Partnership to Advance Clean Energy-Deployment

1. 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 IT
3. Smart Grid Case Studies
• Duke Energy Ohio Case Study
• TPDDL Smart Grid Journey
• Global AMI Deployment Overview
Presentation Structure
2

3. Developing the Utility Roadmap - Smart Grid Maturity Model
3

4. 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 Model
1 2
2
Enabling
Investing based on clear strategy, implementing first
projects to enable smart grid
1
Initiating
Taking the first steps, exploring options, conducting
experiments, developing smart grid vision
0
Default
Default level (status quo)
SGMM Product Suite
Breaking new ground; industry-leading innovation
5
Pioneering
Optimizing smart grid to benefit entire organization
4
Optimizing
Integrating smart grid deployments across the
organization
3
Integrating
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

5. Strategy, Mgmt & Regulatory
SMR
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
WAM
Asset monitoring, tracking &
maintenance, mobile workforce
Technology
TECH
IT architecture, standards,
infrastructure, integration, tools
Customer
CUST
Pricing, customer participation &
experience, advanced services
Value Chain Integration
VCI
Demand & supply management,
leveraging market opportunities
Societal & EnvironmentalSE
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
6

7. • 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
DefiningIT-OT
forUtilities
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
DriversforIT-OT
Convergence
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 faster
to 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
8

9. 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 Grid
9
IT
OT
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. 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 Analysis
Unbalanced load flow
calculations
Optimum Switching plan
determined
IT
OT
Key
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
11

12. 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

13. 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
KeyElements
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

14. 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
Traditional Operations Smart Grid Operations
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%
KeyElements
Source: Duke Energy Ohio Smart Grid Audit and Assessment, 2011

15. 383156
54
50
17 10 8
8 7
73
System Voltage
Reduction
Off-cycle / off-
season meter
reads
Regular meter
reads
Meter operations
– Avoided capital
costs
Vehicle
Management
Power Theft Meter accuracy
improvement
Remote Meter
Diagnostic
Others Total
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
Deferment
Incresed
Revenue
Total 20 Year
NPV Savings
USD 383 million
Source: Duke Energy Ohio Smart Grid Audit and Assessment, 2011
Source: Duke Energy Ohio Smart Grid Audit and Assessment, 2011
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
Source: Duke Energy Ohio Smart Grid Audit and Assessment, 2011

16. TPDDL Smart Grid Case Study
16

17. 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

18. 18
18
Regulator
(DERC)
• Operational Excellence
• Consumer Satisfaction
• Affordable Tariffs
• Sectoral Subsidy Elimination
• Ethical, Safe and Environmental
Friendly Practices
Consumers
• 24X7 Supply
• Affordable Tariffs
• Ethical, Safe and Environmental
Friendly Practices
• Error Free and Timely Services
• Proactive Communication
Community
Business
Associates
• Support to local communities
• Ethical, Safe and Environmental
Friendly Practices
• 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

19.  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. 20
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DA
EMS
DMS
OMS
SCADA
CRM
Billing
SAP
GIS
Call Centre
AMR
Smart Grid Initiatives – ICT Architecture (2/7)

21. 21
RG-3 SUB Ring 1
STM 4Σ2
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RG-5
PUSA ROAD
RANIBAGH GRID
Saraswati garden
NARAYANA PH-I
CORE RING
STM 16
FIBER RING - TPDDL
RANIBAGH CCC
NEW ROHTAK ROAD
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WZP-II
INDER VIHAR
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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 BAGH
SHAKTI NAGAR DO
GTK Grid
SHALIMAR BAGH
PITAM PURA DO
PP III
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MGP-II
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HUDSON LINES
WZP-I
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Fiber Main Ring
Σ Grids
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Σ2 Enterprise and Grid
VSNL VSNL Gateway
for internet
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SUB Ring 3
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SUB Ring 2
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SUB Ring 4
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SUB Ring 5
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Smart Grid Initiatives – Communication Network (3/7)
Entire TPDDL network over Six Rings covering all grids to serve
system operations and other applications

22. 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. 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. 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. 25
Smart Grid Initiatives – Business Process Digitisation (7/7)
Integrated GIS-SAP-SCADA-DMS-OMS
GIS
Survey
Digitization
Redlining
SAP-PMDesign
Manager
Asset
Management
SCADA
OperationsManagement
DMS
OMS
Vehicle Tracking
Field Automation
Consumer Indexing
ConsumerManagement
SAP-ISU
All Customer interactions and processes automated for
providing Best-in-Class services

26. 26
Turnaround Snapshot
Parameter Unit Jul 02 Mar 15
%
change
Operational 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.
Cumulativebenefits
Technology Complexity
New Technologies > New Applications > Increased Benefits:
27

28. 28
Current
scope
Shaping
Demand
Additional
services
Cumulativebenefits
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)
29

30. Way Ahead… (4/6)
30
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)
31
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)
32
Expected cost benefit scenario…
Benefits
Cost

33. 4Q 20132Q 2009 2Q 20111Q 2007
• Grid
Substation
Automation
System;
• SCADA
System;
• Communica
tion 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 1
Score # 1.69
SGMM - Level 2
Score # 2.5
SGMM - Level 3
Score # 3.6
SGMM - Level 4
Score # 4.5
The journey so far and the future steps…

34. Conclusions
34
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

35. South Korea (Jeju)
Total investment: USD 91 MN
AMI: 2190 households, 45 large
consumers
Benefit: USD 75 MN (Private)
Sweden
Total investment: Euro 1.5 bn / 6 yr
Smart Meter: 5.2 million
Benefit: service quality improvement,
customer satisfaction and improved
safety on the network.
Ireland Pilot
AMI: 6000 Meter
Energy Reduction: 2.5%
Peak Reduction: 8.8%
USA (California)
Total investment: USD 750 MN
Smart Meter: 1.7 MN
Benefit: Increased operational
efficiency and reliability
Global AMI Deployment Results Summary
Canada(Ontario)
Smart Meter: 4.5 Million
Project Cost:$1 billion CDN for
AMI installation
Project 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 Million
Project Cost: Euro 2.1
Billion/5 yr
Benefit: 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
Traditional Operations Smart Grid Operations
KeyElements
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
Source: Duke Energy Ohio Smart Grid Audit and Assessment, 2011 36

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.
37

38. Thank You