the limited public resources for investment in energy supply, and the impact of energy resources on environment, reducing Jamaica’s energy requirements is a priority.

Reliability

Although reliability improvement initiatives are in progress, Jamaica’s reliability levels are lower than those observed in other jurisdictions with similar characteristics. Jamaica stands out with 29 hours outage duration per customer compared against similarly sized island nations (See Figure 4).

Figure 4: SAIDI Benchmark Levels – 2011 (KEMA Audit of the JPS Q-factor Report)



As a first step to improving reliability, the OUR commissioned a 2012 review of JPS performance indicators and data collection procedures to confirm a baseline for reliability monitoring. The findings included a declining accuracy of recorded interruption data from 2009 to 2011, with recommendations to address, but observed that JPS is moving to best practice interruption data collection with an accurate Outage Management System, interfacing with the Geographic Information System and the Supervisory Control and Data Acquisition (SCADA) system.

Although the report found that interruptions caused by generation constraints represent approximately 50% of all interruptions, the opportunity to improve electric network resilience and outage restoration is a significant priority.

3.2 MSTEM Policy Overview

In support of Vision 2030 Jamaica, the Government of Jamaica (GoJ) has issued a National Energy Policy (NEP) 2009-2030 and several draft sub-policies with respect to Renewable Energy (RE), Waste to Energy, Biofuels, Energy Conservation and Efficiency and Carbon Trading. The Ministry of Science, Technology, Energy and Mining (MSTEM), the entity with portfolio responsibility for energy in Jamaica, is currently developing another sub-policy called “The Electric Power Sector Policy and Strategy”. This sub-policy identifies priorities for the electricity sub-sector, including the means of smart grid as a medium to facilitate several initiatives arising from the National Energy Policy.

The NEP presents seven goals which will drive Jamaica toward achieving Jamaica’s energy vision of:

A modern, efficient, diversified and environmentally sustainable energy sector providing affordable and accessible energy supplies with long-term energy security and supported by informed public behaviour on energy issues and an appropriate policy, regulatory and institutional framework

Smart grid and the development of a Smart Grid Roadmap for Jamaica support these seven goals. Goals 1, 2, 3, and 7 can be directly impacted by the smart grid program, while goals 4, 5, and 6 will be enabled, as follows:

1. Improved Energy Conservation and Efficiency - “Jamaicans use energy wisely and aggressively pursue opportunities for conservation and efficiency”

• Smart grid supports conservation by providing better visibility and information to customers about their energy usage through technologies, such as smart meters

• Demand management and prepayment programs driven by new rate structures and smart meters have been shown to lower overall electricity demand

• Load flow analysis and balancing supported with improved monitoring and distribution management technologies will reduce technical losses across the electric system

2. Modernized Energy Infrastructure - “Jamaica has a modernized and expanded energy infrastructure that enhances energy generation capacity and ensures that energy supplies are safely, reliably, and affordably transported to homes, communities and the productive sectors on a sustainable basis ”

• Smart grid provides real-time monitoring and management capabilities across the electric network which improve network resilience and responsiveness to problems

• Asset management and grid operations supported by increased real-time monitoring and management will increase the efficiency of capital and operation investments



3. Development of Renewable Energy Sources - “Jamaica realizes its energy resource potential through the development of renewable energy sources and enhances its international competitiveness and energy security whilst reducing its carbon footprint ”

• Smart grid real-time monitoring and distribution management functions provide the capability to manage a diverse set of intermittent renewable resources (e.g., wind and solar), so that the penetration of bulk and distributed renewable resources can be increased

4. Energy Supply Security & Diversification of Fuel Sources - “Jamaica’s energy supply is secure and sufficient to support long-term economic and social development and environmental sustainability ”

• Smart grid will indirectly support fuel source diversification with the enablement of increased penetration of intermittent renewable generation

5. Governance/Regulatory Framework - “Jamaica has a well-defined and established governance, institutional, legal and regulatory framework for the energy sector that facilitates stakeholder involvement and engagement ”

• Smart grid will indirectly support stakeholder involvement and engagement with the improved visibility that is provided to all stakeholders

• Better measurement and monitoring provided by increased sensing and communication capability will support regular stakeholder reporting as well as real-time operational reporting to stakeholders in the course of outage response

6. Government Ministries, Agencies & Departments as Model leader - “Government ministries and agencies are a model/leader in energy conservation and environmental stewardship in Jamaica ”

• The Smart Grid Roadmap will indirectly support the government role as a leader in energy management with a clear articulation of the steps required to achieve Jamaica’s energy vision

7. Eco-efficiency and Green Economy - “Jamaica’s industry structures embrace eco-efficiency for advancing international competitiveness and move towards building a green economy ”

• Smart grid provides conservation and cost saving opportunities for customers through improved and more timely energy usage information utilizing smart meter technology

• Smart grid support of an expanded energy value chain which includes a broad variety of energy service providers creates the opportunity for Jamaican companies to provide products and services aimed at achieving a green economy

Supporting the NEP, the GoJ and the OUR have set targets for renewable generation integration as well as reliability and system loss improvement milestones (See Figure 5). Incentives and penalties are in place or in development to achieve these targets. In addition, the GoJ set a target of reducing public sector energy consumption 5 percent below the 2010 level, by 2015, mainly through public sector efficiency programs. This timeline provides guide posts to the Smart Grid Roadmap.



Figure 5: Jamaica Regulatory and Ministry Timeline

3.3 Jamaica Smart Grid Readiness and Initiatives

3.3.1 Jamaica Public Service Corporation Overview

JPS is the sole electricity distributor for Jamaica and serves two load centers in Kingston and Montego Bay in addition to rural customers. The customer base of approximately 600,000 customers is composed of approximately 90% residential customers, 10% commercial, and 145 industrial customers.

The network delivers power to several large customers with the Caribbean Cement Company (28 MW) the largest and the National Water Commission representing the largest aggregated load across its network of 480 pumps and relays (30 MW peak demand), primarily outside Kingston.

JPS’s peak load is 640 MW and the usage patterns drive a high consumption period during the day and a higher evening peak during most of the year.

Generation capacity is approximately 860 MW provided by JPS-owned power plants, independent power stations, and renewable generation (41 MW) coming from wind and hydro sites.

Network Performance

Figure 6: JPS Outage Metrics and Reliability Indicators (KEMA Audit of the JPS Q-factor Report)

2021-20302016-202020152014201320122011 2021-20302016-202020152014201320122011

Renewables ~5% Renewables 15%115 MW Renewables RFP

System Losses

17.5% Target

Energy Security & Efficiency Project

20%12.5% Renewables target

Energy Efficiency

ReliabilityBaseline Annual reduction target



Demand Management

JPS utilizes a feeder shedding scheme for load management, which rotates across feeders in blocks. In addition, JPS has deployed 6,000 interval meters with time-of-use rates for large commercial and industrial customers.

Outage Management

Currently, JPS utilizes several in-house, non-integrated applications to serve the outage management function. JPS is implementing an outage management system with integration to SCADA, the geographic information system, and the workforce management system.

Distribution Management

In 2009, a new SCADA and energy management system were deployed. Currently, the distribution network load flow analysis is done off-line. Distribution management system functionality is planned as a future extension to the outage management system implementation.

Asset and Workforce Management

Currently, asset and workforce management uses spreadsheets to track asset information and workforce execution, with limited information on asset maintenance or asset history. There is no structured preventive maintenance program. JPS depends heavily on field staff to know asset information, history and asset maintenance requirements.

An asset and workforce management department has recently been created and an asset management system project is in planning for 2014.

Loss Management

Feeder meters are used to calculate a total system loss which varies over time, but has recently been estimated at 26% (10% technical loss and 16% non-technical loss), with some feeders estimated up to 40% loss. The residential AMI program has been designed to address electricity theft where meters are enclosed within cabinets at the distribution transformers.

3.3.2 JPS Smart Grid Readiness

Information collected about JPS’s network is discussed below, including observations regarding JPS’s overall readiness for the deployment of smart grid capabilities (See Figure 7). In some cases the nature of JPS’s network creates a constraint on the potential benefits of smart grid technology solutions (e.g., lack of capacity, lack of redundant feeder paths). In other cases, smart grid readiness is simply limited by the extent of present technical deployments (e.g., communications backbone, lack of integration technologies).

Subject Area

Characteristics Smart Grid Readiness and Constraints Observations

Substations 12 transmission substation

43 distribution substations

Extensive visibility and control with most substations visible in SCADA (fiber to urban substations and microwave in rural).

The SCADA rollout and communications to the substations are an important foundation to smart grid management capabilities.

The lack of a reliable source of asset and maintenance information limits the ability



Subject Area


to increase the efficiency and effectiveness of managing substation assets.

Distribution network and switches

Network configuration does not include significant redundancy; most distribution switches are only used to shed load and are intended to remain closed unless a circuit breaks.

JPS is conducting a distribution automation pilot this year, with 17 switches in key strategic locations that would normally be manual switches.

JPS has SCADA visibility down to feeder reclosers using microwave (pole-mounted reclosers can be operated through SCADA)

JPS has no visibility to distributed renewable resources unless they have a contract to sell back to JPS. A distributed generation survey is in progress to determine location and penetration.

The opportunity to provide alternative feeder paths supporting distribution automation is limited to a small part of the network.

The lack of a distribution management system limits the ability to operate a real-time network using dynamic decisions to optimize resources and manage demands.

Prior to the completion of the distributed generation survey, it is unclear the degree to which distribution network generation is impacting feeder power quality.

Increasing distributed generation penetration will present a network management issue for impacted feeders.

Capacitor banks, reactors, and voltage regulators

Currently, there is no remote monitoring of voltage regulators and capacitors (bulk capacitor banks monitored at substation, but not on pole tops).

Low voltage power quality (PQ) is generally only looked at if there is a known or reported issue in the area. Currently, PQ claims are investigated manually (e.g., looking at events and other customers), which is time consuming and often inconclusive. The extent of power quality issues can be expected to increase with the growth of distributed generation.

JPS is planning to install PQ meters on all distribution feeders (Currently, JPS uses moveable power quality sensors).

JPS’s ability to optimise power factor (PF) across its network is relatively limited. Significantly greater network observability would be required in order to intelligently deploy greater power factor correction capability.

At lower voltage levels PF tends to vary more over time, so automated capabilities are required.

JPS’s ability to influence voltage quality is limited due to lack of observability over the course of the day/week/year. The current PQ meter program has the potential to address this.

While regulators are installed, they have no remote monitoring or coordinated control capability and this limits JPS’s ability to adjust voltage levels in the MV/LV system.

Meters Most meters are electro mechanical meters (350K-400K), with some electronic meters (150K-200K).

6,000 commercial AMI meters have been

JPS’s widely dispersed customer base creates challenges in last mile communications required for a comprehensive AMI deployment. Trialling in this area should provide some



Subject Area


deployed to customers with 3,000 kWh consumption or more. These meters support interval meter reading and time-of-use billing.

24,000 residential AMI meters have been deployed, supporting remote reading, remote connect/disconnect, and theft prevention:

• Residential AMI meter deployment targeted at high-density, high-loss feeders

• Enclosure/cabinet solution attached to the distribution transformer with 12-15 meters per enclosure and communications to the cabinet

• Interval reads possible on latest deployed meters (4,000 meters)

• In most cases, premises displays include only current usage. Latest deployed meters (4,000 meters) includes historical and current usage data

JPS has not deployed a meter data management system

insight into optimal communications (while allowing for other likely smart grid communication needs).

The lack of a meter data management system will impact the ability to bill from the smart meters at scale.

Figure 7: JPS Smart Grid Readiness Observations



4 Smart Grid Maturity Model

4.1 Smart Grid Maturity Model Overview

The Smart Grid Maturity Model (SGMM) is a management tool which has become a standard to guide, appraise and improve a utility’s path toward smart grid transformation in multiple operational areas through defining specific levels of capabilities and desired results. It establishes a common framework and language, defining all the elements of a smart grid transformation in order to bridge gaps between strategy and execution that might exist. The SGMM can be used in a variety of ways, the most powerful of which is to create a common vision and prioritization of initiatives providing the greatest opportunity for improvement, innovation and transformation and helping utilities develop a programmatic approach to track progress.

The SGMM assesses an organization’s maturity to implement and leverage smart grid solutions. Each stage of maturity has a defined set of characteristics and outcomes (See Figure 8). These stages of maturity are assessed across eight Domains - logical groupings of functional components of a smart grid transformation implementation (See Figure 9).

Figure 8: Maturity Levels of the Smart Grid Maturity Model



Figure 9: Domains of the Smart Grid Maturity Model

Each stage of maturity in each domain is described via detailed characteristics. There are more than 200 characteristics representing capabilities which describe how a utility would be expected to operate at each stage of the smart grid journey.

Over 120 utilities from over 20 countries have completed SGMM assessments. This community of large and small utilities with varying business models (e.g., fully integrated, retail only, etc.) is the benchmark to which utility SGMM assessments are compared. This benchmark comparison is used as the basis for planning discussions to determine smart grid target capabilities. The aspirations established in the process are guides to initiative planning.

4.2 Smart Grid Maturity Model Assessment

With representation from Ministry of Science, Technology, Energy, and Mining (MSTEM), Jamaica Public Services Company (JPS), the Office of Utilities Regulation (OUR), the Petroleum Corporation of Jamaica (PCJ) and IBM, a workshop was conducted on July 4, 2013 documenting the current smart grid capabilities of JPS’s network (See Figure 10).



Agenda Topic Description

Opening Remarks Introduction from MSTEM

Project Update Approach and timeline; Final Products and expected outcomes

Overview of Smart Energy Concepts and Technologies

Overview of smart grid concepts and technologies; Overview of government policies to support smart grid; Overview of utility initiatives to create smarter electricity infrastructure; Key lessons learned in smart grid transformations; Relevant case studies Objective: Develop common understanding of impact of smart grid

Overview of Jamaica’s Smart Energy Position

Current policy objectives; Existing initiatives and projects; Review of objectives by key stakeholder groups Objective: Develop baseline understanding of MSTEM policy, objectives, initiatives, planning and direction around smart grid and smart energy

Smart Grid Maturity Model Introduction

Objective and history; Method to implement

Smart Grid Maturity Model Guidelines

Guidelines for completing the survey and participation

Smart Grid Maturity Model Survey

Complete assessment of the 8 Smart Grid Maturity Model Domains

Wrap Up and Next Steps

Figure 10: July 4, 2013 SGMM Assessment Workshop Agenda

The SGMM assessment results identified Jamaica’s progress and preparedness in several smart grid areas with Jamaica attaining Level 1 maturity in the Organization & Structure and the Grid Operations domains. In addition, significant progress was noted in the Technology and Customer domains.

The detailed survey results (See Figure 11) show the presence of characteristics expected at each of the maturity levels for the respective domains. To achieve a maturity level, 70% of the characteristics of that level must be evident. In the illustration below, green indicates that Jamaica has achieved this for Level 1 maturity in the Organization & Structure and the Grid Operations domains. Yellow and red reflect varying progress in developing a maturity level’s characteristics.



Figure 11: Jamaica SGMM Results

Strategy, Management and Regulation: This domain evaluates the degree to which management mechanisms are in place to guide and advance the smart grid program. A smart grid vision and strategy are an expected characteristic. Jamaica’s results reflect the lack of an explicit smart grid vision and strategy for Jamaica.

Organization and Structure: This domain evaluates the structure, culture, and communications in place to support a smart grid transformation. Key characteristics in this domain relate to an organizational structure, policies, and processes to promote and reward cross functional planning, design, and operations. JPS’s actions to support smart grid technologies through assigning budget and resources (e.g., Residential Automated Metering Infrastructure program and grid automation pilots) are the reason for achieving Level 1 maturity.

