smart grid deployment experience and utility case studies

Smart Grid Deployment Experience and Utility Case Studies

Partnership to Advance Clean Energy-Deployment (PACE-D)

Technical Assistance Program

2

1. Developing Utility Smart Grid Roadmap – Smart Grid Maturity Model• SGMM Overview• SGMM Domains and Levels• SGMM Tata Power Case Study

2. Smart Grid Integration of OT and IT3. Smart Grid Case Studies

• Duke Energy Ohio Case Study• TPDDL Smart Grid Journey• Global AMI Deployment Overview

Presentation Structure

3

Developing the Utility Roadmap - Smart Grid Maturity Model

SGMM is a management tool that provides a common framework for defining key elements of smart grid transformation and helps utilities develop a programmatic approach and track their progress.

Smart Grid Maturity Model1 2

2Enabling

Investing based on clear strategy, implementing first projects to enable smart grid

1Initiating

Taking the first steps, exploring options, conducting experiments, developing smart grid vision

0Default

Default level (status quo)

SGMM Product Suite

Breaking new ground; industry-leading innovation5

Pioneering

Optimizing smart grid to benefit entire organization 4

Optimizing

Integrating smart grid deployments across the organization

3Integrating

SGMM Levels

Global Intelligent Utility Network Coalition (GIUNC) developed SGMM and it is currently under the stewardship of the Software Engineering Institute at Carnegie Mellon University

Source: SEI http://www.sei.cmu.edu/ 4

SGMM would allow utilities to assess their current smart grid position and reach consensus on the direction and pace of their smart grid journey. SGMM provides a guiding framework to utilities in

smart grid planning and implementation efforts

Strategy, Mgmt & Regulatory

SM

R

Vision, planning, governance, stakeholder collaboration

Organization and Structure

OS Culture, structure, training,

communications, knowledge mgmt

Grid Operations

GO Reliability, efficiency, security,

safety, observability, control

Work & Asset Management

WA

M

Asset monitoring, tracking & maintenance, mobile workforce

Technology

TE

CH

IT architecture, standards, infrastructure, integration, tools

Customer

CU

ST

Pricing, customer participation & experience, advanced services

Value Chain Integration

VC

I

Demand & supply management, leveraging market opportunities

Societal & Environmental S

E Responsibility, sustainability, critical infrastructure, efficiency

Smart Grid Maturity Model - Domains

Source: SEI http://www.sei.cmu.edu/

1 2

5

Domains are logical groupings of smart-grid-related capabilities and characteristics for which the SGMM defines a maturity progression. Each level of maturity within a domain is fully described by a set of expected characteristics and

a set of informative characteristics.

6

Smart Grid Integration of IT and OT

• Enterprise Resource Planning

• Enterprise Asset Management

• Mobile Workforce

Management

• Customer Information

Systems

• EMS

• SCADA

• GIS

• DMS

• Asset Management

• Substation Automation

Execution, monitoring and control of the electric system

Commercial decision making, planning, business processes management and resource allocation

Historically, OT and IT for distribution operations have been developed, maintained, and used in silos in a utility organization

IT OT

Def

inin

g IT

-OT

for U

tiliti

es

The need to integrate new types of assets/agents to the electric network and make them “operationally ready”

Siloed Smart Grid applications won’t support efficient operation of the distribution system, the full value of the smart grid lies in integration of IT and OT

Convergence of IT and OT – Moving away from Process Silos

Driv

ers

for I

T-O

T C

onve

rgen

ce Different streams of information are stored in silos, resulting in lack of a synchronized view of asset information

Large quantity of information with Smart Grid - The IT/OT system must quickly sort through and identify the operationally relevant data points

21 3

7

8

Information Technology Big data analytics to generate critical insights and automated actions

Insights drive just-in-time work to optimize enterprise

Large volumes of data for visibility into condition and status

Operational Technology Real time monitoring and control of critical field assets

Benefits of the IT/OT Converged Enterprise

Respond fasterto real time conditions - lower operating and capital costs

Accurate data at all times- Improved alignment between operations and business goals

Transparent, on-demand reporting enables better decision making and alignment to achieve energy savings goals

Convergence of IT and OT – Moving away from Process Silos

IT-OT integration helps to streamline the management of the overall system and offers improved workflow and simplified task execution thus enabling high-speed and high-quality decisions.

