Power Delivery Network Smart Grid and Big Data Applications Power Delivery Network Smart Grid and Big Data Applications Power Delivery Network Smart Grid and Big Data Applications Power Delivery Network Smart Grid and Big Data Applications

Presented at the 3rd Annual Indonesia Power Conference 27th to 30th Presented at the 3rd Annual Indonesia Power Conference 27th to 30th November 2012, Jakarta, Indonesia

Himadri Banerji, Ex Chief Executive Reliance Energy Ltd India Himadri Banerji, Ex Chief Executive Reliance Energy Ltd India Himadri Banerji, Ex Chief Executive Reliance Energy Ltd India Himadri Banerji, Ex Chief Executive Reliance Energy Ltd India & MD EcoUrja & MD EcoUrja & MD EcoUrja & MD EcoUrja

2Utility business processes operating as separate legal entities in a deregulatedUtility business processes operating as separate legal entities in a deregulatedUtility business processes operating as separate legal entities in a deregulatedUtility business processes operating as separate legal entities in a deregulatedenvironment. (Courtesy of ABB.)environment. (Courtesy of ABB.)environment. (Courtesy of ABB.)environment. (Courtesy of ABB.)

The Mission StatementThe Mission StatementThe Mission StatementThe Mission StatementApproach to T&D Network PlanningApproach to T&D Network PlanningApproach to T&D Network PlanningApproach to T&D Network Planning

Drivers for Total Network InvestmentDrivers for Total Network InvestmentDrivers for Total Network InvestmentDrivers for Total Network Investment

1. "Our company will be the premium regional provider of electric power. Recognizing that its current financial situation prohibits competing on the basis of price, this utility has decided to make quality and service its hallmark. Achieving lowest possible cost is not the goal; achieving lowcost while meeting high service standards.

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cost while meeting high service standards.2. "Provide economical electric power for the prosperity of the region. This utility has a long-standing tradition of low rates, a way of attracting new industry (i.e. growth) to the region. Plans that invest a good deal to improve quality are simply "not with the program. Marginal quality improvements in a new plan are permissible, only if they lead to lower cost.

Implementing Renewable Implementing Renewable Implementing Renewable Implementing Renewable Energy Directive Energy Directive Energy Directive Energy Directive

Drivers for Total Network InvestmentDrivers for Total Network InvestmentDrivers for Total Network InvestmentDrivers for Total Network Investment

In order to reach the 15% overall energy target, the RES suggests that: More than 30% of electricity is to be generated from renewable sources; 12% of heat is to be generated from renewable sources such as biomass, solar and heat pump sources in homes and businesses; 10% of transport energy is to come from renewable

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businesses; 10% of transport energy is to come from renewable sources. The RES recognises that increasing generation from renewable will have implications for grid investment, grid technology and grid connection policy. All of these issues have the ability to impact on T&Ds investment plans.

Approach to analysis of integrating Approach to analysis of integrating Approach to analysis of integrating Approach to analysis of integrating renewablesrenewablesrenewablesrenewables

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Approach to analysis of integrating Approach to analysis of integrating Approach to analysis of integrating Approach to analysis of integrating renewablesrenewablesrenewablesrenewables

6Example of Example of Example of Example of VCCVCCVCCVCC----HVDC HVDC HVDC HVDC transmission transmission transmission transmission for a Wind Turbine Integrationfor a Wind Turbine Integrationfor a Wind Turbine Integrationfor a Wind Turbine Integration

Major Challenges

Security of electricity supplySociety is becoming more and more dependent on reliable and high-quality electricity supply. The power industry around the world continues to face an ever changing technological and regulatory environment.

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The power industry around the world continues to face an ever changing technological and regulatory environment.

As a result of the efforts to combat climate change, deployments of wind, solar, tidal, wave and other power generators with variable and less certain power output are being installed and will continue to be installed on a large scale.