Grid Operations: This domain covers advanced grid observability and grid control. Jamaica is designated Level 1 due to the initial steps taken evaluating distribution network observability (e.g., the Power Quality meter trial on distribution feeders) and automation technologies (e.g., smart switch deployment).

Work & Asset Management: This domain measures the degree to which asset operation incorporates fact-based performance data, enabling the evolution from reactive to predictive maintenance and the more efficient use of resources. Although not reflected in the current state assessment, the designation of an asset management department and developing plans for an asset management solution will increase scores in this domain.

Technology: This domain evaluates the information management capabilities present to connect and support the smart grid-enabled data sources and users. The alignment of JPS’ enterprise IT architecture to smart grid capabilities and incorporating smart grid-enabling applications in design considerations provided JPS with strong scores across maturity Levels 1, 2, and 3.



Customer: This domain evaluates the degree to which customer are provided options and capabilities to manage their energy usage and costs. The existing smart meter program achieved many of the characteristics expected in Levels 1, 2, and 3 (e.g., remote connect/disconnect and provision of energy usage information).

Value Chain Integration: This domain evaluates capabilities managing demand and a diverse set of supply resources beyond traditional boundaries (e.g., distributed energy resources provided by customers and other 3rd parties). JPS’s efforts to identify distributed generation sources and the capabilities to support them as well as the identification of security requirements to enable interaction with 3rd parties are represented by the progress to achieving Level 1 characteristics.

Societal & Environmental: This domain covers conservation and green initiatives, sustainability, economics and the ability to integrate alternative and distributed energy. Energy efficiency programs and the provision of consumption data to customers through the Residential Automated Metering Infrastructure system provided Jamaica some progress in this domain.

Jamaica’s assessment across many of the domains is in line with utilities that complete the Smart Grid Maturity Model for the first time (See Figure 12). The characteristics described in the model have often not been articulated in a utility that has been operating without smart grid technologies. However, the comparison to the peer group is a helpful reference point for smart grid planning discussion in which utilities decide which characteristics would provide value to their stakeholders.

Figure 12: JPS SGMM Assessment Results

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1

2

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5

Peer average Jamaica Public Service Company

SGMM Peer Community Data (?250K Meters)SGMM Peer Community Data (>250K Meters)

Average and Range



4.3 Smart Grid Maturity Model Aspirations

To build off the baseline smart grid capabilities identified in the SGMM assessment, a second SGMM workshop was conducted on September 25, 2013 with representation from the Ministry of Science, Technology, Energy, and Mining (MSTEM), Jamaica Public Services Company (JPS), the Office of Utilities Regulation (OUR), the Petroleum Corporation of Jamaica (PCJ) and IBM. The session reviewed the results from the current state Smart Grid Maturity Model assessment and compared the results with other utilities in the >250,000 meter benchmark. Based on this discussion, the working group identified future-state capabilities for Jamaica’s electrical network at different time horizons (See Figure 13).

Figure 13: Jamaica Smart Grid Future-State Aspirations

The use of three time horizons for the planning discussion allows for addressing the highest priority areas in the next few years, incorporating additional priorities in seven years as investments and policies demonstrate progress, and finally pursuing additional areas by 2030 as their value to Jamaica’s stakeholders is confirmed.

For each domain, the process of identifying target capabilities was based on a practical discussion incorporating a solid rationale, acknowledgement of obstacles, and the development of a preliminary action plan (See Appendix for a full discussion on each domain).

000

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Jamaica todayJamaica today

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Jamaica 2030 aspirationsJamaica 2030 aspirations

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222Jamaica 2016 aspirationsJamaica 2016 aspirations



4.3.1 Strategy, Management and Regulation (SMR):

Aspirations: Jamaica shall target Level 3 maturity by 2016 and achieving Level 4 by 2020 to be maintained through 2030 (See Figure 14).

This domain evaluates the degree to which management mechanisms are in place to guide and advance the smart grid program. These aspirations are intended to formalize the smart grid program so that the investments are guided by an encapsulating vision which will assist with external stakeholder alignment and a management approach designed to realize benefits across smart grid investments.

Figure 14: Jamaica Strategy, Management, & Regulation Domain Aspirations

5

5.3 New business model opportunities emerge as a result of smart grid capabilities and are implemented.

5.2 Smart grid business activities provide sufficient financial resources to enable continued investment in smart grid sustainment and expansion.

5.1 Smart grid strategy capitalizes on smart grid as a foundation for the introduction of new services and product offerings.

44.3 Smart grid strategy is shared and revised collaboratively with external stakeholders.

4.2 Smart grid is a core competency throughout the organization.

4.1 Smart grid vision and strategy drive the organization’s strategy and direction.

3

3.4 Required authorizations for smart grid investments have been secured.

3.3 Smart grid leaders with explicit authority across functions and lines of business are designated to ensure effective implementation of the smart grid strategy.

3.2 A smart grid governance model is established.

3.1 The smart grid vision, strategy, and business case are incorporated into the vision and strategy.

2

2.6 There is support and funding for conducting proof-of-concept projects to evaluate feasibility and alignment.

2.5 There is collaboration with regulators and other stakeholders regarding implementation of the smart grid vision and strategy.

2.4 Budgets are established specifically for funding the implementation of the smart grid vision.

2.3 Operational investment is explicitly aligned to the smart grid strategy.

2.2 A common smart grid vision is accepted across the organization.

2.1 An initial smart grid strategy and a business plan are approved by management.

11.3 Discussions have been held with regulators about the organization’s smart grid vision.

1.2 Experimental implementations of smart grid concepts are supported.

1.1 Smart grid vision is developed with a goal of operational improvement.

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20302030

20202020

20162016



4.3.2 Organization and Structure (OS):


This domain evaluates the structure, culture, and communications in place to support a smart grid transformation. Aspirations in this domain were devised to support the execution of the smart grid vision and strategy with a well considered management structure based on the appropriate measurement, communications, and training.

Figure 15: Jamaica Organization & Structure Domain Aspirations

5

5.3 Channels are in place to harvest ideas, develop them, and regard those who help shape future advances in process, workforce competencies, and technology.

5.2 The organization is able to readily adapt to support new ventures, products, and services that emerge as a result of smart grid.

5.1 The organizational structure enables collaboration with other grid stakeholders to optimize overall grid operation and health.

4

4.3 Decision making occurs at the closest point of need as a result of an efficient organizational structure and the increased availability of information due to smart grid.

4.2 There is end-to-end grid observability that can be leveraged by internal and external stakeholders.

4.1 Management systems and organizational structure are capable of taking advantage of the increased visibility and control provided through smart grid.

3

3.6 Education and training are aligned to exploit smart grid capabilities.

3.5 A matrix or overlay structure to support smart grid activities is in place.

3.4 Leadership is consistent in communication and actions regarding smart grid.

3.3 Performance and compensation are linked to smart grid success.

3.2 Smart grid measures are incorporated into the measurement system.

3.1 The smart grid vision and strategy are driving organizational change.

2

2.5 The linking of performance and compensation plans to achieve smart grid milestones is in progress.

2.4 Education and training to develop smart grid competencies have been identified and are available.

2.3 Most smart grid implementation and deployment teams include participants from all functions and LOBs that the deployment will impact.

2.2 The organization has aligned most operations around end-to-end processes.

2.1 A new vision for a smart grid begins to drive change and affect related priorities like addressing the need for an adequately skilled workforce in a smart grid environment.

11.3 Smart grid awareness efforts to inform the workforce of smart grid activities have been initiated.

1.2 Leadership has demonstrated a commitment to change the organization in support of achieving smart grid.

1.1 The organization has articulated its need to build smart grid competencies in its workforce.

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20302030

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4.3.3 Grid Operations (GO):


As this domain covers advanced grid observability and grid control, aspirations in this domain are intended to enable JPS to improve reliability and prepare for increased renewable generation penetration while operating the network more efficiently.

Figure 16: Jamaica Grid Operations Domain Aspirations

55.2 System-wide, analytics-based, and automated grid decision making is in place.

5.1 Self-healing capabilities are present.

4

4.5 There is automated decision-making within protection schemes that is based on wide-area monitoring.

4.4 Grid operations information has been made available across functions and LOBs.

4.3 Operational forecasts are based on data gathered through smart grid.

4.2 Grid operational management is based on near real-time data.

4.1 Operational data from smart grid deployments is being used to optimize processes across the organization.

3

3.6 There is automated decision-making within protection schemes.

3.5 Grid data is used by an organization’s security functions.

3.4 Smart meters are important grid management sensors.

3.3 Grid operations planning is now fact-based using grid data made available by smart grid capabilities.

3.2 Control analytics have been implemented and are used to improve cross-LOB decision-making.

3.1 Smart grid information is available across systems and organizational functions.

2

2.4 Investment in and expansion of data communications networks in support of grid operations is underway.

2.3 Aside from SCADA, piloting of remote asset monitoring of key grid assets to support manual decision making is underway.

2.2 Advanced outage restoration schemes are being implemented, which resolve or reduce the magnitude of unplanned outages.

2.1 Initial distribution to substation automation projects are underway.

1

1.5 Safety and security (physical and cyber) requirements are considered.

1.4 Outage and distribution management systems linked to substation automation are being explored and evaluated.

1.3 Proof-of-concept projects and component testing for grid monitoring and control are underway.

1.2 New sensors, switches, and communications technologies are evaluated for grid monitoring and control.

1.1 Business cases for new equipment and systems related to smart grid are approved.



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4.3.4 Work & Asset Management (WAM):

Aspirations: Jamaica shall target Level 2 maturity by 2016, Level 3 by 2020, and Level 4 by 2030 (See Figure 17).

This domain measures the degree to which asset operation incorporates fact-based performance data, enabling the evolution from reactive to predictive maintenance and the more efficient use of resources. The aspirations in this domain are intended to support reliability improvement while achieving capital and operational expenditure reductions in areas such as workforce management, asset maintenance, and inventory management.

Figure 17: Jamaica Work & Asset Management Domain Aspirations

20302030

20202020

20162016

5

5.2 Assets are leveraged to maximize utilization, including just-in-time asset retirement, based on smart grid data and systems.

5.1 The use of assets between and across supply chain participants is optimized with processes defined and executed across the supply chain.

4

4.4 Service life for key grid components is managed through condition-based and predictive maintenance, and is based on real and current asset data.

4.3 Performance and usage of assets is optimized across the asset fleet and across asset classes.

4.2 Asset models are based on real performance and monitoring data.

4.1 A complete view of assets based on status, connectivity, and proximity is available to the organization.

3

3.7 Modeling of asset investments for key components is underway.

3.6 Asset inventory is being tracked using automation.

3.5 An integrated view of GIS and asset monitoring is in place.

3.4 Integration of remote asset monitoring with mobile workforce systems, in order to automate work order creation, is underway.

3.3 Remote asset monitoring capabilities are integrated with asset management.

3.2 CBM programs for key components are in place.

3.1 Performance, trend analysis, and event audit data are available for components of the organization’s systems.

2

2.3 An organization-wide mobile workforce strategy is in development.

2.2 An integrated view of GIS for asset monitoring based on location, status, and interconnectivity (nodal) has been developed.

2.1 An approach to track, inventory, and maintain event histories of assets is in development.

1

1.3 Asset and workforce management equipment and systems are being evaluated for their potential alignment to the smart grid vision.

1.2 Potential uses of remote asset monitoring are being evaluated.

1.1 Enhancements to work and asset management have been built into approved business cases.

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4.3.5 Technology (TECH):


This domain evaluates the information management capabilities present to connect and support the smart grid-enabled data sources and users. These aspirations are intended to provide a foundational capability in information management and network communications which will support key business areas, such as asset management and grid operations, with improved ability to monitor the grid across a variety of data sources.

Figure 18: Jamaica Technology Domain Aspirations

55.2 The enterprise information infrastructure can automatically identify, mitigate, and recover

from cyber incidents.

5.1 Autonomic computing and machine learning are implemented.

4

4.6 Security strategy and tactics continually evolve based on changes in the operational environment and lessons learned.

4.5 Performance is improved through sophisticated systems that are informed by smart grid data.

4.4 Predictive modeling and near real-time simulation are used to optimize support processes.

4.3 Systems have sufficient wide-area situational awareness to enable real-time monitoring and control for complex events.

4.2 Business processes are optimized by leveraging the enterprise IT architecture.

4.1 Data flows end to end from customer to generation.

3

3.6 A detailed data communication strategy and corresponding tactics that cross functions and LOBs are in place.

3.5 The organization has an advanced sensor plan.

3.4 The use of advanced distributed intelligence and analytical capabilities are enabled through smart grid technology.

3.3 Smart grid-specific technology has been implemented to improve cross-LOB performance.

3.2 Systems adhere to an enterprise IT architectural framework for smart grid.

3.1 Smart grid-impacted business processes are aligned with the enterprise IT architecture across LOBs.

2

2.7 Security is built into all smart grid initiatives from the outset.

2.6 Pilots based on connectivity to distributed IEDs are underway.

2.5 There is a data communications strategy for the grid.

2.4 A common technology evaluation and selection process is applied for all smart grid activities.

2.3 Standards are selected to support the smart grid strategy within the enterprise IT architecture.

2.2 Changes to the enterprise IT architecture that enable smart grid are being deployed.

2.1 Tactical IT investments are aligned to an enterprise IT architecture within an LOB.

1

1.5 There is a process to evaluate and select technologies in alignment with smart grid vision and strategies.

1.4 Opportunities are identified to use technology to improve departmental performance.

1.3 A change control process is used for applications and IT infrastructure.

1.2 Existing or proposed IT architectures have been evaluated for quality attributes that support smart grid applications.

1.1 An enterprise IT architecture exists or is under development.




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4.3.6 Customer (CUST):


This domain evaluates the degree to which customer are provided options and capabilities to manage their energy usage and costs. The aspirations in this domain are intended to continue the focus on loss management while providing customers an expanded set of options for managing electricity costs, including energy management tools and prepayment.

Figure 19: Jamaica Customer Domain Aspirations

5

5.5 The organization plays a leadership role in industry-wide information sharing and standards development efforts for smart grid.

5.4 Security and privacy for all customer data is assured.

5.3 Plug-and-play, customer-based generation is supported.

5.2 There is automatic outage detection at premise or device level.

5.1 Customers can manage their end-to-end energy supply and usage levels.

4

4.7 A common customer experience has been integrated.

4.6 In-home net billing programs are enabled.

4.5 Automatic response to pricing signals for devices within the customer’s premise is supported.

4.4 Residential customers participate in demand response and/or utility-managed remote load control programs.

4.3 Customers have access to near real-time data on their own usage.

4.2 There is outage detection and proactive notification at the circuit level.

4.1 Support is provided to customers to help analyze and compare usage against all available pricing programs.

3

3.9 All customer products and services have built-standards based on security and privacy controls.

3.8 Customer education on how to use smart grid services to curtail peak usage is provided.

3.7 Common experience has been implemented across two or more customer interface channels.

3.6 Residential customers have on-demand access to daily usage data.

3.5 There is automatic outage detection at the substation level.

3.4 Demand response and/or remote load control is available to customers.

3.3 A remote connect/disconnect capability is deployed.

3.2 Two-way meter communication has been deployed.

3.1 The organization tailors programs to customer segments.

2

2.6 Security and privacy requirements for customer protection are specified for smart grid-related pilot projects and RFPs.