Source: Ventix Presentation, IT/OT Convergence

IT/OT

Convergence

Convergence of IT and OT – Use Case

Enterprise Asset Management

Traditional Scenario Convergence of IT-OT

Stored Asset Data

Maintenance Activity

Enterprise Asset Management

Real time asset data - SCADA

Asset Health Model – Predictive Analytics, trending &

forecasting of equipment performance

Equipment Alarms/ Notification/ Root Cause/

Potential FaultBased mostly on manufacturer specifications of standard

maintenance and required work Work Management

System (WMS)Work Order –

Replace/Repair

Asset Health Monitoring –Automatic monitoring of tasks on all assets in a substation in near real time using and enabling preventive maintenance

Source: ABB: Convergence of Information and Operation Technologies (IT & OT) to Build a Successful Smart Grid9

ITOT

Key

EAM (IT) store and manage asset data

EAM manages maintenance task for asset.

In traditional scenario - no consideration of actual working or loading conditions,

connectivity, operational parameters, etc.

EAM gets near real time data from SCADA (OT)

Advanced applications implemented to perform predictive maintenance, trending and forecasting of equipment performance.

Analysis used to determine impact of asset performance on overall system (technical & economic) and also remedial actions given via WMS

(IT) to field staff improve the asset’s performance.

1 2

10

Self Healing Networks – Automatic network monitoring enabling isolation of fault and minimizing its impact on end customers

FLISR Application(fault location, isolation, and service

restoration)

Fault Current Indicator Status

Breaker/Switch Status

SCADA

Switching control action sent to Field

Devices

GIS – Network Model

Data AnalysisUnbalanced load flow

calculations

Optimum Switching plan determined

IT

OTKey

Source: IT/OT convergence, ABB Review

FLISR application gets real time inputs such as fault current, faulted circuit

indicator status, breaker/ switch status and network model from GIS

Using inputs application determines optimal switching plan to isolate the fault and restore service to as many customers as possible

Unbalanced load flow calculations using network model performed to determine any voltage violations for the possible switching plans

Once the optimal switching plan has been chosen, the appropriate control actions can be transmitted to the field devices through SCADA (OT) communications

Convergence of IT and OT – Use Case

Convergence of IT and OT in Smart Grid foster new applications like predictive asset maintenance, smart self- healing and many others which in turn increase efficiency and reduce costs in the industry

1 2

11

Smart Grid Case Studies

Duke Energy – Ohio Smart Grid A brief overview of the project background and scope

Project Highlight

Background Project objectives Project desired outcomes

For Consumers

• Improved accuracy of billing.

• Energy use information available in near real time

For Utilities

• Decreased billing calls due to reduced bill estimates.

• Reduced outage time.• Reduction of system

losses due to improved modeling.

• Improved data for investment planning

2

1• To implement distribution automation to help prevent and shorten outages

• To enable AMI and reduce the need for estimated bills

• To enable remote service connections and disconnections for faster customer service

• To capture and post daily energy usage data online so customers can make wiser energy decisions

• To incorporate more renewable, distributed generation into the grid

• Total investment of USD 100 mn allotted for Ohio grid modernization project in AMI and DA application

• ~140,000 new smart grid meters have been installed since 2008 in Ohio impacting 700,000 consumers

Sources• eia.gov/analysis/studies/electricity/pdf/sg_case_studies.pdf• naruc.org/international/Documents/Duke%20Smart%20Grid%20%20-%20Don%20Schneider%20Duke%20Energy.pdf

Duke Energy – Ohio Smart Grid Comparison of traditional grid operations and smart grid operations post deployment of Advanced Metering Infrastructure (AMI)

Meter Readers walk from house to house to capture electric and gas meter data with handheld equipment

No capability to understand if a customer issue was on the utility or customer-side of the meter

Traditional meters did not offer capabilities to detect tampering (mis-wired or bypassed meters)

Traditional meters need to be replaced over time resulting in regular capital cost

Smart meters send interval data directly to the utility and hence eliminating most of annual meter reading labor costs

Real-time remote diagnostic helped determine if meter is operating normally. If meter was receiving voltage, no field personnel are sent to investigate.