LoadLoadLoadLoad forecastforecastforecastforecastforforforfor thethethethe leadleadleadlead----timetimetimetimeyear(s)year(s)year(s)year(s)

ExistingExistingExistingExisting systemsystemsystemsystem&&&& plannedplannedplannedplanned additionsadditionsadditionsadditionsthroughthroughthroughthrough leadleadleadlead----timetimetimetime

Short-rangePlanning process

SHORTSHORTSHORTSHORT----AND LONGAND LONGAND LONGAND LONG----RANGE PLANNINGRANGE PLANNINGRANGE PLANNINGRANGE PLANNING

Drivers for Total Network InvestmentDrivers for Total Network InvestmentDrivers for Total Network InvestmentDrivers for Total Network Investment

Power Power Power Power system system system system studiesstudiesstudiesstudies Planning process

IdentifiedIdentifiedIdentifiedIdentified areaareaareaareacapacitycapacitycapacitycapacity shortfallsshortfallsshortfallsshortfallsandandandand solutionssolutionssolutionssolutions

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studiesstudiesstudiesstudies

Chasing Higher IRRs

Integrated Big Data and

Enterprise GIS for

Capital Budgeting

Expectations of Power UtilityExpectations of Power UtilityExpectations of Power UtilityExpectations of Power Utility

Improve revenue by improving ENS ( Energy Not Served). Improve performance by improving SAIFI, SAIDI.

Improving Customer Complaints logs in Trouble Call Management.

Long-standing faults brought to a minimum.Long-standing faults brought to a minimum.

Limiting number of interruption per day a) Breakdown b) Preventive Maintenance c) Load-shedding.

Expectations of Power UtilityExpectations of Power UtilityExpectations of Power UtilityExpectations of Power Utility

Good collection & billing System.

To reduce Outage Time.

To stop Power theft.

To provide better services to the consumers.

To have stabilized Asset Management System.

Safety- Zero fatality rate.

On August 14, 2003, large portions of the MidwestOn August 14, 2003, large portions of the MidwestOn August 14, 2003, large portions of the MidwestOn August 14, 2003, large portions of the Midwestand Northeast United States and Ontario, Canada,and Northeast United States and Ontario, Canada,and Northeast United States and Ontario, Canada,and Northeast United States and Ontario, Canada,experienced an electric power blackout. The outageexperienced an electric power blackout. The outageexperienced an electric power blackout. The outageexperienced an electric power blackout. The outage

affected an area with an estimated 50 millionaffected an area with an estimated 50 millionaffected an area with an estimated 50 millionaffected an area with an estimated 50 millionpeople and 61,800 megawatts (MW) of electricpeople and 61,800 megawatts (MW) of electricpeople and 61,800 megawatts (MW) of electricpeople and 61,800 megawatts (MW) of electric

load in the states of Ohio, Michigan, Pennsylvania,load in the states of Ohio, Michigan, Pennsylvania,load in the states of Ohio, Michigan, Pennsylvania,load in the states of Ohio, Michigan, Pennsylvania,New York, Vermont, Massachusetts, Connecticut,New York, Vermont, Massachusetts, Connecticut,New York, Vermont, Massachusetts, Connecticut,New York, Vermont, Massachusetts, Connecticut,

and New Jersey and the Canadian province ofand New Jersey and the Canadian province ofand New Jersey and the Canadian province ofand New Jersey and the Canadian province ofOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes afterOntario. The blackout began a few minutes after4:00 pm Eastern Daylight Time (16:00 EDT), and4:00 pm Eastern Daylight Time (16:00 EDT), and4:00 pm Eastern Daylight Time (16:00 EDT), and4:00 pm Eastern Daylight Time (16:00 EDT), and

power was not restored for 2 days in some parts ofpower was not restored for 2 days in some parts ofpower was not restored for 2 days in some parts ofpower was not restored for 2 days in some parts ofthe United States. Parts of Ontario suffered rollingthe United States. Parts of Ontario suffered rollingthe United States. Parts of Ontario suffered rollingthe United States. Parts of Ontario suffered rollingblackouts for more than a week before full powerblackouts for more than a week before full powerblackouts for more than a week before full powerblackouts for more than a week before full power

was restored.was restored.was restored.was restored.