2.5 The impact on the customer of new services and delivery processes is being assessed.

2.4 Remote connect/disconnect is being piloted for residential customers.

2.3 The organization is modeling the reliability of grid equipment.

2.2 The organization has frequent (more than monthly) knowledge of residential customer usage.

2.1 Pilots of remote AMI/AMR are being conducted or have been deployed.

1

1.4 The utility consults with public utility commissions and/or other government organizations concerning the impact on customers.

1.3 A vision of the future grid is being communicated to customers.

1.2 Security and privacy implications of smart grid are being investigated.

1.1 Research is being conducted on how to use smart grid technologies to enhance the customer’s experience, benefits, and participation.

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4.3.7 Value Chain Integration (VCI):


This domain evaluates capabilities managing demand and a diverse set of supply resources beyond traditional boundaries (e.g., distributed energy resources provided by customers and other 3rd parties). The aspirations in this domain are intended to prepare for customer demand relating to a wider set of offerings (e.g., distributed generation, demand response) and the emergence of new energy models, which include third party providers. These aspirations will allow JPS to manage a diverse portfolio of grid resources in support of more effective and efficient grid operation as it prepares for new market models.

Figure 20: Jamaica Value Chain Integration Domain Aspirations

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5.3 The organization’s automated control and resource optimization schemes consider and support

regional and/or national grid optimization.

5.2 Resources are adequately dispatchable and controllable so that the organization can take

advantage of granular market options.

5.1 The optimization of energy assets is automated across the full value chain.

4

4.4 Visibility and potential control of customers’ large-demand appliances to balance demand and

supply is available.

4.3 Secure two-way communications with Home Area Networks (HANs) are available.

4.2 Portfolio optimization models that encompass available resources and real-time markets are

implemented.

4.1 Energy resources (including Volt/VAR, DG, and DR) are dispatchable and tradable.

3

3.4 Security management and monitoring processes are deployed to protect the interactions with an

expanded portfolio of value chain partners.

3.3 Additional resources are available and deployed to provide substitutes for market products to

support reliability or other objectives.

3.2 Customer premise energy management solutions with market and usage information are enabled.

3.1 An integrated resource plan is in place and includes new targeted resources and technologies.

2

2.4 Secure interactions have been piloted with an expanded portfolio of value chain partners.

2.3 Pilots to support a diverse resource portfolio have been conducted.

2.2 The value chain has been redefined based on its smart grid capabilities.

2.1 Support is provided for energy management systems for residential customers.

1

1.5 Security requirements to enable interaction with an expanded portfolio of value chain partners have

been identified.

1.4 There is a strategy for creating and managing a diverse resource portfolio.

1.3 Energy storage options and the capabilities needed to support them are identified.

1.2 Distributed generation sources and the capabilities needed to support them are identified.

1.1 Assets and programs necessary to facilitate load management are identified.

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implemented.


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been identified.





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4.3.8 Societal & Environmental (SE):


This domain covers conservation and green initiatives, sustainability, economics and the ability to integrate alternative and distributed energy. The aspirations in this domain are intended to support Jamaica’s energy goals aimed at achieving environmental sustainability and the development of renewable energy sources by incorporating environmental impact in decision making. These aspirations include the development of a regulatory approach that supports JPS with returns on its investments to support energy efficiency and conservation.

Figure 21: Jamaica Societal & Environmental Domain Aspirations

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5.3 The organization is a leader in developing and promoting industry-wide resilience best practices

and/or technologies for protection of the national critical infrastructure.

5.2 Customers control their energy-based environmental footprints through automatic optimization of

their end-to-end energy supply and usage level (energy source and mix).

5.1 Triple bottom line goals align with local, regional, and national objectives.

4

4.5 The organization fulfills its critical infrastructure assurance goals for resiliency, and contributes to

those of the region and the nation.

4.4 End-user energy usage and devices are actively managed through the utility’s network.

4.3 Programs are in place to shave peak demand.

4.2 A public environmental and societal scorecard is maintained.

4.1 The organization collaborates with external stakeholders to address environmental and societal

issues.

3

3.4 The organization regularly reports on the sustainability and the societal and environmental impacts

of its smart grid programs and technologies.

3.3 Programs to encourage off-peak usage by customers are in place.

3.2 Segmented and tailored information that includes environmental and societal benefits and costs is

available to customers.

3.1 Performance of societal and environmental programs are measured and effectiveness is

demonstrated.

2

2.5 Increasingly granular and more frequent consumption information is available to customers.

2.4 Environmental proof-of-concept projects are underway that demonstrate smart grid benefits.

2.3 The organization considers a “triple bottom line” view when making decisions.

2.2 Energy efficiency programs for customers have been established

2.1 Smart-grid strategies and work plans address societal and environmental issues.

1

1.4 The smart grid vision or strategy specifies the organization’s role in protecting the nation’s critical

infrastructure.

1.3 Environmental compliance performance records are available for public inspection.

1.2 The environmental benefits of the smart grid vision and strategy are publicly promoted.

1.1 The smart grid strategy addresses the organization’s role in societal and environmental issues.

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issues.

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demonstrated.

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infrastructure.




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5 Smart Grid Roadmap

Jamaica’s Smart Grid Roadmap has been devised to meet Jamaica’s short- and long-term goals. Short-term initiatives have been designed to address high electricity costs and reliability issues while developing the foundation for Jamaica’s long-term energy independence and sustainability goals. As the fuel cost reduction benefits of Jamaica’s generation expansion program are realized, longer-term initiatives enable Jamaica’s ability to adjust the energy supply mix while continuing to achieve performance and efficiency objectives.

Jamaica’s Smart Grid Roadmap consists of a series of work streams supported by programs (See Figure 22). The work streams and supporting programs are:

• Information Management

• Loss Management

• Customer Conservation and Energy Efficiency

o Prepayment

o Smart Buildings

o Smart Water

o Dynamic Rates

• Asset Management

• Grid Operations

o Distribution Automation

o Renewable Integration (Utility Scale)

o Distributed Resources

Figure 22: Smart Grid Roadmap Overview

Grid Operations


Asset Management


Loss Management

Work Stream 2013-2016 2017-2020 2021-2030

Grid Operations


Asset Management


Loss Management

Work Stream 2013-2016 2017-2020 2021-2030

Foundational ProgramEnhanced Program

Legend

Loss Management

Smart Water

Smart Buildings

Asset Management


Renewable Integration


Dynamic Rates


Prepayment



Each program is described in this section, highlighting what has already been done in the area and the rationale for the proposed initiatives. Cost and benefit drivers are included for each program and a detailed value discussion is presented in the following section of the report.

5.1 Information Management

Currently, most of JPS’s substations are visible in SCADA utilizing fiber to urban substations and microwave to rural substations. SCADA has visibility to some feeders down to reclosers. In addition to SCADA for grid operations, JPS utilizes public network providers for communications to the deployed Smart Meters.

Data collection and management are foundational to achieving smart grid capabilities. As new higher functioning devices (already available on the market) are procured and deployed, the benefits derived from these devices are limited by current communications and ‘back-end’ information management capabilities.

Investments on the Smart Grid Roadmap will expand the number of electric network monitoring and control devices that require a communications network. To support the low latency communication requirements to these devices, public networks in Jamaica are a viable option. Global examples demonstrate utilities building their own communication networks to better manage the service level requirements and costs. A private network investment could be supported in Jamaica with a consortium approach to share costs across stakeholders (e.g., JPS, National Water Commission and emergency services). Further, a hybrid approach would allow for the building of a private network in dense device and population areas, supported by public networks in rural settings. The planning and evaluation of these approaches are incorporated in the roadmap.

To provide information management capabilities, modern smart grid information architectures address the collection and treatment of additional data available from improved Intelligent Electronic Devices (IEDs). Information collected from IEDs within substations, as well as devices in the field, is aggregated and analysed at multiple levels including the enterprise level, the network operations level, regional office and the substation level. Timely availability of information at these levels enables such capabilities as system-wide fault location and anticipation, asset conditioning monitoring and maintenance, power quality monitoring and eventually, improved visibility to the customer.

The target architecture should address where the data is stored, processed and analysed as well as where it is expected to be displayed and what interconnections are required between data acquisition points and storage points. Future device, transport and application projects must take into account this target interconnected state.

The target architecture should make specific provision for structured data stores of high volumes of measurement and event data through the use of a data historian and by using corporate data warehousing/analytics investments (e.g., the current historian deployed for transmission). A data historian is a critical tool in the management of this largely time-series information. Modern historians are able to manage extremely large volumes of data from a variety of sources with multiple data frequencies and latencies.

Investments in this work stream will enable the progression toward near-real time operational data in the short-term (2016) and automated decision making and predictive operational data modelling in the medium term (2020)



5.1.1 Initiative Descriptions

Figure 23: Information Management Initiatives

• Network Communications Design - Communications architecture design to meet communication requirements to transport device data to operational and business applications, including the evaluation of different network ownership scenarios (e.g., a public private partnership or consortium approach that shares the investment requirements across stakeholders, such as the National Water Commission or emergency services)

• Information Architecture Design - Information architecture design initiative to manage device data flows and provision available data for use internally and externally to JPS. In addition to JPS network operation and planning functions, the information architecture should consider external users, such as customers, distributed generation providers and other 3rd party stakeholders.

• Information Architecture Deployment

• Network Communications Deployment

Additionally, to support the development of JPS’s data collection and information management capabilities, MSTEM and GoJ should support:

• Network Communications Coordination - Coordination of communications network investment across Jamaica’s stakeholders (e.g., JPS, National Water Commission, emergency services) that optimizes cost across stakeholders

• IT Investment Framework – Regulatory support for investment in information technology components identified in the information architecture, acknowledging their role in achieving network performance objectives (e.g., reliability improvement, increased asset efficiency), with investment support including the ongoing costs associated with managing the data (e.g., data management and maintenance of accurate data stores)

• Data Standards - Development of data provision requirements and standards (e.g., integration standards between JPS and stakeholders)

• Security Standards - Development of mandatory cyber security standards to address the potential for cyber attacks

5.1.2 Cost Drivers

• Network Communications Deployment initiative

Work Stream Program 2013-2016 2017-2020 2021-2030Work Stream Program 2013-2016 2017-2020 2021-2030


Network Communications Design

Information Architecture Design

Information Architecture Deployment


Network Communications Deployment

Planned/Existing JPS Initiatives

Proposed JPS Initiatives

Legend

MSTEM/GoJ Initiatives



Legend


• Network Communications Coordination • IT Investment Framework• Data Standards• Security Standards



o WiMAX Bay Stations

o PTP Microwave Backhaul

o Installation

• Information Architecture Deployment initiative

o Enterprise Service Bus

o Data Historian Configuration (e.g., the current historian deployed for transmission)

o IT Hardware

o Implementation and configuration labor

5.1.3 Benefits Drivers

• Foundational across the Smart Grid Roadmap enabling data transport and management

• Shared private network communication costs across stakeholders (e.g., National Water Commission, emergency services) provide savings in comparison to public network providers. In some examples, 40% savings to stakeholders (i.e., cost charge back is 40% less than payment to 3rd party service provider)

5.2 Loss Management

Loss management is an area of ongoing focus in Jamaica due to the high degree of energy theft. With OUR limits on the amount of loss which can be passed on to the customers, it’s a problem for JPS and the country.

JPS is deploying a meter hardening solution in the highest loss areas. In addition, a feeder meter program has been deployed to assist with identifying feeders where consumption doesn’t reconcile with billing. Meanwhile, JPS has four AMI solutions deployed.

Given the magnitude of losses within the system and the costs to JPS in not addressing these issues as quickly as possible, the Smart Grid Roadmap supports a systematic approach to balance costs with benefits to help JPS reach their goals in an orderly manner. The approach is designed to recognize the following:

• The level of deployment of AMI across the feeders is not consistent and may not support accurate theft detection

• The amount and nature of theft varies from feeder to feeder

• The demographics varies across feeders and therefore so does the nature of theft

• The approaches used on each feeder will vary as will the costs

• Enterprise technology deployment costs may take multiple years further delaying benefits

• The potential for benefits in the short to near term varies depending on the approaches taken

The approach begins by developing the objectives and approaches, prioritizing the feeders and then developing the cost/benefit model (See Figure 24).



Figure 24: Loss Management Approach

1. Objectives: ROI, time frame, etc.

2. Approaches: Hardening, AMI analytics, energy balancing, site inspections, etc.

3. Feeder Prioritization: Level of loss, demographics, approaches, costs, AMI deployment, time, etc.

4. Deployment Plan: The technology deployment and yearly feeder remediation plan

5. Business Case: Year to year costs and target losses.

By approaching the loss management issues systematically JPS will avoid large investments in single technologies and have the advantage of field testing approaches and measuring costs versus benefits as the program progresses. These findings will aid JPS in altering the order and approaches as success is measured.

Approaches

Utilities are employing different approaches to address different types of non-technical loss, including review and refinement of back-office processes, increased frequency of field visits, hardening of assets (e.g. central metering in cabinets), increased network sensors including AMI meters, and energy analytics (e.g., predicted versus actual consumption, consumption/voltage anomaly detection) (See Figure 25).



Figure 25: Non Technical Losses Possible Recovery Actions

Each of these approaches has varying costs and implementation time frames. IBM recognizes that JPS needs to validate the approaches and benefits in the short to medium term. Each approach can be implemented with as minimal technology investment as possible to ensure benefits can be realized earlier and large investments (e.g., back-office and field) do not become stranded. For example, data is the foundation of analytical functions. It is our experience that approximately 75% of effort in deploying a successful solution involves getting processes and technology to maintain and hold accurate data. Rather than JPS invest significant effort in deploying enterprise technologies (e.g. Meter Data management System) and processes to achieve the desired goal, limited deployment can be achieved with targeted solutions using spread sheet or rudimentary data models in a compliant SQL database. The approach will advocate at what point in the roadmap JPS will require the deployment of processes, technology and skills to support the continued deployment of a successful loss management program.

Measuring Success – Adaptable Road Map

As already mentioned the success of approaches will vary by feeder. As the feeder remediation progresses, JPS must continually measure the success of the approaches and the order of feeder/technology plans to ensure that the objectives are being met. The result will change the roadmap which must be adapted continually to the realities of the remediation experience (See Figure 26).

Non Technical Losses

Non Technical

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Inaccurate MetersInaccurate Meters

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Figure 26: Approach Adaptation

1. Measure Theft: How much energy is being lost prior to approaches being implemented

2. Implement Approaches on Feeders: Execute the approach plan

3. Measure Results: Current level of loss, costs and time

4. Adjust or Change Approaches and Priorities: Based on results adjust the feeder approaches, introduce new approaches and re-prioritize as necessary

5. Update Roadmap: Update the over-all roadmap as necessary




Figure 27: Loss Management Initiatives

• Loss Management Plan Creation

o Create the objectives of the feeder remediation detailing savings, time and constraints.