Smart meters generated tampering alarms and monitored meter data to identify theft. This resulted in increased revenue by 0.5% of overall revenue

Smart meters do not require the use of equipment related to manual meter reads such as handheld devices resulting in reduced costs

Traditional Operations Smart Grid Operations

Key

Ele

men

ts

Traditional meters and associated handheld equipment decrease in accuracy over time, requiring routine testing

Due to their digital nature, smart meters do not require regular testing to ensure accuracy hence resulting in reducing testing and refurbishment costs

Meter Reads

Meter Diagnostics

Power Theft

Capital Costs

Operational Costs

Source: Duke Energy Ohio Smart Grid Audit and Assessment, 2011

Duke Energy – Ohio Smart Grid Comparison of baseline grid operations and smart grid operations post deployment of Advanced Metering Infrastructure (AMI)

Outage Detection

Billing

No capability to detect the outage locations and extent of customer outage

Issuance of bills were delayed by as much as two days

With capability to analyze and detect customer outage using real time meter data it avoided “already restored” tickets and reduced assessor labor costs

Bills to be made available on the first day of the billing cycle leading to acceleration of cash collections and interest expense reduction


Apart from financial benefits, implementation of smart grid technologies like AMI provided social benefits through reduction in fuel consumption, CO2 emissions, increasing energy efficiency, and enabling a cleaner environment

Vehicle Management

Traditionally meter readers used meter reading vehicles to manually read meters on door-to-door routes

Metering data is communicated via wireless network to utility which reduces need for manual meter reads, resulting in the reduction of vehicles used for meter reading

Accuracy Improvement

Traditional meters on average, register a slightly lower energy use reading than actual consumption.

The electric smart meters do not have moving parts and can correct temperature-related error, making them inherently more accurate and resulting in revenue gains of 0.3-0.35%

Key

Ele

men

ts


System Voltage Reduction

Off-cycle / off-season meter

reads

Regular meter reads

Meter opera-tions – Avoided

capital costs

Vehicle Management

Power Theft Meter accuracy improvement

Remote Meter Diagnostic

Others Total

156

5450

17 10 8 8 7

73

383

383

Estimated 20 Year Net Present Value of Operational Benefits (in USD million)

Duke Energy – Ohio Smart Grid Estimation of NPV of operational benefits through deployment of Advanced Metering Infrastructure (AMI) and Distribution Automation (DA) system

Break-up of benefits based on savings category

35%

34%

17%

14%

O&M Cost Savings

Fuel Cost Savings

Capital De-ferment

Incresed Revenue

Total 20 Year NPV Savings USD 383 million



A number of operational benefits are unlocked as a result of AMI implementation which generate positive NPV for the project - Thus allaying fears of utilities, if any of high initial costs of smart grid implementation

Break-up of benefits based on functionality

$212 Million, 55%

$171 Millon, 45%

DA

AMI

Total 20 Year NPV Savings


16

TPDDL Smart Grid Case Study

17

Regular Power Cuts, Black Outs & Brown Outs

20,000 applications pending for New Connections - even Attribute change (Name, Load etc.) requests were pending for years

1,00,000 Billing Complaints - 15% of the customer base complaints pending in files

Erroneous Customer Database – 50% of customers had some form of an error

Absence of Customer Relationship approaches – virtually no emphasis on customer comfort

No Digitization- Limited Computerization / Absence of CRM for tracking and monitoring of Customer Complaints

Nothing moved unless long hours were spent standing in queues

Initial Challenges – 2002

1818

Regulator(DERC)

• Operational Excellence

• Consumer Satisfaction

• Affordable Tariffs

• Sectoral Subsidy Elimination

• Ethical, Safe and Environmental Friendly Practices

Consumers

• 24X7 Supply

• Affordable Tariffs


• Error Free and Timely Services

• Proactive Communication

Community Business Associates

• Support to local communities


• Ethical and Safe Practices• Timely Payment• Proactive Communication• Long Term Association