Relational database (RDB) Rise to prominent use by utilities

However failure of traditional databases like RDBs to scale well in the face of rising data volumes, complexity, and speed has been well proven, with alternative technologies often outperforming them by more technologies often outperforming them by more

Object-oriented databases (ODB) and emerging NoSQL technologies, HADOOP,

Big Data is typically considered to be a data collection that has grown so large it cant be effectively or affordably managed (or exploited) usingconventional data management tools: e.g., classic relationaldatabase management systems (RDBMS) or conventionalsearch engines, depending on the task at hand. This can as easily occur at 1 terabyte as at 1 petabyte, though most discussions concern collections that weigh in at several terabytesat least.

To satisfy these imposing requirements constraints, Web entrepreneurs developed data management systems that achieved supercomputer power at bargain-basement cost by distributing computing tasks in parallel across large clusters of commodity servers. They also gained crucial agility and further ramped up performance by developing data models that were far more flexible than those of conventional RDBMS.

The best known of these WebThe best known of these WebThe best known of these WebThe best known of these Web----derived technologies are nonderived technologies are nonderived technologies are nonderived technologies are non----relational databases relational databases relational databases relational databases (called (called (called (called NoSQLNoSQLNoSQLNoSQL for Not for Not for Not for Not----OnlyOnlyOnlyOnly----SQL, SQL being the standard language for querying SQL, SQL being the standard language for querying SQL, SQL being the standard language for querying SQL, SQL being the standard language for querying

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(called (called (called (called NoSQLNoSQLNoSQLNoSQL for Not for Not for Not for Not----OnlyOnlyOnlyOnly----SQL, SQL being the standard language for querying SQL, SQL being the standard language for querying SQL, SQL being the standard language for querying SQL, SQL being the standard language for querying and managing RDBMS), like the and managing RDBMS), like the and managing RDBMS), like the and managing RDBMS), like the

HadoopHadoopHadoopHadoop framework (inspired by Google; developed and openframework (inspired by Google; developed and openframework (inspired by Google; developed and openframework (inspired by Google; developed and open----sourced to sourced to sourced to sourced to Apache by Yahoo!) and Apache by Yahoo!) and Apache by Yahoo!) and Apache by Yahoo!) and Cassandra (Cassandra (Cassandra (Cassandra (FacebookFacebookFacebookFacebook), ), ), ),

and search engine platforms, and search engine platforms, and search engine platforms, and search engine platforms, CloudViewCloudViewCloudViewCloudView (EXALEAD) (EXALEAD) (EXALEAD) (EXALEAD) NutchNutchNutchNutch (Apache).(Apache).(Apache).(Apache).

in real-time

to identify anomalies If you have these

situational awareness means

what you need to know, have control of &conduct analysis for

having an understanding of

to identify anomalies in normal patterns or behaviours that can affect the outcome of a business or process.

If you have these things, making the right

decision in the right amount of time in any

context becomes much easier

Veracity Validity Volume Velocity Variety

Data from Utilities devices and sensors has an extraordinarily broad range of relevant time durations for which they are Data from Utilities devices and sensors has an extraordinarily broad range of relevant time durations for which they are Data from Utilities devices and sensors has an extraordinarily broad range of relevant time durations for which they are Data from Utilities devices and sensors has an extraordinarily broad range of relevant time durations for which they are valuable to the business, from milliseconds, to decades valuable to the business, from milliseconds, to decades valuable to the business, from milliseconds, to decades valuable to the business, from milliseconds, to decades

The utility industry's time scales vary over 15 orders of magnitude due to the unique diversity of sensors and critical business processes, and often at much faster intervals than other industries, which, when trying to create scalable situational awareness, impacts all five Vs of the industry's Big Data pressures.