• Feeder Loss Assessment - Perform the feeder by feeder remediation assessment, utilizing feeder meter deployment with a connectivity model to enable localized loss calculation. Utilize additional loss detection analytics to identify loss across the entire customer base and address sophisticated energy theft schemes

• Feeder Loss Strategies - Develop Feeder loss curtailment strategies with costs and technology availability

o Development of process and technology plan

o Develop the business case

• Ongoing Refinement - Measure, execute the plan, measure and revise plan

Additionally, to further the loss management program, MSTEM and GoJ should support the design and execution of:

• Electric Theft Legislation - Theft penalty legislation (with appropriate penalties) to support the theft detection effort and provide particular focus on organized energy theft (e.g., providers enabling wide-scale theft through electrician services)

• Customer Theft Outreach - Customer education outreach on the theft topic to support JPS’s energy loss communication program

• Theft Data Policy - Customer data policy to dictate how customer data can be used to police for unusual, illegal behaviour


Loss Management

Loss Management Plan Creation

Loss Management



Legend




Legend


Feeder Loss Assessment

Feeder Loss Strategies

Ongoing Refinement

Current Smart Meter Project

• Customer Theft Outreach• Theft Data Policy• Electric Theft Legislation



5.2.2 Costs Drivers

• Plan Creation

• Labor for data management

• Data storage software and hardware (potentially MDMS module)

• Data archiving

• Meters


• Reduced losses to meet OUR target of 17.5% loss cap – Last year, US$30 Million in lost energy was not recovered by JPS (i.e., losses in excess of the 17.5% electricity loss allowance)

• Reduced unbilled consumption improves network performance – Metered electricity consumption over 30% less than unmetered usage for customers that have been receiving no-cost electricity

5.3 Customer Conservation and Energy Efficiency - Prepayment

Prepayment for electricity service is being explored by JPS. The latest smart meter selection and deployment supports prepayment functionality and plans are underway for a prepayment pilot evaluating a central management option as well as a meter controlled option (e.g., using a card at the meter).

Limited experience in North America and global examples, such as Meralco in the Philippines, demonstrate the additional energy cost control that prepayment programs give customers. In addition, prepayment lowers utility debt write-offs by limiting bad debt exposure and provides a mechanism to incorporate arrears payments into the prepayment program.

Findings demonstrate significant improvements in bad debt write offs due to prepayment offerings (e.g., 50% reductions) with increased customer satisfaction and engagement in their electricity consumption. These experiences show customers reducing overall consumption (e.g., 10% reduction) and achieving bill savings (e.g., 6% reductions) even with higher rates for electricity purchased through these programs. (Source: Wimberly, Jamie. "Connecting with Customers." Proc. of NARUC Summer Meeting. DEFG, July 2013. Web. 12 Aug. 2013; http://www.azcentral.com/business/articles/20100711biz-prepaid-power-srp-rates0711.html#ixzz2eANCZQfC)

Design considerations for Jamaica’s prepayment program are in the following areas:

• Target customer segments for the volunteer program

• Centralized (requires meter remote disconnect/connect) vs. meter-level account management

• Timing/frequency of consumption pricing, charging, and customer account updates

• Account “wallet” thresholds

• Customer notification requirements (e.g., low balance, disconnect warning, emergency credit)



• Customer feedback mechanism with the cost projections and budget management information available

• Customer payment options (e.g., 3rd party vending networks, SMS, portals) and methods (e.g., credit/debit card, telco account)

• Rate plan switching ability (e.g., prepay to postpay, rate plans)

In addition, JPS will need to evaluate technology choices for the back-office payment engine which will manage calculations and triggers. The scope of the take-up will dictate the need for additional meters beyond the planned smart meter rollout.


Figure 28: Prepayment Program Initiatives

• Prepayment Pilot

• Prepayment Program Definition - Development of disconnection/reconnection policy to document the customer notification requirements, customer communication channels, and grace periods

• Prepayment Partnerships - Develop partnership arrangements between JPS and payment agencies, including telecommunication companies

• Prepayment Solution Implementation – Implement a payment engine to support the bill calculation and triggers of a prepayment program

• Meter Data Management System – Data management system to support the prepayment solution and the larger scale of smart meter rollout

Additionally, to further the prepayment program, MSTEM and the GoJ should support:

• Prepayment Policy - Definition of a disconnection/reconnection policy equitable to customers and JPS and the development of a prepayment rate and policy on the distribution of initiation costs to support the rollout of the program


Energy Efficiency & Customer

Conservation

Prepayment

Prepayment Pilot

Prepayment Program Definition

Prepayment Partnerships

Prepayment Solution Implementation



Legend




Legend


Prepayment Policy

Limited Smart Meter Expansion for Prepayment


Meter Data Management System



5.3.2 Costs Drivers

• Prepayment-enabled meters, with disconnect

• Customer feedback mechanism (e.g., in-home display, SMS, IVR)

• Payment mechanism (e.g., kiosks, partners)

• Payment engine (e.g., back-office calculations, triggers) and supporting systems


• Increased Customer payment process efficiency due to automated processes

• Reduced customer activation and de activation process due to automation

• Improved cash flow, with payment earlier

• Minimized financial losses to protected customers

• Increased customer control of electricity costs

5.4 Customer Conservation and Energy Efficiency – Smart Buildings

Jamaica has undertaken an Energy Efficiency and Conservation project which includes enabling the efficiency of buildings through retrofits in the areas of cold roofing, solar tinting, air conditioning and lights.

Due to high energy costs, such as those in Jamaica, and the fact that energy costs represent 23 percent of the total occupancy costs of facilities (“IBM Smarter Buildings Survey: Customers Rank their Office Buildings,” page 2. April 29, 2010. http://www-03.ibm.com/press/attachments/ IBM_Smarter_Buildings_Survey_White_Paper.pdf), the value of reducing facility energy use is clear.

In addition to these important steps to support energy efficiency, Smart Buildings can include all the elements of monitoring and managing occupancy (e.g., financial, operational, and asset efficiency).

Organizations achieve their environment and energy management goals by recognizing the use of three key tactics:

• Operations and maintenance – Identify operational improvements to help reduce facilities maintenance downtime and costs, including proactively maintaining facilities, as well as making sure equipment is operating at peak efficiency

• Portfolio and project management - Identify priorities for funding allocations, analyse project risks and financial benefits, and manage project management controls and alerts

• Facilities space management – Identify areas of improvement to increase utilization of leased assets and reduce the number of facilities across the organization, which in turn generates increased return on assets

The features and capabilities of an effective environmental and energy management solution should address the following key areas:



1. Energy data capture and analysis - The ideal energy management solution would streamline and automate environmental and energy performance measurements. It would also provide real-time monitoring, simplify reporting and ease data quality audits.

2. Facilities operations and maintenance - The number-one tactic used by organizations that achieve their energy reduction goals is making operational improvements to help reduce facilities maintenance downtime and costs (IBM, “Crossing the sustainability chasm.” May 2012. http://www.ibm.com/common/ssi/cgi-bin/ssialias?subtype=WH&infotype=SA&appname=SWGE_TI_EA_USEN&htmlfid=TIL14006USEN&attachment=TIL14006USEN.PDF). In fact, using this tactic, organizations can cut energy costs by 10 to 20 percent with minimal capital investment. (Federal Energy Management Program, “Operations & Maintenance Best Practices: A Guide to Achieving Operational Efficiency.” August 2010. http://www1.eere.energy.gov/femp/pdfs/omguide_complete.pdf). Proactively maintaining facilities, as well as making sure equipment is operating at peak efficiency, are proven strategies to reduce energy costs. Some environmental and energy management solutions go so far as to automatically trigger maintenance work orders.

3. Portfolio and project management - Organizations seeking to achieve environmental and energy reduction goals should find an energy management solution that can identify priorities for funding allocations, analyse project risks and financial benefits, and automate project management controls and alerts.

4. Facilities space management - The right energy management solution should simplify the facilities planning process and identify areas of improvement, helping to determine the energy impact of the space, facility objectives and performance goals. It should help assess and increase utilization of leased assets and reduce the number of facilities across the organization.

A good technology solution (e.g., an Integrated Workplace Management Systems) to support these approaches is one that provides greater instrumentation at all levels to help identify which facilities to target.

An Integrated Workplace Management Systems (IWMS) should identify operating anomalies within energy consuming equipment such as HVAC units and automate corrective actions. It should provide integrated analysis tools that analyze and compare potential efficiency measures to optimize the financial and environmental returns from energy reduction investments. The ideal IWMS will deliver true integration across operational modules for maintenance, project management and space planning to accelerate successful implementation and ensure the projected returns are realized.

In addition to public sector buildings, healthcare, education, and some commercial facilities are candidates for a coordinated approach across these building management tactics. The roadmap describes initiatives to advance efficient building management in the public sector and initiatives to drive these practices further into Jamaica’s buildings.




Figure 29: Smart Buildings Initiatives

• Building Data Collection - Data collection initiative to identify building inventory and the current performance of building management to track progress and track the performance of assets

• Building Sub-Meters - Sub metering within a building or sensors deployment that allows for a granular view of building management and accountability across multiple offices and tenants inside a building (below the current meter)

• Building Analysis - Trend analysis to evaluate comparative anomalies (e.g., 2nd floor vs. 3rd floor electricity consumption)

• Building Program Definition - Focus area definition based on findings (e.g., lease management, facilities management, etc.) and the identification of potential technologies (e.g., motion sensing light switches, optimizing maintenance routes, an Integrated Workplace Management System)

• Building Management Technology Deployment

Additionally, to further the development of smarter buildings, MSTEM and GoJ should support the design and execution of:

• Energy Efficiency Regulatory Framework - Regulatory approach that motivates JPS to move forward with energy efficiency and create a “win” for JPS (i.e., defining new regulatory models to incent energy efficiency), resulting in a policy and regulatory framework to support triple bottom line JPS decision making (i.e., including environmental impact in business decisions).

• Building Efficiency Lease Incentives - Policy to support shared cost between the construction company, leasing company and the occupant to incentivize energy efficiency decisions where the construction company or the leasing company is encouraged to invest



Conservation

Smart Buildings

Building Data Collection

Building Sub Meters



Legend




Legend


Building Management Technology Deployment

Energy Security and Efficiency Project

Building Analysis

Building Program Definition

• Energy Efficiency Regulatory Framework• Energy Efficiency Building Code• Building Efficiency Lease Incentives• Building Efficiency Reporting



in energy efficiency solutions or target higher efficiency (e.g., balance higher cost energy efficiency units against the reduced cost of operation)

o This includes encouraging leases that move away from the inclusion of all energy costs in the lease payments as a mechanism to incentivize the inclusion of energy efficiency investments and shared benefits from the same (e.g., rather than leases that include unlimited energy, leases that share the energy efficiency costs and benefits).

• Building Efficiency Reporting - Policy to support leasing company reporting requirements for energy efficiency (e.g., tax incentives for providing energy efficiency information)

• Energy Efficiency Building Code - Policy to support energy efficiency in the building code

5.4.2 Costs Drivers

• Data collection and recording

• Building sub-meters

• Integrated Workplace Management System software license and implementation


• Reduced energy costs

• Reduced maintenance costs

• Improved asset and facilities utilization

5.5 Customer Conservation and Energy Efficiency – Smart Water

Water management is an important topic for Jamaica and a significant influence on the electrical network. Commercial and technical distribution losses are resulting in significant unbilled water, approaching 70% nation wide. As the largest aggregate customer of electricity, this inefficiency in the National Water Commissions’ (NWC) distribution network represents a significant amount of lost electricity consumption used to operate water pumps. In addition, managing the timing of pump electrical consumption is an opportunity to align NWC’s service requirements with JPS’s electrical network needs and costs. Further alignment between JPS and NWC infrastructure and information presents additional opportunities for shared benefit.

Currently, NWC is working to address commercial losses by pursuing the rollout of 100,000 solid state meters and 40,000 mechanical meters to better monitor water consumption at the consumption points. In addition, to address technical losses, such as leaks in the water network, NWC is conducting a Pressure Management Study, pursuing a SCADA rollout for better network awareness, and executing a tank and pump refresh program to achieve higher water pumping efficiencies. A JPS time-of-use rate program designed to shift electric consumption from peak usage and cost periods is available for customers with demand of 25 kilovolt–amperes (kVA) or more (through a single meter).




Figure 30: Smart Water Initiatives

• JPS/NWC Infrastructure Alignment - Achieve efficiencies across JPS and NWC with an infrastructure alignment initiative which identifies areas where investment can be shared to meet needs across both organizations

o Investment in a data communications network to connect with devices across the electrical and water distribution networks

o Shared meter reading expenses to allow a single meter reading operation to meet the needs of reading water and electrical meters

• JPS/NWC Economic Alignment - Align NWC and JPS economic interests with rate programs that align NWC demand with JPS network availability and lowest possible generation costs (i.e., shift usage to partial and off peak periods), and incentive plans to reward NWC for power factor/power quality improvement where NWC invests to ensure that NWC consumption is not negatively impacting JPS network operations (See Figure 31).

Figure 31: Power Quality Impacts on Water and Electric Networks

• JPS/NWC Information Architecture Alignment - Align NWC and JPS information systems to allow for cross-referencing between customer accounts, to achieve better customer visibility and identify unusual discrepancies between water and electricity consumption


Smart Water



Legend



Conservation

JPS/NWC Infrastructure Alignment

JPS/NWC Economic Alignment

JPS/NWC Customer Alignment

JPS/NWC Information Architecture Alignment

• NWC Water Meter and Pump Update• NWC Pressure Management Survey• NWC SCADA Rollout

Planned/Existing NWC Initiatives• JPS/NWC Shared Investment Policy• Power Factor Tariff Design

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• JPS/NWC Customer Alignment - Integrate NWC and JPS customer information visualization so that customers can manage their utility accounts from one interface. In many other districts and countries awareness of usage drives conservation. Without adequate feedback, community engagement is difficult and has little ability to impact behaviours. The ability to target customer losses by residents (e.g., leaking taps, poor performing refrigeration) is problematic with 3 month old consumption readings and bills.

Additionally, to further the development of smarter water, MSTEM and GoJ should support the design and execution of:

• JPS/NWC Shared Investment Policy – Develop framework for NWC and JPS shared investments and benefit realization

• Power Factor Tariff Design – Initiative to a support tariff scheme which incentivizes customer investments in power quality correction

5.5.1 Costs Drivers

• Customer information system data sharing


• Shared JPS/NWC investments and operational efficiencies across JPS/NWC

• Shifting NWC pumping to off-peak provides a peak demand relief to the electricity network.

• Correlation of individual consumption of water can be aggregated to mains flows and help to reduce non revenue water levels. Combined with a pressure study, reduction of 10% of loss is achievable within a short time frame (3-5 years)

5.6 Customer Conservation and Energy Efficiency – Dynamic Rates

Jamaica has deployed smart meters capable of interval billing and applying rates for different consumption periods. Commercial and industrial customers with consumption above 3,000 kWh have the option to participate in time-of-use (ToU) rates. The latest smart meters deployed to residential customers also have interval billing capability (i.e., of the 24,000 deployed residential smart meters, 4,000 meters support interval billing).

Jamaica’s electricity consumption peak is driven by residential consumption between 6:30pm to 9:30pm, with day time consumption up to 50MW less. The opportunity to shift consumption from the evening peak is limited due to the challenge of shifting usage for cooking and evening lighting and the high cost of a full residential smart meter deployment.

However, there is opportunity to move commercial daytime usage from the partial peak (6am to 6pm) to off-peak (10pm to 6am). This would allow Jamaica to save fuel costs associated with the relatively less efficient generation that is deployed during the partial peak. In addition, this potential consumption shift would allow JPS to avoid network augmentation investments in zones with heavy commercial and industrial penetration. Opt-in curtailment (e.g., interruptable) rates which apply to commercial and industrial customers who agree to participate in a demand reduction scheme during times of network stress could also assist with avoiding network investments.

Business customers are restricted in their ability to make consumption adjustments due to business requirements. The reward for positive behavior (i.e., demand shifting) must be meaningful. Because the time-of-use demand charge in electricity bills represents just a portion of the total bill, achieving significant bill savings requires a large usage shift. The time-of-use rate design must allow for customers to meaningfully impact their bill and the customer needs to be



able to benefit from the fuel cost savings related to the demand shift. In addition, other utility experience demonstrates that it takes a concerted effort to successfully drive transition to time-of-use rates and behavior change. Customer education, usage analysis, and feedback loops (e.g., customer displays) are required to actual realize participation that will impact consumption patterns.


