smart grid and meter data management systems

Copyright © 2011 by ScottMadden. All rights reserved.

Smart Grid and Meter Data Management Systems

October 2011

Contact: [email protected]

[email protected]

mailto:[email protected]


Framework For the Integrated Smart Grid

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Applications and

Technologies

Distribution

Automation

EMS, DMS, OMS,

GIS

Event detection and condition based response, fault protection,

congestion management, remote switching, voltage control

Distribution and substation automation, asset protection, power

quality management, automated feeder configuration, operation

closer to true system limits

Point of consumption voltage

and current readings

Demand

Response

Peak load management

and control

Short interval energy data acquisition, Load forecasting and load

shifting

Data about visualization of and

control of energy end use

AMI AMI, MDM, CIS, Outage

Detection, Billing

Remote meter reading, remote connect/disconnect, theft

detection, customer prepay, real time pricing

Real time customer access to

meter data

Distributed

Generation

Visibility and control

systems for distributed

assets

Monitoring, dispatch and control of distributed assets such as

renewables, CHP and energy storage devices

Integration of distributed

generation assets, enablement

of VPP, and microgrid structures

VPP and

Microgrids

Visibility and control

systems for distributed

assets

Aggregation of supply and demand resources into a network that

is either always grid tied (VPP) or can be islanded from the grid

(Microgrid)

Virtual Power Plants (VPP) and

Microgrids

Smart

Charging of

EV and PHEV

Utility control and load

monitoring for EV and

PHEV applications

Application data flow for EV and PHEVs

End-user interface for smart

charging and vehicle-to-grid

applications

Customer

Solutions

Integration of utility systems

into consumer business

processes

Application data flow to/from end-user energy and building

management systems

Home/building portals, online

billing, and pay/prepay, TOU

pricing data

Source: Greentech Media Research; EKA Systems; ScottMadden: “Integrating Smart Grid into Strategic and Business Planning” 2009; EPRI Smart

Grid, March 2011; EPRI Field Area Network, April 2011

Communications

LAN

Local Area

Network

WAN

The backhaul network between the AMI

Network and the utility

AMI NETWORK

The Field Area Network is the

communications infrastructure that links

the smart meter and the WAN to allow two-

way real time data transfer

HAN

Grid aware devices linking

loads and appliances for

utility and consumer control

and management

Power Generation Transmission Substation Distribution Home or Building

Utility System Application Functionality End-User Data

Meter Data Management Systems are required for all Applications and Technologies listed below

Adapted from Greentech Media Research

Meter Data Management Overview


Meter Data Management Overview

AMI/Smart Grid implementations are creating problems of “big data” that is overwhelming legacy systems and creating demand for efficient Meter Data Management systems

“Big data” is choking the legacy information systems: both back-office IT and operations technology (OT)

— An industry executive recently remarked: “where are we going to store all this data, how will we organize it and how can we utilize it to improve our business?”

— Legacy systems cannot parse new types of information and have a severe lack of adequate storage capacity

Meter Data Management systems deal with issues of big data and can include and assist with the following systems

— Meter Data Repository (MDR)

— Advanced Metering Infrastructure (AMI)

— Smart Grid Applications (such as Demand response, outage management systems, etc.)

The MDM market is driven by a combination of regulation and utility modernization, and it is likely to grow substantially in the near future despite some limitations to growth

Grid security has been a constant struggle for Smart Grid defenders and without an organized MDM system increasing data will create more security fears

The MDM market is still relatively immature and unpredictable (as highlighted in the most recent Gartner “magic quadrant” assessment) but there are successful implementations from which we can glean best practices

— Establishing utility-specific goals for Smart Grid applications, data collection and end-user interfaces with AMI/MDM systems is important before selecting a vendor

— Deploying MDM systems at the same time as AMI infrastructure has proven more cost-effective than waiting

— Employee and customer education is important throughout the process of AMI/MDM implementation

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MDM systems are proving to be an essential aspect of Smart Grid implementations, especially as projects begin

to scale up and the amount of data increases exponentially.


What is Meter Data Management (MDM)?

Smart Grid is largely about data, including gathering new data through new technologies and bringing together data from previously disparate systems

MDM systems have to cope with increasing amounts of data and a variety of applications

MDM systems can be customized to specific utility requirements

— Service Oriented Applications (SOAs) are likely to be the norm for Smart Grid implementations

— Enterprise service buses (ESBs) will be required to translate between applications and will also be required for translating within MDM systems and the AMI infrastructure

Below is a visual representation of how MDM systems fit into the larger picture of Smart Grid implementation

— The MDM system is separate from the in-office IT systems, and forecasts suggest that they are likely to stay separate, though they will have to work much more closely than in legacy systems

— Within the MDM systems’ architecture are modules and/or application nodes that allow the system to assess, synchronize and analyze data coming from multiple sources and between networks

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Source: Powergrid International, 2011


What is Meter Data Management (MDM)? (Cont’d)