There There There There were three time windows where situational awareness would have given sufficient time to adequately were three time windows where situational awareness would have given sufficient time to adequately were three time windows where situational awareness would have given sufficient time to adequately were three time windows where situational awareness would have given sufficient time to adequately respond. respond. respond. respond.

Enterprise wide Geographical Information System (GIS) in REL

Network Data

SLDs, Layouts, Cable Routes

Equipment Data

Specifications, Diagrams, Operational History

Structural Data

Towers, Pillars, Poles, Plinths

New EHV Stations , HVDS, LTMP,

O&M etc.

ArcSDE, ArcIMSArcCatalog, ArcMap

Enterprise Data Management GIS Platform

Consumer Data

Name, KNo., Service Line, DT No

Responder OMS, ArcFM

Network Analysis Tools, Application Programs

Seeing is believing !!!!!!!We have seen it

BusinessSupport

Transmission/DistributionWMS/Staking/IVR

CustomerCare (CIS)

XML

Integration Framework

XML XML XML

System Architecture

ArcGIS(Core GIS Functions)

OpenRDBMS

ArcFM Solution(Models and Tools for Mapping and Network Data Management)

System Architecture

Need for GIS Impressive progress in power sector, but still insufficient.

Demand

Widening gap between demand and supplydue to T& D losses amounting to 25% in the

Supply distribution link.

Losses BYPL BRPL

AT&C Loss % 50.71 39.68

Distribution Loss % 48.11 42.7

No. of Consumers 836000 1070000

Target T & D loss Reduction Solution 1) Implementation of GIS modules2) Distribution management thru GIS

The estimated T&D losses for the fiscal 04-05 for BRPL and BYPL, Delhi

Estimates of Implementing GIS at Delhi

Initiatives taken by GIS PMO group established at CEO Office of the company are as follows -

Development of Functional Requirements and Data Model. Updating of Reliance Corporate Land base Maps. Capturing the entire EHV/HV network. Capturing the entire LV network. Capturing Consumer Information. In House Digitization and field QC. Consultancy Services by REL

Updating of Reliance Corporate LAND base Maps Integrated large scale corporate land base map prepared based on RICs data requirements with base data as IKONOS imagery imported from Space Imaging. IKONOS imagery digitized by RDWL team through network of digitization vendors. Maps supplemented with field survey information conducted by contractors identified by RDWL.

Flaw in above system Information updated by RDWL was insufficient for locating Electrical network and individual Consumer Service points.

Solution * Updating of all buildings with service line feeding

* Including all new transport features including road, railway, flyovers.

Codification Guidelines of RDWL

Providing unique id to all building for its identification.

Linking it with its consumer/service line.

road, railway, flyovers.

Unit Unit Cost Qty.Total Cost

(Mn) Cost Per

Consumer

Land Base Sq Km 20,000 900 18 9.44

Land Base Updating Polygons 8 1,000,000 8 4.2

Cost Estimates for Land base and Updating

Development of Functional Requirements and Data Models

ESRI / M&M appointed as GIS service providers by REL ( on behalf of BRPL and BYPL ) for- studying existing system.- developing functional requirement for proposed GIS.

GIS Tools * COTS available platforms from ESRI.* Third party applications from Miner and Miner.* Customer Applications for GIS interfaces for integration with other applications

- SAP (ISU-CCS for Consumer Information).- SAP (PM) for Operations and Maintenance.- Cymedist Interface for Network Analysis.- Cymedist Interface for Network Analysis.- GIS Interface for SCADA system.

Development of tool based on functional requirement and application design document approved by REL for ESRI / M&M

Testing and approval for implementation at cluster Citrix application servers at DAKC.

Applications made available for access from anywhere in the Reliance Network including both the DISCOMS in Delhi.