Figure 32: Dynamic Rates Program Initiatives

• Demand Response Strategy - Develop demand response strategy (2016)

• ToU Tariff Assessment - Commercial ToU rate redesign to provide meaningful incentive for demand shifting with proof of concept (2020)

• ToU Customer Communications - Support commercial ToU with customer-centric dialog and tools to support the change in usage

• Curtailable/Interruptable Tariff Assessment - Curtailable/Interruptable load tariff design

• Expanded Residential Smart Meter Rollout - Residential smart meter deployment when supported with business case incorporating benefits from meter operations cost reductions and the prepayment program (2020) (Utilizes the Meter Data Management System initiative in the Prepayment program)

Additionally, to further the Time-of-Use (ToU) program, MSTEM and GoJ should support:

• ToU and Energy Management Tariff Design – ToU and curtailable/interruptable load tariff

• Customer Communications - Customer education outreach on the value of ToU for Jamaica and customers

• Customer Data Policy - Customer data policy to dictate how customer data will be protected and used

• Offering Cost Allocation - Define regulatory treatment of costs associated with enabling an expanded set of offerings and providers (e.g., home energy management systems)


Dynamic Rates



Legend




Legend


Expanded Smart Meter Rollout

Demand Response Strategy

ToU Tariff Assessment

ToU Customer Communications


Conservation


• ToU and Energy Management Tariff Design• Customer Communications• Customer Data Policy• Offering Cost Allocation



5.6.2 Costs Drivers

• Customer energy management analysis tools

• Additional meters for residential ToU – Greater Kinston Smart Meter rollout estimated at US$50M, including meters and communications network


• Demand management

o Fuel cost savings

o Avoided network investment

• Meter operations

5.7 Asset Management

Currently, JPS’s asset and workforce management uses spreadsheets to track asset information and workforce execution, with limited information on asset maintenance or asset history. There is no structured preventive maintenance program. JPS depends heavily on field staff to know asset information, history and asset maintenance requirements. An asset and workforce management department has recently been created and an asset management system project is in planning for 2014.

Utilities are increasingly moving from reactive maintenance to condition-based maintenance. Leading utilities are beginning to deploy predictive maintenance, initially on devices that are monitored with time series data (e.g., transformers) and then using asset maintenance information and the real-time data. The collection of good field maintenance data along with integrated applications are a key to improved asset decisions, productivity, and reliability. Asset lifecycle decision support is allowing the asset management application to extend itself to the planning function.

Mobile workforce integration/automation is also seen as an important component of asset management functionality.

• There is a trend to “self-directed” fault management at the field service level (enabled by real-time mobile workforce application interaction with the asset management system)

• Paperwork reduction and data capture at the point of maintenance activity are two typical drivers for application integration; driving improved field productivity

• Utility field workforces have increasing access to spatial information in the field

An integrated asset management program can enable asset management while consolidating sources of asset condition data. This provides the ability to integrate the entire asset lifecycle from design to construction to operation. This integration facilitates the transition of operational design information from the design phase to operation for the purpose of enabling condition-based maintenance as per design parameters. The integration also facilitates managing all the information and events associated to the asset to ensure that the asset model and related databases are up to date. This unified approach will allow JPS to manage asset deployment, specifications, monitoring, calibration, costing and tracking to extend the life and reliability of the highest value assets: the initial focus is on key value assets and metrics, expanding to a wider set of assets as business value dictates.

Maturity in asset management will support the total asset lifecycle of high value assets by:



• Understanding asset gaps, weaknesses, efficiencies, losses and timing for long-term capital planning to optimize capital spending and maintenance

• Using condition-based maintenance and asset management to extend asset life and increase the accuracy of predictive analytics models for capital planning

• Prioritizing spending requirements to best meet business strategies within provided budget limitations

o Better understand when to replace assets

o Analyze the historic usage of assets to build a pattern that indicates the expected remaining life for existing assets

• Improving Work Management, where practical, such as:

o Streamlining work management processes (e.g., work planning, initiation, design, execution, closure)

o Enhancing integrated business processes such as supply chain management, resource utilization (e.g., labor equipment, materials)

Key elements of the asset management program should include:

• Maintenance Performance Management: Improve the information available to measure the effectiveness of maintenance programs. Provide metrics and information to ensure that the right maintenance is executed at the right time in the right place. This will improve reliability while optimizing operating costs.

• Maintenance Strategy: Design maintenance strategies that provide the right balance between planned maintenance (preventive, condition based) and reactive maintenance to maximize asset reliability while optimizing maintenance costs.

• Maintenance Planning: Improve the effectiveness of maintenance planning activities. Optimize the processes to determine the right maintenance to perform, a prioritized work plan and a resource requirement plan.

• Maintenance Management: Enhance the ability to actively manage maintenance work orders throughout the entire work order lifecycle from initiation to completion, maximizing the number of work orders completed as planned, on time, on budget.

• Inventory Management: Implement material management best practices to ensure that material is available to execute maintenance activities when required. Balance material availability and inventory costs to provide high service levels in particular for critical maintenance orders.


Figure 33: Asset Management Initiatives


Workforce & Asset

Management

Work & Asset Management

Asset Management Strategy

Asset Management System

Asset Data

Remote Asset Monitoring

Asset Process Redesign

Reliability-Centered Maintenance



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Asset Lifecycle Policy



• Asset Management Strategy - Develop asset management strategy with supporting business case (2016), including approach and system to track asset inventory and history

o Start with asset inventory/registry

o Identify system that supports the data collection and data maintenance

o Set scope of asset classes to cover

• Substation assets are key due to high economic and reliability impact (e.g. transformers, breakers, capacitors in the substation)

o Structure data hierarchy using key attributes

o Set process to collect information understanding that all attributes will not be collected initially

• Develop asset data governance plan across systems (e.g., Geographic Information System, Distribution Management System, and Asset Management System) aiming for plant commissioning dependent on system information flow-down to all systems

• Collect information as part of the work order execution process (i.e., whenever a job is done, collect asset information)

• Asset Management System - Implement Asset Management System and integrate with Work Management System to be able to report work against the asset management system (2016)

• Asset Data - Reconcile asset data across existing sources and execute asset information collection process (2016 and beyond)

• Remote Asset Monitoring - Deploy remote asset monitoring across key asset classes as asset communication capabilities are enabled

o Target remote monitoring at most critical substations with large transformers

o Send information where the operators are (e.g., locally at the substation or centrally)

• Asset Process Redesign - Support culture change in the long term (2030) to incentivize asset failure avoidance, rather than rewarding asset fixes.

• Asset Reliability-Centered Maintenance - Reliability-Centered Maintenance will be driven down to the substation level (extending from remote monitoring to predictive maintenance)

Additionally, to support the development of JPS’s Asset Management capabilities, MSTEM and GoJ should support:

• Asset Lifecycle Policy - Regulation and policies to support the development of an asset management system with expectations on reliability and improved asset utilization and reporting requirements

o Reduce the capacity needed to run the grid due to higher utilization



5.7.2 Costs Drivers

• License of EAM application

• Design, build, implementation of EAM solution - WAM system

• Integration

• Business process redesign

• Change management, training

• Data cleansing, data conversion


• Improve reliability - 50% of reliability issues have to do with poor asset maintenance, asset care and tree management

• Reduce maintenance costs

• Improve operations labor efficiency and reduce dispatch costs

• Reduce enterprise asset compliance risks and costs

• Improve procurement process and budgeting to minimize over-ordering by planners and/or engineers

• Centralized data visibility

• Optimize capital across projects

• Tying O&M, capital, risks and business value as a way to prioritize projects

• Streamlining the process to transition design information to operations and maintenance

Benefit Benchmarks

• 10% reduction in maintenance costs through asset management

• 2.5% reduction in transmission and distribution capacity investment due to asset management

5.8 Grid Operations – Distribution Automation

JPS has recently implemented a SCADA system which provides visibility down to feeder reclosers. JPS is conducting a distribution automation pilot this year, with 17 switches incorporated into SCADA in key strategic locations that would normally be manual switches. Decision support for operating theses switches is manually conducted by operators. JPS has a data historian that collects all SCADA points (including generation, transmission, and distribution networks).

Regarding Power Quality (PQ), SCADA can show momentary events at the feeder level, but not PQ sags and swells. PQ claims are investigated manually (e.g., looking at events and other customers). JPS uses moveable power quality sensors and is planning to install PQ meters on all distribution feeders.

The falling costs of sensors and supporting communications technologies, combined with the rollout of “smart” equipment (for example: smart switches, reclosers), are allowing for mainstream adoption of distribution automation capabilities.

Advanced network automation, including methods of routing power, balancing loads and improving distributed generator control, can be achieved through precise demand prediction, as well as parametric model-based methods of maintaining, upgrading and expanding the network based on



fine-grained monitoring of both grid and device performance. Utilities have achieved results in these functional areas by integrating Distribution SCADA (DSCADA) with historians and applying additional reporting and analytic capabilities. Although the business case in key areas may suggested some functional extensions to the Distribution SCADA system, care should be taken in understanding that significant custom development will duplicate out of the box functionality available from applications on JPS’s roadmap (e.g., Distribution Management System).

A Distribution Management System (DMS) can provide:

• Real-time analysis of the state of the distribution power system from real-time sources (for example: SCADA, Distribution Feeder Automation devices, or Automated Meter Infrastructure (AMI)). DMS presents to the operator the current state of the system and analyses and warns the operator of power system violations (for example: overload conditions)

• Real-time position of switches in the distribution system providing the current topological configuration (needed for accurate power flow calculations) whether informed by SCADA, Distribution Monitoring, or by hand-dressing of the switch status

• Multiple network views, both geo and schematic-based, driven by data sourced from GIS

• Ability to issue controls (for example: via SCADA) to breakers, switches etc. to open or close

• Ability to use a power flow model to assist in automatically or manually generating switch plans (That is: change the topological configuration of the power system and avoid committing violations in the process)

• Automatic fault detection, isolation and restoration of a power outage (FDIR) during an unplanned outage

• Simulation of the distribution power system to test various switching and power flow scenarios; eliminating this typically non-automated paper driven activity

• Optimisation of the distribution power system operation by adjusting the power system configuration, for example: Volt/VAR control, feeder load levelling

• Predictive capabilities and automation to avoid critical distribution power system failures

• Use of mathematical algorithms to analyse and predict how to optimise power flow through a utility’s distribution power system and to assist with network switching

• Sophisticated alarm management

A major trend in this space is the convergence of DMS with Outage Management (OMS) capabilities. As such, the DMS project could be an extension of JPS’s current OMS implementation.

A key consideration for the DMS project is that DMS platforms will increasingly ‘open’ access to/from their core network models. This will provide Common Information Model (CIM) compliant services to share core network connectivity information on both normal and as-switched bases. The integration around the OMS/DMS project could be the driver for the deployment of an operational Enterprise Service Bus (ESB). This will allow the DMS to be the core supporting application for network operations and control, without becoming the hub through which all collected network data is passed. This will support the aim to achieve decoupling of DMS from inbound (for example: SCADA) processing. This allows future flexibility for multiple network monitoring and control technologies (such as Distribution Automation, Distributed Energy Resources Management and Advance Meter Infrastructure) to be integrated with the DMS.

JPS should consider staging the roll-out their DMS initiative which could consist of a basic DMS functional implementation followed by a longer term advanced DMS solution. The scope and timing could be based on business need, vendor maturity, and JPS infrastructure readiness.



Deploying advanced functional capabilities (such as Fault Detection, Isolation, Restoration, automation support, fast load flow etc) in the DMS environment should be based on the value to control room operations. If the real value is for network planning or other functions, DMS should then only be the data source for these specific applications (That is: DMS is single source of data to inform the view of actual network state; informs the CIM for other tools to reference). DMS scope should ultimately include capability in mission-critical areas such as:

• State Estimation/Power flow modelling

• FDIR (Fault Detection, Isolation, Restoration)

• What-if Simulation

• Network Optimisation

• Switch Planning and Management


Figure 34: Distribution Automation Initiatives

• Advanced Sensor Plan - Develop advanced sensor plan (2016)

• Power Quality Monitoring - To support Power Quality (PQ) management, ensure that all new device specifications include PQ data and strategically deploy devices to provide full system visibility

• Distribution Management System - Deploy supporting systems to allow for automatic restoration in distribution monitoring enabled feeders. Allow some automation, such as for self sectionalising

o Late in 3 year period, deploy DMS with recommended switching sequences

o Support deployment with a review of outage management processes

o Aim for full schematic/spatial integration over time – allowing operations users to navigate by whichever means is appropriate (10 years)

• Distribution Management System Integration - Integrate the DMS with historian and planning tools; simultaneously evaluate the role of an ESB for integration

o Use shared data requirements between DMS and Asset Management System (AMS) to implement an ESB; ESB foundation for implementation of Power Network Model and leveraging applications such as the Data Historian


Grid Operations


Advanced Sensor Plan

Distribution Monitoring and Control

Distribution Management System

Distribution Monitoring and Control Systems

Distribution Management System Integration

Operational Analytics



Legend




Legend


Power Quality Monitoring



• Distribution Monitoring and Control - Deploy distribution substation monitoring including low voltage (LV) only for urban/sub-urban networks

o Configure select network points in DSCADA

o For rural networks the cost of monitoring can be brought down by only monitoring the high voltage (HV) side

• Distribution Monitoring and Control Systems - Deploy supporting systems to support network monitoring

o Non-SCADA gateway to avoid an information bottleneck through the SCADA system

o Device manager to assist with provisioning and managing of devices (e.g., firmware upgrades)

• Operational Analytics - Evaluate analytic/reporting extensions for key areas (e.g., asset scenario analysis, planning) and users (e.g., dashboards)

5.8.2 Costs Drivers

• Software license and implementation for DMS application, including adapters (e.g., SCADA, OMS, etc.)

• Software license and implementation for Non-SCADA Gateway and Device Manager

• Substation and network sensors and installation

• Integration with planning tools, historian

• Data validation and integration (quality and data profiling, source data acquisition, staging, transformations)

• Process impacts


A Distribution Management System is the single most important application in a smart grid architecture. The quality of the solution and its implementation can directly impact JPS’s network aspirations in nearly all areas. In particular safety, reliability, flexibility and sustainability outcomes are probably unachievable without a robust, proven and trusted DMS platform. DMS benefit areas include:

• Safety - Safe network operations require a high degree of network visibility. As remote control and automation are deployed across the network, the requirement for proven safety protocols and software enabled interlocks increases

• Reliability - Reliability initiatives are also heavily dependent on the DMS and, in particular, the advanced modeling and automation functions becoming available in the near future

• Flexibility - Advanced capabilities such as online load flow studies and Volt/VAr analysis will be required to achieve the degree of network flexibility and manage more complex power flows resulting from higher levels of distributed generation and storage on the grid

• Reduction of power losses (technical and commercial)



• Reduction of operation costs (improved fault management, reduced energy not supplied, reduced switching)

• Reduction of network development costs (improved utilization of facilities and investment postponement)

• Improved power quality (on-line and off-line regulation of transformer tap changers)

• Intangibles: improved situational awareness, improved operations and IT work efficiency, and improved customer satisfaction

Distribution Monitoring and Control Capital Efficiency Benefits

• Avoided costs of installing and reading Maximum Demand Indicators and load surveys

• Avoided costs of reliability improvements

• LV network augmentation deferrals

• Efficient investment in high voltage network

• Re-rating substations

Distribution Monitoring and Control Process Efficiency Benefits

• Outage claims costs reduction

• Inbound outage calls management

• Operator productivity – fault location

• Customer voltage investigations

• Outage data management

• Reduce battery monitoring costs

5.9 Grid Operations - Renewable Generation (Utility Scale)

Jamaica is currently expanding traditional and renewable generation, including the 360MW conventional generation solicitation and the 115MW renewable generation request-for-proposals. In the island setting, managing frequency control and the reserve margin are challenges. In addition, the increasing renewable penetration targets will drive electric grid management issues as more intermittent sources, such as solar and wind, are incorporated. A Grid Impact Study is currently underway which is assessing the impact of different renewable energy sources and penetration levels on the JPS electric network.