Requirement of Enhanced Consumer Satisfaction while following Ethical, Safe and Environmental friendly operations

Stakeholder Expectations

Communication Infrastructure (OF, Radio) SCADA/EMS/DMS (Siemens Sinaut Spectrum 4.5) Grid Station Automation Enterprise Resource Planning (SAP) Distribution Automation GIS (GE Small World 4.0) Network Planning Tool (CymeDist 3.5) Automatic Meter Reading (Homegrown) Outage Management System (GE PowerOn 2.1) Enterprise Application Integration

19

TPDDL Smart Grid Story – Milestones (1/7)

20

C O M MN.

N E T W O R K

TRANSCO GRID STN

TPDDL GRID STN

DIST SUB STN

CUSTOMERS

D I SASTER RECOVERY

WEB

DA

EMS

DMS

OMS

SCADA

CRM

Billing

SAP

GIS

Call Centre

AMR

Smart Grid Initiatives – ICT Architecture (2/7)

21

RG-3 SUB Ring 1STM 4 Σ2

2

2 2

2

2

Σ

Σ

RG-5

PUSA ROAD

RANIBAGH GRID

Saraswati garden

NARAYANA PH-I

CORE RINGSTM 16

FIBER RING - TPDDL

RANIBAGH CCC

NEW ROHTAK ROAD

Σ Σ

Σ

Σ Σ

Σ Σ Σ

Σ

Σ

Σ Σ Σ

Σ Σ

Σ

Σ

Σ

Σ

Σ Σ

Σ Σ

2

Σ

Σ2

Σ Σ

Σ

Σ

Σ

WZP-II

INDER VIHAR

AZAD PUR

WAZIRABAD

CIVIL LINES

SARASWATI GARDEN

PANDU NAGAR

VSNL

S PARK

KESHAV PURAM DO

ROHTAK ROAD

RAM PURA

TRI NAGAR

ASHOK VIHAR H BLOCK CCC

GULABI BAGH SHEHJADA BAGHSHAKTI NAGAR DO

GTK Grid

SHALIMAR BAGH

PITAM PURA DO

PP III

PP II

MGP-II

INDER PURIHUDSON LINES

WZP-I

ASHOK VIHAR GRID

MGP-1

Σ2

RG-IVRG-22

RG-23

BAWANA GRID-6

POOTH KHURD GRID

BAWANA WATER WORKS and Bawana DO

DSIDC A7, NARELA

DSIDC1 NARELA

RG-1

PP-1

HDR’PUR

SGTN

JAHANGIR PURI

AIR KHAMPUR

BADLI

RG-6

RG-II

Fiber Sub RingFiber Main Ring

Σ Grids2 Enterprise DATA Σ2 Enterprise and Grid

VSNL VSNL Gateway for internet

RAMA ROAD Σ

Σ2

Σ2

Σ2

Σ2

Σ2

2NARELA DO

DSIDC2 NARELA

SUB Ring 3STM 4

SUB Ring 2STM 4

SUB Ring 4 STM 4

SUB Ring 5STM 4

Smart Grid Initiatives – Communication Network (3/7)

Entire TPDDL network over Six Rings covering all grids to serve system operations and other applications

Fully Scalable System

Complete relay data

monitoring

Metering data for Energy

Audit

DC system monitoring

ACDB system Monitoring

OLTC remote operation & monitoring

SCADA Compatible

Stations

22

Sixty seven 66/11 KV & 33/11 KV Unmanned Automated Grid Substations catering to TPDDL Peak Demand of 1700 MW

Smart Grid Initiatives – Automation (4/7)

23

Smart Grid Initiatives – Unmanned Grid Stations (5/7)

Sixty seven 66/11 KV & 33/11 KV Unmanned Automated Grid Substations catering to TPDDL Peak Demand of 1700 MW

24

Distribution Automation through SCADA: Centralised Load Dispatch Centre.

Remote Monitoring and Control of Sub-Transmission and Distribution Network.

Real time monitoring of Generation and Transmission through SLDC and NRLDC interface.