Capturing Entire EHV/HV NetworkPhase 1The GIS data dictionary included the entire network of EHV and HV. EHV Grid Stations and their equipments. 11/0.44 kv substations and their equipments. 66.33 and 11 kv feeders.

Survey agencies identified for capturing

EHV/HV networks.

Digitization of captured Unit Unit Cost Qty.

Total Cost (Mn)

Cost Per Consume

r

Digitization of captured data using in-house

digitization tools developed by RDWL and REL

Digitized data migrated to REL Corporate electric

data base server at DAKC.

Database made accessible through ESRI COTS and

customer application from anywhere in Reliance WAN including both DISCOMS in

Delhi.

33/66 KV Conductor Km

33/66 KV Cables Km 650 476 0.3094 0.16

11 KV Conductor Km

11 KV Cables Km 650 1,441 0.9367 0.49

EHV Station Nos 2,500 124 0.31 0.16

HV Stations Nos 500 8,000 4 2.1

Cost Estimates for EHV / HV Data Collection

Capturing the entire LV Network

Phase 2Capturing LV network

Features captured Consumer Feeding Points

* LV Support Structures* LV Feeder Pillars* Street Light Structures

LV Feeder Network (0.44 kv ) connectivity

Consumer Feeding Structure points codified with unique codes for linking them with respective

set of consumers.

This would enable linking of every consumer with its feeding point & 11/440 v substation, required for

energy audit, NA, O&M and other applications.

LV Feeder Network (0.44 kv ) connectivity

UnitUnit Cost Qty.

Total Cost (Mn)

Cost Per Consum

er

Feeder Pillars/Support Structures SS 8 800,000 6 3.36

Cost Estimates for LV Data Collection

In-House Digitization and Field QCData being captured is governed with stringent QA requirements based on feature being captured

Team deputed for carrying out QC who conducts field checks before accepting data for digitization

Data is then handed over to Data is then handed over to digitization team where digitization is done using industry standard CAD/GIS packages.

Capturing Consumer InformationNon-availability of accurate consumer records had been one of the main reasons for commercial losses.

GIS based consumer indexing has been carried out by many DISCOMS / SEBs, without much of a fruitful result.

At BSES, Delhi it is at a conceptual; stage and different models are being evaluated for collecting consumer information

The consumer data being collected will be integrated with its building id for its spatial location and network connectivity with its feeding structure id in GIS.

Unit Unit Cost Qty.

Total Cost (Mn)

Cost Per Consume

r

Consumers Consumer 7 1,906,000 13 7

Cost Estimates for Consumer Data Collection

Skeleton of GIS

SCADA

NO

CIS

NO

CIS SAP

OMS

DATA

INTEGRATION AS A CONCEPT

Use work process flows to define touch points of integration to support business processesUse enterprise and process modelingto describe how data and components service the needed business processes

Shared data doubles the accuracy and quality requirements

look at the data from each systems perspective (financial vs. operations)

INTEGRATION AS A CONCEPTWhen Should Integration be Considered?

Data/applications exist in many placesMerger/acquisition of requirementsSupporting thousands of users with many different requirements

Scalability

Why integration?

Benefits of IntegrationMetrics -- Measuring Integration SuccessBenefits of Integration

Reduces cost of connecting components and adding/changing components.Adds value to business processesEnforces process consistencyData Consistency

Success

Customized for the organizationTie Benefits and Metrics

Customer service measurementsrelated to more up-to-date information

How can Integration increase revenue? improve customer service? give more information about our

business?

High Tension Network

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SAP PM

!Fault Detected

SCADA

SAPNotification

&Work order

Integration with Other Applications

Low TensionNetwork

` Analyze Fault

ArcFM

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Electric Data/

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OMS/

!Fault Reported

GIS-

Network Analysis

ConsumerInformationSystem(CIS)

Enterprise Wide Integrated GIS.