To manage renewable integration, utilities are pursuing complementary approaches of improved forecasting and utility-scale electricity storage. Improved forecasting based on a wider set of data inputs can improve the utilization of renewable generation and lower the expensive requirements for additional stand-by generation and storage options.




Figure 35: Renewable Generation Initiatives

• Forecasting Assessment - Develop forecasting capabilities with an assessment of forecasting requirements and required inputs to improve forecasting accuracy for improved renewable utilization

• Forecasting System Deployment – Evaluate, select, and deploy system to support fine-grain renewable forecasting

• Sensor Expansion - Execute sensor expansion to address missing data inputs for improved renewable forecasting

• Conventional Generation supporting Renewable Generation Strategy - Develop conventional generation strategy to provide required generation ramping capabilities to accommodate increased renewable generation within the limits of forecasting capabilities

• Storage Strategy - Develop utility-scale storage strategy to meet the grid management requirements of increased renewable generation

• Storage Deployment

5.9.2 Costs Drivers

• Sensors for forecasting

• Forecasting system

• Storage deployment

• Conventional short-ramping generation to support intermittent renewable generation (part of the generation investment plan)


• Increased renewable asset utilization

• Increased renewable generation in the portfolio mix

• Reduced short ramp time generation requirements


Grid Operations

Renewable Generation

(Utility Scale)

Forecasting Assessment

Sensor Expansion (Renewable Utilization Focus)

Conventional Generation supporting Renewable Generation Strategy

Storage Strategy



Legend




Legend


Forecasting System Deployment

Storage Deployment



• Reduced grid storage requirements

5.10 Grid Operations - Distributed Resources

The “Net Billing” program pilot has resulted in the recent commissioning of 5 distributed generation (DG) sites (i.e., customers with 100 kW or less) and approximately 50 applications are in the pipeline. Due to the high electricity costs and decreasing system costs, Jamaica is experiencing the arrival of photovoltaic (PV) grid parity (i.e., the cost of electricity supplied by a residential PV system is less than the cost of regulated electricity pricing) and could be looking at a longer term trend in this area. Consumer desire to mitigate high supply costs and volatility, in addition to increasing reliability and service quality expectations, will lead to expanded adoption.

The electric network will face operational issues driven by power flow reversal from PV generation where JPS can expect over-voltages as PV hits 30+% penetration. Random clustering of PV generation will cause local problems. Depending on the invertors, the PV installations will create harmonic distortions.

Voltage fluctuations due to PV generation intermittency will drive storage requirements and network planning considerations. JPS should look for transmission and distribution asset deferral benefits but have backup plans (just like line outages), should the DG technology have an unplanned outage. JPS must also consider the information management effects of DG growth, such as the need for a system to function as an operational performance historian. It will affect operational technologies in the distribution domain as well as legacy IT applications in the revenue management and commodity management areas.

Many advanced energy storage technologies are commercially available and have been demonstrated in many utility field deployments. JPS should consider small pilot projects for telecommunications and substation site batteries and remote location line upgrade deferrals.

Regulatory and policy initiatives should focus on the appropriate balance between enabling competitive forces and environmental goals with the need to ensure reliable and resilient service to all customer classes. New entrant threats to the traditional utility financial model and its regulatory compact are precipitating active regulatory discussion on new business models. Regulators under pressure to reject rate increases and cost recovery are increasingly receptive to a greater degree of incentive-based regulation to balance cost and innovation.


Figure 36: Distributed Resources Program Initiatives



Distributed Generation Planning and Build

Microgrid Assessment

Distributed Generation Strategy

MicrogridEnablement

Distribution Generation and Storage Pilot

Grid Operations



Legend




Legend


• Distributed Generation Offering Support• Distributed Generation Tariff Design



Supported by initiatives in the Grid Operations work stream, additional Distributed Generation (DG)-focused initiatives include:

• Distributed Generation Planning and Build - Distributed generation planning and network augmentation to address the feeder-level operational issues related to distributed generation penetration, incorporating the findings of the current feeder impact study (i.e., Distributed Generation Penetration Study currently in progress)

• Distributed Generation Strategy - Develop strategy to manage additional resources, such as distributed generation, demand response, and potential areas such as residential home energy management systems (HEMS)

• Distributed Generation and Storage Pilot - Evaluate doing real life trials of clustered embedded generation from renewable generation sources and distributed storage (2016)

o Assess the mitigating effects on voltage variation from smart inverters with reactive power support (2016)

o Assess the level of network observation and control required to manage the “disruptive effects” and benefits of embedded generation (2016)

• Microgrid Assessment - Develop the microgrid as a concept to allow communities to island, so reliability, deferred network augmentation and network flexibility can be explored (2020)

• Microgrid Enablement - Distributed generation, storage and microgrids are supported as standard business (2030)

Additionally, to support the development of distributed generation in Jamaica, MSTEM and GoJ should support:

• Distributed Generation Offerings Support - Policy to support competitiveness (e.g., creating options for other electricity distributors to provide service to customers, such as 3rd party distributed generation communities; new business models which support JPS-owned DG leased to customers)

• Distributed Generation Tariff Design - Tariff design (e.g., fixed delivery or connection charge) to compensate JPS for its role as the distribution network operator even as revenue from electricity sold to customers decreases due to DG (e.g., “net zero” customers)

o Different rate structures will be required to support the existing infrastructure investment used by “net zero” customers and other business models where the infrastructure may be owned by 3rd parties.

5.10.2 Costs Drivers

• Pilot

o Inverters with reactive power support

o Grid sensors

o Photovoltaic DG

o Storage



• Microgrid controller and supporting systems

• Network enhancement to support DG penetration (part of the network refresh investment program)


• T&D network investment deferral

• Improved reliability

• New business opportunities

• Environmental sustainability



6 Smart Grid Roadmap Benefits and Costs

6.1 Smarter Planet Value Quantification Model Overview

IBM’s Smarter Planet Value Quantification Model (SPVQM) provides a quantitative model based upon the cumulative experiences of numerous utilities in implementing smart grid transformations to estimate expected costs and benefits under multiple scenarios.

IBM’s Center for Applied Insight created this model based upon the cumulative experiences of numerous utilities in implementing smart energy transformations. IBM conducted extensive primary and secondary research across the energy sector to quantify the value of key capabilities needed to address emerging market demands, such as the integration of distributed and renewable resources, regulatory pressure to provide expanded service and lower environmental impacts, new technologies and market entrants, and pressure to reduce costs.

The model brings together case studies, business cases, secondary research, pilot project results and existing benefit models to provide a business case for smarter energy investments. It allows utilities to examine their own benefits, as well as the benefits that accrue to their customers and society – key areas of interest to regulatory bodies.

Getting to a dynamic business model that supports smarter energy is a journey. The destination can, however, be described by a common set of outcomes and capabilities (See Figure 37).

Figure 37: Smarter Energy Value Streams

• Monitor and Automate: The journey starts with evaluation of existing infrastructure, generation, transmission and distribution networks. Initial focus involves expanding beyond the automation and real-time knowledge we have with traditional SCADA systems on the transmission grid to similar visibility on the distribution network.

• Connect Participants: The journey also requires the integration of customers and other participants. Plugging them in from a knowledge and visibility perspective as well plugging

The Journey to Smarter Energy

Part

icip

ato

ry n

etw

ork

Sense & respond

Integrate customers and providers with the network and enable participation and conversation

Share information, analyzing and acting upon it to balance supply with demand given real-time conditions

Optimize network using rules, constraints and intelligent agents

Measure and controlGain observability over the network and automate control functions

Connect participants

Analyze & optimize

Monitor and automate (Network)

Advanced FunctionalityBasic Functionality

Progress/maturity over time

On

e-w

ay f

low

Orchestrate the network and all

its participants to continuously assure

an outcome that is better than

the sum of the individual parts

Part

icip

ato

ry n

etw

ork

Sense & respond

Integrate customers and providers with the network and enable participation and conversation

Share information, analyzing and acting upon it to balance supply with demand given real-time conditions

Optimize network using rules, constraints and intelligent agents

Measure and controlGain observability over the network and automate control functions


Analyze & optimize




On

e-w

ay f

low







them in to the electric grid by enabling distributed generation, storage and renewable generation. This sets up the capability of a multi-way conversation among the participants.

• Sense and Respond: Visibility and integration provides the ability to share information, analyze it in real-time – sensing and responding to real-time conditions. Knowing what’s going on at any given moment across the value chain provides faster reaction time and a more accurate response. Outage and demand response are two areas that are greatly enhanced by the measurement and control established earlier in this journey.

• Analyze and Optimize: Analysis and Optimization provides each participant the ability to see real-time conditions and to optimize their response to secure the outcome they want – the utility is able to manage the grid proactively and avoid problems; consumers are able to project their usage and change it based on pre-set parameters; generators are able to determine how much to sell based on real-time conditions. Much of the decision making is provided by automation and intelligent agents.

IBM analysis found widespread agreement around many of the benefits of smart grid investments. The model estimates benefits for 6 specific value drivers: transmission and distribution (T&D) operations and maintenance costs, T&D capital expenditure, generation capital expenditure, energy cost, environmental and customer costs (See Figure 38). IBM research netted industry-wide agreement in some areas and wide variances in others. The model uses a conservative approach by using the low end of all ranges in cases where there was a difference of opinion or experience.

Figure 38: Benefit Benchmarks

6.2 Smarter Planet Value Quantification Model Findings

Experience shows that most utilities “wind their way” through the smart grid journey, taking each project on a stand alone basis. JPS is pursuing a number of projects which are advancing capabilities against the Smarter Energy value streams (See Figure 39).

Value Driver Investment Area Example of Potential Benefit

T&D O&M Costs Outage Management

Asset Management

10% of restoration costs

10% of maintenance costs

T&D Cap Ex Demand Response 5% reduction in peak demand

Generation Cap Ex Voltage/VAR Optimization

Demand Response

2% reduction in peak demand

6.5% reduction in peak demand

Energy Costs Smart Meters

Voltage/VAR Optimization

25% reduction in commercial losses

0.2% reduction in energy supply needs

Environmental Energy Efficiency 7% reduction in carbon

Customer Costs Energy Efficiency

Outage Management

7% reduction in energy consumption

20% reduction in cost to customer

Value Driver Investment Area Example of Potential Benefit

T&D O&M Costs Outage Management

Asset Management

10% of restoration costs

10% of maintenance costs

T&D Cap Ex Demand Response 5% reduction in peak demand

Generation Cap Ex Voltage/VAR Optimization

Demand Response

2% reduction in peak demand

6.5% reduction in peak demand

Energy Costs Smart Meters

Voltage/VAR Optimization

25% reduction in commercial losses

0.2% reduction in energy supply needs

Environmental Energy Efficiency 7% reduction in carbon

Customer Costs Energy Efficiency

Outage Management

7% reduction in energy consumption

20% reduction in cost to customer

Quantifying the benefits



Figure 39: Current and Planned JPS Investments

This is not an unusual sequence of investments. The Smart Grid Roadmap is designed to build on these investments by enhancing value both “to the right within a step” and “up the curve to the next step”. The investment path builds on past investments to the end goal of orchestrating the network.

The Smarter Planet Value Quantification Model incorporated parameters specific to Jamaica, such as customer count, electricity costs, and operating budgets (See Appendix for a full list of model inputs).

Using the timing of investments in Jamaica’s Smart Grid Roadmap and expectations on the timing of benefits, the model estimated gross benefit of US$1.313 Billion over a 15 year period on investments of US$144.6 Million. These benefits include US$547 Million in customer benefits from improved reliability, lower bills, and reduced energy costs. JPS’s estimated benefits of US$767 Million are driven primarily by operational and capital expenditure efficiency. The US$93 Million environment benefit from reductions in emissions is included in JPS benefits, anticipating the value of carbon emission credits. These “Utility” and “Environment” benefits provide JPS an estimated 5.4 year payback period on the smart grid investments.

At steady state when all investments have been completed, the model projects that smart grid investments will provide total annual benefits of US$244.9 Million across all of the value streams (See Figure 40).

Figure 40: Year 15 Estimated Benefits

Part

icip

ato

ry n

etw

ork

Sense & respond


Analyze & optimize




On

e-w

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low





The Journey to Smarter Energy

Implemented SCADA 4 years

ago

Connecting all C&I customers and

limited residential smart meters now

Conducting distribution grid monitoring pilot

(e.g., Power Quality)

Planning Distribution Management System

implementation

Implementing Outage Management System



The estimated benefits at steady state for customers are US$105.3 Million and US$139.6 Million for JPS (See Figure 41). In the Monitor and Automate value stream most of the benefits go to JPS from increased grid intelligence. The benefits in the Connect Participants value area represent a higher percentage of customer benefits as customers see value from lower bills and energy costs from increased energy management capabilities. The utility sees benefits from areas, such as electricity loss improvement. The customers have significant benefits in the Sense and Respond value area from reliability improvements. The utility sees most of the benefits in the Analyze and Optimize value area as the smart grid investments provide JPS the ability to more efficiently operate the grid.

Figure 41: Annual Smart Grid Benefits at Year 15

Milli

on

s (

US

$)

Annual Benefits at Year 15 (Steady State)



7 Appendix A

7.1 Smart Grid Overview, Lessons Learned and Case Studies

7.1.1 Smart Grid Overview

The fundamentals of power grid operations have not changed much during the past 100 years since the time of Thomas Edison. The existing transmission and distribution system largely uses technologies and strategies that are many decades old and include limited use of digital communication and control technologies. At the same time, the needs of customers and the demands placed on utilities are increasing, with increased expectations on reliability, efficiency, customer choices, and the use of renewable energy sources.

Smart grid is the transformation of power operations through advancements in Operational and Information Technologies to improve system reliability and efficiency, address the challenges of higher levels of intermittent renewable sources, and enable more-active consumer participation in their energy consumption decisions. As such, smart grid is an end-to-end transformation of the electric system that applies advances in technology to deliver a range of new benefits to policy makers, regulators, utilities, and consumers:

• Improve reliability through better monitoring and control using new sensors and network protection devices supported with improved outage management applications

• Improve consumer energy management capabilities and options by providing technologies which support demand management and the use of distributed energy resources

• Improve delivery infrastructure efficiency by providing monitoring, control and optimization capabilities supported by extensive measurements, rapid communications, centralized advanced diagnostics, and feedback control

• Increase energy sustainability by supporting increased renewable energy and energy efficiency

To achieve these aims, smart grid provides capabilities across four domains (See Figure 42).

Figure 42: Smart Grid Capability Domains

Automatically monitor, assess, and

control the grid to adapt to changing conditions to meet customer reliability and power quality

requirements

Deploy and manage workforce and

infrastructure assets more effectively to improve operating

and capital efficiency

Optimize the dispatch and control

of distributed resource to improve

reliability & economic dispatch

Grid Operations

Workforce & Asset Mgmt

Supply & Demand

Optimization

Provide solutions that enable

customers to become “active”participants in the

energy supply chain to better manage

energy consumption

Customer Solutions



Within each of these capability domains, utilities define underlying capabilities needed to meet their business requirements. The target capabilities are an important first step in defining the value that a smart grid program is intended to achieve and defining a smart grid roadmap.