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MDM systems are not uniform, but many have similar modules. The table below is based on the Ecologic model for MDM system modules and products. Its product is more of an umbrella MDM System integration that covers any and all Smart Grid applications, but any combination of the following are available from different producers

MDM System Modules Overview Applications Assisted

by Module

Meter Data Repository (MDR)

• Responsible for assessing, synchronizing, and storing meter data long term

• Primary storage module, though given the complexity and amount of incoming data, storage is likely to exist across the MDM system

All

Network Performance Monitor (NPM)

• Tracks irregular, disrupted performance across meters to determine issues and outages

Demand response; Outage management

Data Synchronization Engine (DSE)

• Cross-checks and synchronizes incoming data to limit inaccuracies from meters

Billing; Back-office synch

Virtual Metering (VME) • Summarizes and aggregates usage Billing; Demand

response

WAVE/iWAVE • Works with AMI systems to certify usage at intervals (WAVE intervals are

daily; iWAVE intervals are whatever the AMI system will allow) Billing; Demand response

Meter Reading Analytics (MRA)

• Runs algorithms to calculate usage baselines to determine irregularities from specific areas

Demand response;

On Demand Engine (ODE)

• Allows users to connect/disconnect/display usage in real-time Billing, Demand response; outage management

Enhanced Outage Management (EOM)

• Works to spot outages in real-time to improve response time Outage management

Source: Ecologic 2011

Meter Data Management Market


Market Drivers for MDM Integration

MDM integration growth can be explained by four primary market drivers

Regulation (American Recovery and Reinvestment Act and the Smart Grid Investment Grants)

— Approximately $3.4 billion has been allocated to the SGIG for smart grid development

At the state level, Public Utility Commissions (PUCs) are stepping up requirements for utility companies

— PUCs often grant utilities guaranteed rates of return on capitalized assets, which incentivizes utility companies to invest heavily in capital projects, such as new MDM systems

— The California PUC has developed the first set of standards for smart meter implementation for utility companies

The ruling outlines standards for access data for consumers, data security, tier alerts for rate changes, etc.

The ruling also calls for new smart meter and AMI system integrations to be approved by the PUC

Supply/Demand management issues (especially for renewable energy integration)

— As renewable energy gains market share, successful integration and energy storage can only be successful with improved AMI, which requires MDM systems

Utility Modernization

— Utilities pressured to modernize by competition, regulation and in order to improve declining revenues

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MDM systems integration is proving a necessary part of Smart Grid integration, and companies can reap

economic benefits for implementing early and while regulation still favors it


Limitations to MDM Growth

There are three primary limitations to MDM growth and increased implementation, other than high capital costs

Lack of robust standards for functionality and communications

— The Smart Grid Interoperability Panel (SGIP) is currently evaluating several priorities for standards and is integrating feedback from Smart Grid producers for the NIST

They have developed 19 Priority Action Plans (PAP) that are currently under revision

Waiting for regulations and standards to develop is ill advised, as it is likely to be an ongoing process

Shortages in skilled IT staff

— Shortages in skilled IT staff are a problem with most new technologies and will ease over time as the markets mature

— Shortages might also be linked to a lack of investment in IT by utility companies which has been a chronic and widespread issue for the utility industry

Incomplete and immature SOAs (Service Oriented Applications) at utilities

— SOA has become a catch-all phrase to describe new applications to be integrated into the Smart Grid

— Many of the applications will require MDM systems to support the influx of data, and without understanding the effects of these SOAs, it is difficult to build adequate MDM systems

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Despite these limitations Smart Grid MDM systems sales are predicted to grow consistently over the next 5

years, and by 2014 the MDM market will be around $221 million to upwards of $450 million by 2018


Grid Security, Data Privacy and MDM Systems

Two major issues have emerged to highlight Smart Grid security and privacy issues

Two major issues have

Many transmission industrial control systems, such as supervisory control and data acquisition (SCADA), have remained relatively free from attack simply because they are isolated from corporate networks - Unfortunately, the Stuxnet attackers have solved that by using universal serial bus (USB) drives, which have no need of an Internet to spread, as their attack medium.

Realization of the smart grid’s potential will require new interfaces between IT and ICS networks which further erodes the isolation that has given a sense of protection to ICS

Given the patchwork systems that are likely to form, security will becoming an increasing risk due to increased vulnerabilities at every interconnection, application, enterprise service busses, between networks, within networks, etc.

With utility companies having access to significant data about individual private citizens, there are bound to be concerns about how that data is used, who has access to the data, and how it is protected. Utilities can expect regulation around the use of data, with corresponding compliance and reporting requirements.