OMS-Responder

GIS-AM/FM

SCADA-DMSSAP

Custom Tools( Energy Audit

Scheduler et al.)

Electric Network Trace

LT NETWORK

Service Line

Service Point

CONSUMER DATA

Load growth planning Using Geo-referenced data

Distribution Management thru integrated GIS

Load Calibration (LC), Load Flow Calculation (LFC) Switching Orders based on minimum Loss path Static spatial connection and dynamic behavior of organizational model & equipment model Switch and switch status telemetry superimposed with cable/conductor type & length Electrical parameters (R, X, B, G ) derived there from to give loss data and options Voltage profiling with load data superimposed on above Power quality and THD Distance relay zones superimposed on map to give nearest fault location Fault Isolation and switching restoration options

Estimated Benefits of GIS As per estimation, GIS will benefit by decreasing both Commercial and Technical losses. Based on assumption for 0.5%, 1.5% and 2.5% increase in MU billed for the first, second and third year respectively by reduction of losses and better O & M.

Pre GIS Implementation Post GIS Implementation

BYPL MU

BRPL MU Total

Approx Tariff

I Yr. (1.0% Incr MU)

Approx. Increas

e in Revenu

e

II Yr. (1.5% Incr MU)

Approx. Increas

e in Revenu

e

III Yr. (2.5% Incr MU)

Approx. Increas

e in Revenu

eMU MU Total Tariff MU) e MU) e MU) eDomestic 1591 2801 4392 2 43.92 87.84 66.54 133.08 112.56 225.12

Commercial 580 740 1320 4 13.2 52.8 20 79.99 33.83 135.32

Industrial 272 406 678 4 6.78 27.12 10.27 41.09 17.38 69.51

Agriculture 1 66 67 1 0.67 0.34 1.02 0.51 1.72 0.86

Bulk 368 1100 1468 1 14.68 7.34 22.24 11.12 37.62 18.81

Total Units Billed 2812 5113 7925 79.25 175.44 120.06 265.78 203.11 449.62

Benefits after GIS Implementation Note: From the table, increase in revenues with prevailing tariff is

175mn, 265Mn and 450Mn respectively for three years.

Estimating Return on Investments

Based on the assumptions of the benefits made, it can be seen that the project has a pay back less than one year of its implementation.

CostIncrease in

RevenueNet Cash

Flow IRR

GIS Implementation 128 0 -128

GIS Implementation (End of I Yr) 40 175 135 6%Maintenance Cost estimated as 25% Of total Maintenance Cost estimated as 25% Of total Implementation (Yr. II) 42 266 224 95%Maintenance Cost estimated as 15% Of total Implementation (Yr. iii) 25 450 424 138%

From the Table it can be seen that the project not only has very less payback period, but has fabulous returns over second and third year with net cash flows as 135mn, 224mn and 424Mn with IRR as 6%, 955 and 138% for first, second and third year respectively

Return on investments

Thank YouThe Project has since been commissioned and the

T&D Losses have been reduced adding significantly to the IRR

Presented at the 3Presented at the 3Presented at the 3Presented at the 3rdrdrdrd Annual Indonesia Power ConferenceAnnual Indonesia Power ConferenceAnnual Indonesia Power ConferenceAnnual Indonesia Power Conference27272727thththth to 30to 30to 30to 30thththth November 2012, Jakarta, IndonesiaNovember 2012, Jakarta, IndonesiaNovember 2012, Jakarta, IndonesiaNovember 2012, Jakarta, Indonesia

Dr Himadri Banerji, MD EcoUrja Dr Himadri Banerji, MD EcoUrja Dr Himadri Banerji, MD EcoUrja Dr Himadri Banerji, MD EcoUrja Ex Chief Executive Reliance Energy Ltd IndiaEx Chief Executive Reliance Energy Ltd IndiaEx Chief Executive Reliance Energy Ltd IndiaEx Chief Executive Reliance Energy Ltd India