Once utilities have defined specific smart grid capabilities and features, then the supporting initiatives, technologies, and process adjustments can be defined, prioritized, and sequenced.

Although target smart grid capabilities vary widely across utilities, the definition of smart grid investments to deliver the capabilities must account for smart grid end-to-end components across five levels (See Figure 43):

1. Smart, Connected Devices (“Intelligence”) – These are the end points of the system and the devices with which communication is possible. These include sensors, equipment, and meters across the network.

2. Integrated Communication Networks (“Connected”) – These are the layers of the telecommunication network which cover the different zones of the network, from inside the home, to the neighborhood, to the substation, backhaul and into the utilities operating systems. These are the communication layers that make communications to devices on the electrical network possible.

3. System Integration Platform (“Integrated”) – This level provides infrastructure, data and systems management to support the applications environment. This includes areas such as security and information network management.

4. Applications & Analytics (“Automated”) – This is the collection of applications that drive smart grid functions and includes systems such as asset management, outage management and operational analytics.

5. Presentation (“Informed”) – This level provides the visualization that enables the utility to make informed decision around smart grid functions and includes dashboards and interfaces that get information to the right place at the right time.



Figure 43: Smart Grid End-to-End Components

7.1.2 Smart Grid Lessons Learned

From established smart grid implementations around the globe, several key findings and lessons learned to achieving a successful cross-enterprise transformation are evident:

1. Strategy

• Planning a smart grid program requires an ongoing evaluation of business strategy focused on delivering business value. A centerpiece to success is focusing on the value derived from new capabilities, not technology alone (i.e., business value should drive projects and investment – not visa versa).

• Value analysis requires reasonable precession which looks at where the benefits will be achieved (e.g., 75% of the benefit may come from 25% of the feeders covered by fault isolation and restoration technologies). Rolling out technologies across the electrical network without consideration for high impact areas is expensive and risky.

• Because smart grid-related technologies are rapidly maturing, developing a smart grid roadmap is not a one-time process and should be updated every 18 to 24 months as technologies mature and business drivers evolve.

2. Collaboration

• Smart grid transformation requires a much closer collaboration with customers, regulators, financers, researchers, technology and service vendors, and internal stakeholders than ever before. Key internal and external stakeholders need to be on

Advanced Electric Meters

In-Home displays

Personal Computers

Load Control Devices

Smart Appliances

Handheld Data Devices

Advanced Gas Meters

Advanced Water Meters

Electric Vehicles Outlets

Solar Panels

Reclosers

Sensors

Voltage Controllers

Switches

Substation & Grid Devices

Smart MetersIn-home Devices

Ruggedized Laptops

Mobile Devices Distributed Resources

Cell Phones

Wind Turbines

Home Area Network

Neighborhood Network

AccessNetwork

Backhaul Network

ExtranetCore & Office Network

1. Smart, ConnectedDevices

2. Integrated Communication Networks

3. System Integration Platform

4. Applications & Analytics

CHP

Servers System and Network Management

Storage and Backup

Business Process Management

Computing Infrastructure

Application & DataIntegration

Systems Management

Security Management

Messaging & Web Services

EMS DMS

MDMS

Meter Data Collection

Load Control

GISNetwork Analytics

OMSAsset Management

CIS

Call Management

WMS

5. Presentation Employee Portal/ Dashboard

Field Employee Mobile Devices

Display Device Interface

Customer Mobile Devices

Customer Web

Paper Bills

Energy Storage



the same page, so that there is agreement on the destination before the course is set to get there.

• Internally, utilities need to be prepared for the significant cross-organizational impacts. Smart grid value is realized and enabled by technology via integration across organizational boundaries and “engineering” projects.

3. People

• The cross-enterprise impact and functional requirements of smart grid should drive a renewed focus on staff, their roles, competencies, compensation, performance and structure. An effective smart grid governance model with clear organizational roles, responsibilities, and accountabilities is critical going forward.

4. Process

• Smart grid-impacted processes touch almost every part of the utility organization, which requires a redesign of business processes and applications across several domains. Vendor involvement is critical when developing to-be business processes to understand best practices and keep implementation practical.

5. Technology

• Smart grid implementations represent the large-scale introduction of a complex set of evolving, interdependent technologies from different vendors. Transition to a smart grid is not a simple, single, sequentially lifecycle as most IT transformations. For a given smart grid transformation there may be numerous parallel efforts progressing through different phases simultaneously. Multiple initiatives are highly interrelated and must be coordinated.

7.1.3 Smart Grid Relevant Case Studies

The development of Jamaica’s Smart Grid Roadmap benefits from the experiences of other utilities in similar circumstances and facing similar priorities. This set of references includes utilities addressing the challenge of an island jurisdiction, implementing customer demand management programs, integrating renewable resources, addressing significant energy losses, and, finally, managing large-scale smart grid transformations. The approaches and results of utilities like these are guides to Jamaica’s Smart Grid Roadmap.

Malta‘s Nationwide Island Smart Grid

Challenge:

Similar to Jamaica, on the island nation of Malta, electricity is generated entirely by imported fossil fuel. The electrically powered desalination plants provide over half its water supply. Meanwhile, rising sea levels threaten Malta’s underground freshwater source. This complex series of challenges required immediate attention to ensure that the country delivers affordable, secure energy while protecting the environment. In addition, to meet this challenge, both Enemalta, the electric utility, and Malta’s Water Services Corporation are undergoing an internal transformation process geared towards increased efficiency.

Solution:

� Deploy 250,000 interactive meters to monitor electricity usage in real time, set variable rates

� Integrate water meters

� Enable remote monitoring, management, meter readings and meter suspensions



� Restructure the billing process to eliminate estimated accounts so customers pay only for what they actually use

� Enable flexible tariffs to sustain new policies on energy consumption

� Implement pre-payment solutions

� Enable remote monitoring of electricity and water grids to reduce technical and commercial losses

� Introduce energy efficiency analytics of consumption patterns enabling a real-time view of energy use to identify opportunities for reduction

� Introduce a customer portal to enable customers to track current consumption and choose the most appropriate agreements

Benefits:

� Data from the intelligent meters can be analyzed to help lower costs, adopt efficient and sustainable consumption patterns and cut greenhouse gas emissions

� By addressing water and power issues as a system, citizens can make smarter decisions about how and when they use power

HydroOttawa (Ontario, Canada) – Time of Use Rate Program

Challenge:

Facing generation capacity shortages, Ontario set the course to become a North American leader in energy conservation by targeting a smart meter into every home and small business by 2010 (~4.5 million). To understand the demand management value of the smart meter investment, Ontario looked for validation of the demand reduction impact provided by hourly interval metering with Time-of-Use (TOU) pricing.

Solution:

IBM and eMeter led a price pilot on behalf of the Ontario Energy Board in anticipation of a province-wide time-of-use rate implementation.

375 customers in the Ottawa area were put onto one of three innovative electricity rates: TOU, Critical Peak Pricing (CPP) and Critical Peak Rebates (CPR) (See Figure 44). The hourly usage and pricing information was collected at least nightly, and presented on the web the next morning.

Figure 44: Ontario Regulator’s Proposed Time-of-Use Rate/Tariff Profile

Duration: August 2006 until February 2007.

Benefits:

� Up to 25% demand response

Summer Winter

Rate

Rate

Time of DayTime of Day



� 6% conservation effect � 75% of customers save on TOU rates � 75% of customers prefer TOU rates � Today, Over 3.7 million customers are on TOU rates

Hydro One (Ontario, Canada) – Renewable Integration

Challenge:

As a result of the Ontario Green Energy Act, a significant amount of new distributed generation (DG) will be incorporated onto Hydro One’s distribution system. Without detailed load forecasting of load and distributed generation supply, artificial limits would be placed on distributed generation capacity to ensure stable grid operations.

Solution:

� Advanced analytics software algorithms were developed to model both demand forecast and forecast supply from DG

� Inputs include AMI data for load and generation, demographic data, weather and the grid connectivity model

� Forecasted load done by feeder; generation forecasted by unit for next four hours

� Comparison of feeder load and generation output to predict if output satisfied set thresholds. If threshold is exceeded, enable dispatch of generators on a feeder so that the threshold is satisfied on all segments

Benefits:

� Near real-time predictive and optimization analytics to determine the amount of generation within a network section and shed any excessive generation to maximize variable DG capacity

� Comparison of load and generation forecasts allows the utility to ensure variable DG output is below tolerable thresholds

� Enable optimization techniques which provide recommended actions to maintain power quality

� The DG analytics solution provided a margin of +/- 20% accuracy on model predictions for generator sources and loads involved in the pilot with 95% of all load and source profiles being modeled accurately

� The DG analytics package can help Hydro One meet the Ontario legislative requirements to enable renewable energy onto the distribution grid and can increase the number of distributed generation connections to be integrated by up to 50%

Eskom (South Africa) – Energy Loss Management

Challenge:

� Illegal consumption of power is estimated to cost the economy about R 4.4 billion a year ($440M USD)

� 5,000 GWh of power illegally consumed every year

� Electricity theft occurred in all sectors of customers.

� Tampering identified in about 1% of Large Power Users (LPU) meters and 6% of Small Power Users (SPU) meters



Solution:

Eskom implemented a comprehensive ‘Energy Loss Management Program (ELP)” utilizing boundary meters, energy balancing and analytics, and site audits/inspections (See Figure 45).

Figure 45: Eskom’s Energy Loss Management Program Structure

The “audit, measure and fix” work stream uses business intelligence to identify and target customers that are high risk customers. Customer audits are prioritized using anomaly reports such as customers that are consuming very little in comparison to other customers in the same category, or customers consuming even though their accounts have been terminated. The results of audits are measured on the ELP scorecard where the number of audits done per month and number of problems fixed per month are tracked and measured.

The "ringfence electrical networks to balance energy" work stream focuses on the identification of network boundaries, installing statistical meters to measure energy flows and to balance energy inflows and outflows so that anomalies can be identified.

The "implemented tested technologies” work stream focuses on investigating technology options to reduce energy losses, piloting and testing these technologies and measuring the benefits.

The "ensuring sustainability through resourcing" work stream focuses on detailed business and environmental analysis to determine gaps in the business – these gaps could be process, people and technology related.

The "communications" work stream focuses on both internal communication as well as communication to the general public. Internal staff is educated on what energy losses are and the impact their work activities have on energy losses. A public engagement drive has been initiated that encourages all South Africans to be or become legal power users.



Benefits:

� 19,298 LPU audits were done, with 1,960 problems identified and 1,913 problems fixed

� 254,507 SPU audits were done, with 46,688 problems identified and 20,691 problems fixed

� 2,117,977 PPU audits were done, with 240,300 problems identified and 168,062 problems fixed

� A loss to the business of over R 120 million ($12M USD) has been prevented as a result of the fixes done on problems identified from April 2009

Florida Power and Light (Florida, United States) – Smart Grid Program Management

Challenge:

A smart grid transformation is large, complex and lengthy: transition to smart grid capabilities is not a simple, single, sequentially phased life-cycle as are most IT transformations.

Given the broad scope of smart grid transitions, efforts are often broken into two or more parallel programs of effort, and then individual projects within those programs (e.g., one program may focus on deployment of advanced meters, another on substation automation).

Transitions may iterate through many or all stages of the implementation approach several times, for different areas (e.g., an advanced metering deployment project may be followed by an effort focused on improved outage management, utilizing data provided by this newly deployed advanced metering infrastructure).

Transitions are also recursive in that they launch pilot projects at various phases. Each pilot project is in effect an accelerated progression through an implementation.

The cumulative effect is that for a given utility’s smart grid transformation there may be numerous parallel efforts progressing through different phases simultaneously.

Solution:

Deploy an overall program management office across the various smart grid and smart energy initiatives to support project definition, status report, cross-initiative dependency management, and benefits tracking (See Figure 46).



Figure 46: Sample Program Structure to Address Cross Project Interdependencies and Complexities

Benefits:

� Share methods, standards, and tools with lessons learned across all projects

� Accelerate implementations with increased agility in processes, gating and execution

� Provide consistent, comprehensive and practical processes for consolidated stakeholder reporting

Legend: Project Execution Program Work StreamEngineering/Technology

Work StreamIT&T Work Stream

dSCADA SGIG FeederSegmentation

NGDR EV IntegrationOEVC


Change Management

Risk Assessment and Mitigation

Resource Management and Strategic Sourcing

Engineering and Standards

Telecommunications

System Integration

Interoperability and Cyber Security


Change Management

Risk Assessment and Mitigation

Resource Management and Strategic Sourcing

Engineering and Standards

Telecommunications

System Integration

Interoperability and Cyber Security

Program Office

Program Board



8 Appendix B

8.1 Smart Grid Maturity Model Aspirations – Domain Detail

In the course of the Smart Grid Maturity Model assessment, the working group reviewed Jamaica’s current state results with comparison to other utilities in the >250,000 meter benchmark and identified target capabilities for Jamaica’s electrical network at different time horizons.

For each domain, the process of identifying target capabilities was based on a practical discussion incorporating a solid rationale, acknowledgement of obstacles, and the development of a preliminary action plan. The following sub sections include details from the working session discussion.

8.1.1 Strategy, Management and Regulation (SMR):

In the SMR domain, Jamaica shall target Level 3 maturity by 2016 and achieving Level 4 by 2020 to be maintained through 2030 (See Figure 47).

Figure 47: Jamaica Strategy, Management, & Regulation Domain Aspirations

What motivates this aspiration?

• Clear responsibility for the smart grid program will drive accountability and progress, within JPS

• An encapsulating vision for smart grid will assist with alignment with external stakeholders

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– Some elements of the vision: “most economical path”, “bidirectional”, “customer”, “flexible network for new network components, such as DG”, defined value for stakeholders, and support “societal and environmental” value to stakeholders, supporting National Energy Policy goals

• Prepares JPS for the ongoing review and adjustment to the energy market planned by the Ministry and the regulator (e.g., net-billing => power wheeling)

– Prepares JPS for the operational issues related to the expected renewable energy targets; plans investment that addresses network challenges stemming from increased intermittent renewable generation in the most efficient way

• Guides investments that will mitigate the high energy costs; smart grid improves operational efficiency and capital expense (mitigating rate impacts) while providing customers with more information for their energy usage decisions

• In 2020, if smart grid is not a core competency for JPS, the customer may find other solutions (e.g., third parties)

What actions must happen to achieve this aspiration?

• Firm government support is required to drive the smart grid investments

– Clear alignment between JPS, the Ministry and the Regulator on the priorities is required, which supports rate recovery, investment recovery

• Grant funding / third party funding (e.g. World Bank, similar to the stimulus support in the U.S)

• Identify clear smart grid responsibility in a JPS leader to maintain accountability and drive progress

• Develop smart grid vision before 2016 and align to National Electricity Policy (Currently in draft), which is a sub-policy for the National Energy Policy

• Collect lessons learned from existing smart grid projects (e.g., RAMI, Net Billing)

What are the obstacles that must be overcome to achieve this aspiration?

• Impact to the rate base and customer electricity costs must be minimized (particularly in short-term horizon) – need to align interest of customer with utility so it is a “win/win” for both; investment justification must be developed

8.1.2 Organization and Structure (OS):

In the OS domain, Jamaica shall target Level 3 maturity by 2016 and achieving Level 4 by 2020 to be maintained through 2030 (See Figure 48).