Automated Fault Identification & Isolation, Service restoration, Load forecasting & Load Management.

Smart Grid Initiatives – SCADA (6/7)

25

Smart Grid Initiatives – Business Process Digitisation (7/7)

Integrated GIS-SAP-SCADA-DMS-OMS

GIS

Survey

Digitization

Redlining

SAP-PMDesign Manager

Asset Management

SCADAOperations M

anagement

DMS

OMS

Vehicle Tracking

Field Automation

Consumer Indexing

Consum

er Managem

ent

SAP-ISU

All Customer interactions and processes automated for providing Best-in-Class services

26

Turnaround Snapshot

Parameter Unit Jul 02 Mar 15%

changeOperational Performance

AT&C Losses % 53.1 9.87 81%System Reliability – ASAI -Availability Index % 70 99.96 43%Transformer Failure Rate % 11 0.77 95%Peak Load MW 930 1704 83%Length of Network Ckt. Km 6750 13006 93%Street Light Functionality % 40 99.57 149%

Consumer Related Performance New Connection Energization Time Days 51.8 4.6 91%Meter Replacement Time Days 25 3 88%Provisional Billing % 15 2 87%Defective Bills % 6 0.12 98%Bill Complaint Resolution Days 45 6 87%Mean Time to Repair Faults Hours 11 1.34 88%Call Center Performance - Service Level % - 91 Payment Collection Avenues Nos. 20 6725 33525%Consumer Satisfaction Index % - 84

27

Way Ahead… (1/6)

Current scope

Shaping Demand

Additional services

• Meter reading;• Basic outage management;• Theft detection;• Prepayment;• Billing;• Limited automation.

• Real time pricing;• Micro-grids;• Fault prediction;• Smart grid switching;• Home energy

automation;• Distributed generation

from fuel cells, solar, and online backup generation;

• OUTAGE MANAGEMENT.

• Time of Use & Peak pricing;• In-home displays;• Integrated disconnect;• Home energy management;• Confirmed load control;• Net metering/ solar;• Home energy audit;• Advanced fault monitoring;• Use of Spatial technologies.

Cum

ulati

ve b

enefi

ts

Technology Complexity

New Technologies > New Applications > Increased Benefits:

28

Current scope

Shaping Demand

Additional services

Cum

ulati

ve b

enefi

ts

Integrate existing services to new platform;Regulatory approvals for Capex.

Transform existing services using advanced communications;Regulatory approvals for Capex;Create new markets.

Utility challenges in implementing new technologies…

Technology Complexity

Way Ahead… (2/6)

29

How do we get there…..

Modern Grid Milestones:

Advanced Metering Infrastructure (AMI)

Advanced Distribution Operations (ADO)

Advanced Transmission Operations (ATO)

Advanced Asset Management (AAM)

Way Ahead… (3/6)

30

Way Ahead… (4/6)

Characteristic AMI ADO ATO AAM

Enables Active Consumer Participation √ √

Accommodates all Generation & Storage Options

√ √ √

Enables new products, services and markets

√ √ √

Provides PQ for digital economy √ √ √ √

Optimizes Assets & Operates efficiently √ √ √ √

Anticipates and responds to System Disturbance

√ √ √ √

Resiliency to Attack & Natural Disaster √ √ √

Keeping the “End in Mind”…

31

Way Ahead… (5/6)

AMI establishes communications to the loads, assists revenue management and empowers the consumer.

AMI and DR

Distribution (ADO)

Transmission (ATO)

Asset Management (AAM)

Expected sequence of milestones….

AAM optimises and improves asset management.

ADO enables self healing, improves sales and optimises Opex.

ATO optimises Capex, addresses congestion in transmission lines & reduces Opex.

32

Way Ahead… (6/6)

ATO

ADO

AMI

Expected cost benefit scenario…

Bene

fits

Cost

4Q 20132Q 2009 2Q 20111Q 2007

• Grid Substation Automation System;

• SCADA System;

• Communication Infra-structure.

• Broad band over Power Line (BPL);

• DA;• DMS / OMS;• Enterprise Application

Integration (EAI);• Billing Systems (SAP);• Distributed Gen (DG);• Network Asset Mgmt.