There are several steps to take to limit security risks in AMI/MDM systems

— Assess how you collect and manage customer data

— Determine changes to all business processes from AMI/MDM systems integrations

— Take vulnerability assessments

— Profile possible threats to the system

— Develop comprehensive security management plans

Cloud computing has proven too insecure for Smart Grid applications, but may resurface after it matures

— Google and Oracle dropped production of Smart Grid cloud technologies within a week of each other

— eMeter has teamed with Verizon to develop cloud technology for MDM systems, but have yet to release

— Indicators show that data is likely to be stored across nodes and at different hubs to allow for real-time data applications

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Source: Powergrid International, 2011; Pike Research, 2011


Grid Security, Privacy and MDM Systems (Cont’d)

At a minimum, the following security issues must be addressed:

Stronger identity management

Multi-factor authentication protocols

Computer incident response programs and procedures

Change management, asset management, and configuration management

Business continuity planning

In-depth defense processes and procedures for IT and ICS networks

Stronger security on SCADA control systems

More secure interfaces between IT and ICS networks

Video monitoring capabilities for substations and control rooms

End-to-end encryption of data from the HAN to the utility central site

Process to prevent worms from spreading through smart meters

Stronger cyber security software on smart meters

Resiliency throughout the advanced metering infrastructure (AMI)

Data integrity for electric vehicle recharging transactions

Data privacy for electric vehicle billing data and recharging transactions

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Source: Powergrid International, 2011; Pike Research, 2011

Utilities Companies and Implementing MDM Systems


Utility Companies and MDM Systems

Utility companies are confident in the technology for MDM systems but are less confident in their own ability to integrate that technology into existing IT and OT systems

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Survey Results: How concerned are you

with your company’s ability to assess and

deploy the following applications?

Survey Results: Indicate the degree to

which you feel that there is a technology

gap in the following categories.

Source: Greentech Medie 2011

Despite limited market maturity, utilities know they need MDM systems to manage new types of incoming data

and they know that effective MDM systems are available. They just do not know how to implement new MDM

systems into existing systems architecture.


Strategic Use of Automated Meter Data

The traditional approach to Smart Grid projects focuses on technology, process, and organization -- a more holistic approach recognizes the role and importance of data as a strategic driver

Transformation Drive

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Metering

Devices

AMI

Data

Collection

Meter Data

Validation

Meter Data

Warehouse

Customer Information Systems

Billing Protocols

Service Order

Mgmt Meter

Programming

Asset Mgmt

Meters &

Devices

Reporting

Settlements

Load Research

Load Forecasting

Data Analysis

Rates

Regulatory

Resource Planning

Sales & Marketing

Traditional Data Uses

Interval demand and consumption

Meter status and error reporting

Even completion notification

Condition alerts (tampering, voltage conditions)

Feeder status, monitoring and segmentation

Distributed generation data

PHEV data

HAN data

Power quality monitoring and incident reporting

Grid voltage measurements

Emerging Data Uses

Traditional AMI/AMR installations have focused on hardware, system implementation and infrastructure deployment

Optimizing the benefits of Smart Grid requires a data-driven transformation in addition to technology and process

Data is closely intertwined with technology and process, but it doesn’t provide optimized value automatically. The potential benefits of data must be deliberately identified and developed

New AMI meters provide an abundance of data on meter condition and events. Real-time access to this data provides opportunities to get “smart” about meter asset management.

Data can be used to improve operations at micro and macro levels of Asset Management Metering, Billing, & Customer Service Supply Chain decision making


How to Integrate MDM Systems

The following are general steps for planning an MDM implementation for utilities

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Develop MDM Vision

Outline Deployment

Baseline

Determine Gaps

Create Phased

Roadmap

Determine specific goals for the utility

Decide on types of data to include before consulting vendors and exploring options

Determine data usage and storage needs

Engage business units in storage needs versus costs

- Frequency of updates

- Amount of history to keep

- History detail versus summary records

Ask, “what problems are we trying to solve?”

Outline what infrastructure is currently in

Application interfaces can be difficult to connect but can be remedied if the end-to-end system is well understood

Incorporate both in-office IT systems and operating technologies – both will be involved in MDM implementation

Ask, “what is our strategy?”

Determine what is missing from the current infrastructure that is required to meet the goals outlined in the vision

Include gaps in technology, application, communications networks, and possible staffing issues

- End-user

integration and

cooperation is also

an important gap

that will likely need

addressing

Ask, “what are the pitfalls?”

Create a roadmap that outlines manageable steps for each of the integration steps based on the gap analysis

Identify any and all interface challenges between existing technologies/applications

- ESBs might be

required to ‘translate’

between older

applications and new

SOAs

Incorporate feedback from all employees (management, IT) that would be affected by changes

Ask “how do we make it work?”


Contact Us

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Jon D. Kerner

Partner ScottMadden, Inc.

3495 Piedmont Rd, Bldg 10

Suite 805

Atlanta, GA 30305

Phone: 404-814-0020

Mobile: 262-337-1352

[email protected]

Jere “Jake” Jacobi

Partner ScottMadden, Inc.

3495 Piedmont Rd, Bldg 10

Suite 805

Atlanta, GA 30305

Phone: 404-814-0020

Mobile: 262-337-1352

[email protected]



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