Figure 48: Jamaica Organization & Structure Domain Aspirations


• Organization should support the execution of the smart grid vision

• Supports smart grid implementation progress with well considered organization (structure and operation) planning, design, and management

– Maturity Level 3 characteristics support momentum toward smart grid vision, with the appropriate measurement, communications, and training

What action must happen to achieve this aspiration?

• Evaluate existing training programs for alignment to smart grid competencies


• Updates to the compensation plan to align with smart grid performances requires focused internal change management

8.1.3 Grid Operations (GO):

In the GO domain, Jamaica shall target Level 3 maturity by 2016 and achieving Level 4 by 2020 to be maintained through 2030 (See Figure 49).

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Figure 49: Jamaica Grid Operations Domain Aspirations


• Reliability improvement, loss management and load control

• Supports JPS to meet the OUR’s planned reliability penalty/reward program

• Achieves improved network performance, using less operational and capital expense than required in traditional network investment (e.g., network augmentation)

• Prepares JPS’s network for the increased penetration of renewable generation and the associated intermittency issues


• Assess analytics/reporting capability and develop analytics program

• To achieve Maturity Level 2, piloting remote asset management program suggested

• Supporting Maturity Level 2 (Characteristic 2.4), network communications engineer has been hired. Additional evaluation of network communications strategy required (public vs. private and target coverage)



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• Automated decision making within protection schemes (Characteristic 3.6) to leverage Remedial Protection System

• Near real-time operational data used for grid operational management required for Maturity Level 4, and should be available by 2016

• For 2020, wide area management systems would be required for 4.5; significant capital investment


• Investment in grid operations capability must have clear return on investment or dramatically improve reliability in the first time horizon (2016). After 2016, lower fuel costs could allow for more investment to support investments around other drivers which don’t have immediate economic returns (e.g., investments to support DG or renewable penetration)

8.1.4 Work & Asset Management (WAM):

In the WAM domain, Jamaica shall target Level 2 maturity by 2016, Level 3 by 2020, and Level 4 by 2030 (See Figure 50).

Figure 50: Jamaica Work & Asset Management Domain Aspirations

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• Provides foundation for reliability improvements, which will be achieved by remote asset monitoring and preventative/reliability-centered maintenance

• Lowers capital expense requirement by utilizing remote asset monitoring and event tracking to keep assets in service longer

• Provides foundation for operational cost reductions, which will be achieved by optimizing workforce management (higher workforce productivity), asset maintenance (reduced maintenance expense), and inventory management (faster access to inventory)

• Reduce unplanned outages, improve SAIDI and shorten restoration times; thus leading to higher customer satisfaction

• Address safety issues highlighted in audits


• Develop an Asset Management Strategy, supported by business cases to evaluate asset management capabilities and the appropriate classes of assets for remote monitoring investment

– By 2016, develop plan defining asset management target capabilities with approach to track asset inventory and history

– Define integration between generation asset management and transmission/distribution (T&D) asset management

– Design asset replacement plan with asset monitoring capabilities identified to support the progression to remote asset monitoring in 2020 (i.e., avoid significant capital expense by leveraging existing capital budget and spend schedule)

• Plan for business process impacts relating to automated inventory management, mobile workforce strategy, and asset management strategy


• Change in standard practices

• Significant workforce implications

• Capital constraints limit investment timing, e.g., equipment monitoring and communication capability in Maturity Level 3 requires heavy capital expense

8.1.5 Technology (TECH):

In the TECH domain, Jamaica shall target Level 3 maturity by 2016 and achieving Level 4 by 2020 to be maintained through 2030 (See Figure 51).



Figure 51: Jamaica Technology Domain Aspirations


• Improve information management capability and availability based on business case (i.e., pursue advance capabilities based on ability to reduce costs) (Example: Characteristic 4.1 – “Data flows end to end from customer to generation”)

• Support grid operations with improved ability to monitor grid operations in 2016 (e.g., “advanced sensor plan”)


• Support electricity network observablity in 2016, with sensor plan developing requirements aligned to business value delivered (e.g., “advanced sensor plan”)

• Incorporate potential 3rd party interactions (e.g., demand response, micro-grids, distributed generation) in security requirements planning

• Define a Data Communications Strategy, which defines the communication requirements that meet JPS’s smart grid ambitions and network device roadmap (e.g., Intelligent Electric Devices communications and backhaul)




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• Capital expenses relating to foundational investments (e.g., data communications network) require ROI case to avoid impacting electricity costs

8.1.6 Customer (CUST):

In the CUST domain, Jamaica shall target Level 2 maturity by 2016, Level 3 by 2020, and Level 4 by 2030 (See Figure 52).

Figure 52: Jamaica Customer Domain Aspirations


• Initial focus on loss management allows JPS to meet OUR targets for loss

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– Experience indicates that “regularizing” customers receiving no-cost/stolen electricity will drop consumption by 60%

• Number one focus is on meeting lower electricity cost expectations

– Provides energy management tools to customers, which can assist in managing energy usage and expenses

– Demand management is a medium term driver (due to capital requirements)

• Targeting services to customer segments that value those services provides the opportunity for allocating costs and avoids adding to the energy cost/rate base for all customers


• Complete Demand Response Impact Assessment in 2014

• Develop a Demand Response strategy, which evaluates various options and sets a course for investment

• Level 3 Demand Response capability (Characteristic 3.4) requires near real-time information availability which requires significant capital investment

– On demand access to usage information (Characteristic 3.6) is possible with current meter system, and does not have similar capital requirement

• To drive Energy Efficiency programs, select target site for “smart building” demonstration


• Network infrastructure (e.g., communications , residential smart meters) is needed to realize Customer domain aspirations; investment choices and deployment coverage must be supported by business cases

• A driver for achieving maturity Level 3 is providing customers with access to real time usage information supported by a Demand Response Program, which is not possible by 2016

• Relocating meters from the customer premises is costly; a cost effective way must be identified, using smart grid to communicate to customers (e.g., Power Line Carrier)

8.1.7 Value Chain Integration (VCI):

In the VCI domain, Jamaica shall target Level 1 maturity by 2016, Level 2 by 2020, and Level 3 by 2030 (See Figure 53).



Figure 53: Jamaica Value Chain Integration Domain Aspirations


• Preparing for medium to long term customer demand and emerging opportunities to operate the grid more effectively and efficiently (e.g., demand management, additional resources)

– Improves reliability, by supporting additional energy resources (e.g., demand response, storage)

• Empowers customers by enabling broader choice with respect to energy resources


• Analyze results of Distributed Generation Penetration Survey (in progress by PCJ)

• Develop strategy to manage additional resources, e.g., demand response, distributed generation, residential home energy management systems (HEMS)

• Define timeline for supporting DG (i.e., when DG will impact grid feeder-level operations)

• Incorporate potential 3rd party interactions (e.g., demand response, micro-grids, distributed generation, HEMS) in security requirements

• Maturity Level 2 suggests energy management systems for customers

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• Define regulatory treatment of costs associated with enabling an expanded set of offerings and providers (e.g., home energy management systems)

8.1.8 Societal & Environmental (SE):

In the SE domain, Jamaica shall target Level 2 maturity by 2016, Level 3 by 2020, and Level 4 by 2030 (See Figure 54).

Figure 54: Jamaica Societal & Environmental Domain Aspirations


• Aligned to stated National Energy Policy goals (e.g., “environmental sustainability”, “development of renewable energy sources ”)


• Define smart grid vision which includes societal and environmental component

• To drive Energy Efficiency programs, select target site for “smart building” demonstration

• Incorporate “environmental” impact in decision making (e.g., triple bottom line decision making)

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– Develop decision making tools which measure societal and environmental impacts (e.g., impact on economy, pollutants reduction) and provide results for decision making

• Evaluated Time-of-Use (ToU) program, designed to shift peak, in 2020, with proof of concept in 2016 timeframe


• Regulatory approach that supports Energy Efficiency to motivate the JPS to move forward and create a “win” for JPS (i.e., defining new regulatory models to incent energy efficiency)

• Societal and environmental (S&E) programs (e.g., tools to measure S&E impact) will have costs; additionally, decisions supporting S&E may be more costly (e.g. lower economic return-on-investment) than other options



9 Appendix C

Through September and October, IBM has conducted topic sessions on key areas identified in the assessment of Jamaica’s priorities and challenges. With representation from Ministry of Science, Technology, Energy, and Mining (MSTEM), Jamaica Public Services Company (JPS), the Office of Utilities Regulation (OUR), the Petroleum Corporation of Jamaica (PCJ), IBM subject matter experts delivered presentations on potential approaches in each of these areas.

Presentation materials for each of these sessions are available through MSTEM.

9.1 Smart Grid Communications Deep Dive Discussion

Key topics discussed covered potential communications network ownership structures. Although the definition of potential ownership structures is out of scope for the Smart Grid Roadmap project, the team identified potential options including:

• Third party, public networks are a viable option. IBM held separate meetings with Digicel and LIME which specifically concluded that Digicel would be a viable partner for delivering communications to an expanding set of smart grid devices. This includes moving beyond Smart Meters to communications with network operational devices, which have more stringent communication requirements to ensure the safe and reliable operation of the electric grid.

• A Public Private Partnership or Consortium approach could be used to support the cost of rolling out a private network (i.e., JPS owned and operated) and extend the value of the network across other potential users, such as the water utility (i.e., transport water information) and other stakeholders (e.g., emergency services). In the case of London Hydro, this resulted in 40% savings to stakeholders where the cost charge back for network usage was 40% less than payment to a 3rd party telecommunications service provider.

• A hybrid network approach could include JPS building a wireless communications network covering Kingston and utilizing public services from an established telecommunications company to cover less dense areas outside Kingston.

9.2 Renewable Integration Deep Dive Discussion

While discussing the traditional and renewable generation expansion in progress, the working group discussed a number of challenges facing Jamaica including difficulty with frequency control in an island setting and working to lower the reserve margin. In addition, the increasing renewable penetration targets will drive electric grid management issues as more intermittent sources, such as solar and wind, are incorporated.

To manage renewable integration, the discussion focused on the complementary approaches of improved forecasting and utility-scale electricity storage. Globally, current renewable generation forecasting methods are often missing short-term ramp events (anecdotally, only one out of eight ramping events are accurately forecasted). Improved forecasting based on a wider set of data inputs has the potential to improve the utilization of renewable generation and lower the expensive requirements for additional stand-by generation and storage options.



9.3 Smart Water Deep Dive Discussion

Representation from the National Water Commission described Jamaica’s water management situation, highlighting efforts to address the technical and non-technical losses contributing to over 65% unbilled water.

IBM reviewed case studies that demonstrate approaches to utilizing monitoring and analytics to improve water management efficiencies (e.g., reduced losses) and optimize electricity demand to support more efficient operation of the electricity grid. Approaches to drive value across JPS and NWC were discussed, including straightforward infrastructure alignment efficiencies (e.g., meter reading), rate programs and incentive plans that increase the economic alignment between JPS and NWC in the efficient operations of their networks, and additional customer alignment initiatives for efficiencies in customer management (e.g., bill presentment, customer comparison for anomaly detection).

9.4 Customer Conservation Deep Dive Discussion

Loss management will be an important work stream in Jamaica’s Smart Grid Roadmap. The IBM team reviewed loss management approaches seen at other utilities to address different types of non-technical loss, including review and refinement of back-office processes, increased frequency of field visits, hardening of assets (e.g. central metering in cabinets), and increased network sensors including AMI meters (See Figure 55).

Figure 55: Non Technical Losses Possible Recovery Actions

A prepaid electricity program was also a focus of the session with references to prepayment solutions in different geographies. Limited experience in North America and global examples, such as Meralco in the Philippines, demonstrate the additional energy cost control that prepayment

Non Technical

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programs give customers. In addition, prepayment lowers utility debt write-offs by limiting bad debt exposure and provides a mechanism to incorporate arrears payments into the prepayment program.

Finally, Time-of-Use (ToU) billing was included in the discussion. The benefit of wide-scale residential deployment is in question because there is not a large obvious load to shift with tiered pricing (i.e., it is difficult to motivate behaviour away from the evening peak representing cooking and evening lighting). However, ToU and energy management tariffs (e.g., interruptable load tariffs, which reward volunteers in a load curtailment program) for key customer segments (e.g., commercial and industrial customers) are opportunities to impact fuel costs and support JPS grid management objectives by aligning demand with network availability.

9.5 Asset Management Deep Dive Discussion

Understanding that JPS is in the process of planning its asset management program, the session incorporated a discussion of different maturity levels in asset management and identified key recommendations to guide technology choices (e.g., asset management system) that are anticipated in the coming years.

With JPS’s focus on asset management, a number of initiatives were discussed in this area, including deploying an asset management solution, integrating the existing workforce management system with the planned asset management system to realize the full value of these investments, and deploying remote asset monitoring across key asset classes. The longer term view included driving Reliability-Centered Maintenance down to the substation level. The discussion highlighted the need to drive culture change to incentivize asset failure avoidance, rather than rewarding asset fixes.

9.6 Distributed Energy Resources Deep Dive Discussion

The “Net Billing” program pilot has resulted in the recent commissioning of 5 distributed generation sites (i.e., customers with 100 kW or less) and approximately 50 applications in the pipeline. Due to the high electricity costs and decreasing system costs, Jamaica is experiencing the arrival of photovoltaic (PV) grid parity (i.e., the cost of electricity supplied by a residential PV system is less than the cost of regulated electricity pricing) and is looking at a longer term trend in this area (See Figure 56).



Figure 56: PV Grid Parity Arriving

As a result, different rate structures will be required to support the existing infrastructure investment used by “net zero” customers and other business models where the infrastructure may be owned by 3rd parties.

9.7 Smart Buildings Deep Dive Discussion

Jamaica has undertaken an Energy Efficiency and Conservation project which includes enabling the efficiency of buildings through retrofits in the areas of cold roofing, solar tinting, air conditioning and lights.

Due to high energy costs, such as those in Jamaica, and the fact that energy costs represent 23 percent of the total occupancy costs of facilities (“IBM Smarter Buildings Survey: Customers Rank their Office Buildings,” page 2. April 29, 2010. http://www-03.ibm.com/press/attachments/ IBM_Smarter_Buildings_Survey_White_Paper.pdf), the value of reducing facility energy use is clear.

In addition to the important steps that Jamaica is taking to support building energy efficiency, the discussion defined Smart Buildings as more than just energy management to include all the elements of monitoring and managing occupancy (e.g., financial, operational, and asset efficiency). This includes designing leases that move away from the inclusion of all energy costs in the lease payments to incentivize energy efficiency investments and shared benefits from the same (e.g., rather than leases that include unlimited energy, leases share the energy efficiency costs and benefits).

The discussion highlighted that organizations achieve their environment and energy management goals by recognizing the use of three key tactics:

� Operations and maintenance – Identify operational improvements to help reduce facilities maintenance downtime and costs, including proactively maintaining facilities, as well as making sure equipment is operating at peak efficiency

China

South Korea

India

Greece

Texas

California

Spain

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Japan

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UK

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Sweden

NorwayGermany

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Source: McKinsey, PG&E, Pike, EIA

Projected Grid Parity of Key Locations (without incentives)

China

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� Portfolio and project management - Identify priorities for funding allocations, analyse project risks and financial benefits, and manage project management controls and alerts

� Facilities space management – Identify areas of improvement to increase utilization of leased assets and reduce the number of facilities across the organization, which in turn generates increased return on assets



10 Appendix D

10.1 Smarter Planet Value Quantification Model Inputs

Figure 57: JPS/Jamaica Value Model Inputs 1



Figure 58: JPS/Jamaica Value Model Inputs 2

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