• AMI;• DSM;• Mobile

Workforce Management (MWM);

• Smart Grid pilot roll out – Stage 1.

• Generation Integration;

• Transmission Integration;

• Smart Grid roll out – Stage 2.

Phase 1 Phase 2 Future PhasePhase 3

4Q 2016

33

TPDDL – Proposed Smart Grid Deployment

SGMM - Level 1Score # 1.69




The journey so far and the future steps…

34

Conclusions

1. SGMM provides a good starting point for utilities to integrate smart grid into its business processes

2. Convergence of IT and OT provides improved decision making abilities enabling efficiency in operation and enhanced customer experience

3. Deployment experience across countries indicates significant benefits at different levels in the distribution segment

South Korea (Jeju)

Total investment: USD 91 MN AMI: 2190 households, 45 large consumersBenefit: USD 75 MN (Private)

Sweden

Total investment: Euro 1.5 bn / 6 yr Smart Meter: 5.2 millionBenefit: service quality improvement, customer satisfaction and improved safety on the network.

Ireland Pilot

AMI: 6000 MeterEnergy Reduction: 2.5%Peak Reduction: 8.8%

USA (California)

Total investment: USD 750 MNSmart Meter: 1.7 MNBenefit: Increased operational efficiency and reliability

Global AMI Deployment Results Summary

Canada(Ontario)

Smart Meter: 4.5 MillionProject Cost:$1 billion CDN for AMI installationProject Benefit: $1.6 billion CDN

Global large scale AMI deployment is underway – Countries are realizing ROI through improved service quality, increased operational efficiency and reliability while improving customer satisfaction

Source: AMI Case Book Version 2.0, ISGAN 35

Italy (Telegestore Project)

Smart Meter: 32 MillionProject Cost: Euro 2.1 Billion/5 yrBenefit: Euro 500 Million (yearly saving)1.5TWh Energy recovered

36

Duke Energy – Ohio Smart Grid Comparison of traditional grid operations and smart grid operations post deployment of Distribution Automation (DA) system

Load Tap Changers and capacitors in traditional grids not automated

Difficult to detect faulty capacitors, capacitors might be offline for a year before being detected

No real time data or automation to fine tune system for conditions like peak load

Algorithms in the DMS continually make control decisions based on real-time voltage readings (eg. Reduce the voltage drops along the line) providing energy savings and thus reduction in fuel cost

Equipment monitoring, faulty capacitors can be identified and repaired or replaced immediately. This improved capacitor effectiveness and enabled the avoidance/deferral of capital expenditures.

DMS is engaged to activate fine tuning. Fine tuning enables more efficient distribution of power and resulted in less capital investment for handling peak load and improved overall operating expenses


Key

Ele

men

ts

No capability to analyze real time load data or perform automatic on-demand load switching

Improved grid data access and analysis capabilities is used for optimized load switching. Resulting in delayed capacity upgrades by one-two years thus deferring capital expenditures.

System Voltage Reduction

VAR Management

System Fine-tuning

Asset Management


37

References

[1] "Smart Grid Maturity Model Update - Volume 3," Software Engineering Institute, Carnegie Mellon, 2011.

[2] Jeff Meyers, P.E , "How the Convergence of IT and OT Enables Smart Grid Development," Schneider Electric, 2013.

[3] Sharelynn Moore, Itron;Stephen Butler, Teradata, "Active Smart Grid Analytics™ Maximizing Your Smart Grid Investments," Itron White Paper, 2009.

[4] Jennifer Hiscock, Natural Resource Canada (Canada); Doon-Joo Kang, Korea Electrotechnology Research Institute, "AMI Case Book 2.0," 2014.

[5] ABB, "IT/OT Convergence : How their coming together increases distribution system performance," 2012.

[6] metavu, "Duke Energy Ohio Smart Grid Audit and Assessment," 2011.

[7] ABB, "Convergence of Information and Operation Technologies (IT & OT) to Build a Successful Smart Grid".

[8] TCS, "A process approach to Smart Grid deployment," 2013.

Thank You