1. John Dirkman, P.E.
Sr. Director, Product Management
Optimizing Generation, Distribution,
Renewables, and Demand
Response for a Smarter Grid
Confidential
July, 2015

2. Nexant Overview
• Founded in 2000
• 700+ energy industry and software
specialists, 50 with PhD’s
• Recognized global energy leader
• Over 3200 client assignments completed in
over 100 countries
Frankfurt
London
Cotonou
Abuja
Cairo
Utrecht
ShanghaiBahrain
Bangkok
Tokyo
Beijing
Singapore
Seoul
Nexant Headquarters
Nexant Offices
Project Offices
Representative Offices
Salt Lake City
San Francisco
Los Angeles
Chandler
Madison
White Plains
Boston
Portland
Washington D.C.
Des Moines Chicago
Jacksonville
Nashville / Raleigh
Philadelphia
Boulder
Houston
Sacramento
Atlanta
Milan
Specializing in Demand Management, Grid Management, and Energy Technology Services
Software applications in service in over 150 control centers worldwide

3. iEnergy: Demand Side Management and Customer
Engagement Suite
RevenueManager: Customer Billing and Account
Maintenance
Grid360 Transmission Analytics: Transmission grid
planning and analytics – white labeled foundational
EMS software deployed via world’s largest vendors
Grid360 Distribution Analytics: Advanced visualization,
analytics, and planning applications, enabling DER
and smart meter analysis within distribution networks
iHedge and mHedge: Energy Market FTR simulation,
analysis, and engagement - the de-facto solution at all
ISOs in North America and New Zealand
Energy Software

4. iEnergy Demand Side Management
 DSM Central: portfolio management
 Demand Response: DR coordination
 Home: customer engagement
 Onsite: mobile program/rebate assessment
 Trade Ally: contractor management

5. A comprehensive definition of Distributed Energy Resources (DER):
• DG (solar, wind, CHP, geothermal, hydro)
• Energy Storage (battery, pumped hydro, compressed air)
• Electric Vehicles
• Microgrids
• Demand Response Programs
• VVO/CVR
• Energy Efficiency Programs
(long term)
And DER objectives:
• Improve resiliency
• Peak shaving/shifting
• Defer system upgrades
• Satisfy regulatory requirements
DER Definition and Objectives

6. Ongoing Push to Integrate DER’s into Planning,
Operations, and Markets
SCE Local Capacity Requirements
NY Reforming the
Energy Vision
demonstration projects
National Grid RI
assesses DER
alternatives for all T&D
investments over $1M
Pacific Northwest
Smart Grid
Demonstration Project
PG&E
4 targeted demand
management projects
CPUC Distribution
Resources
Planning
proceedings
SCE energy
storage mandate
Brooklyn Queens
project - $200M
in DER’s

7. Grid Service Key Drivers
Energy Production Produce electricity at lowest cost (incl. fuel and losses)
Generation Capacity Meet extreme peak demand levels
Ramping Flexibility Meet steep ramps of varying time durations
Load Following and
Regulation
Rapid response to balance supply and demand
Operating Reserves Provide ability to withstand system shocks (unplanned
outages and unforecasted load changes)
Distribution Capacity Accommodate local peak loads
Distribution Ancillary
Services
Provide voltage stability, frequency response, VAR
management, reduced losses, etc.
DER Investments are Driven by Specific Operational Drivers

8. DER Valuation Framework
• DER utilize a wide range of technologies, with different operating
characteristics and profiles
• DER value depends on how well the characteristics of each DER
resource align with local demand management needs

9. • Figures show top hours of the load duration curve for 3 different substations
• Values are normalized as the percent of annual peak
• In areas with highly concentrated peaks, reducing loads even for a very limited
number of hours can substantially reduce peak demand
• In areas with less concentrated peaks, coverage is needed for more hours and days
Concentration of Local Load Duration Curves Affects the
Type of Resources Required

10. Peak Risk Allocation Summarized for Each Hour of the Day
• DER can then be deployed to mitigate peaking risk

11. Align DER with Peaking Risk
• Goal is to deploy managed DER in the most optimal locations

12. Align DER with Peaking Risk
Consider DER flexibility:
• Can it be dispatched with different start and end hours?
• Can the magnitude of output be controlled (ramping)?
• How far ahead must it be scheduled?
Consider operating constraints:
• When is it available?
• For how long can the resource be sustained?
• Are there limits on how often or when it can be dispatched?
• What is the reliability of the resource?
Calculate costs and benefits
• Depends on the DER objectives
• Variable resources can negatively impact reliability
• Need to consider electrical impacts on distribution systems

13. Web-based SaaS solution
Integration with GIS, DMS, SCADA,
AMI/MDM, OMS, DRMS
Extend network visibility using smart
meter data
Advanced robust numerical analysis
–DER/DR impact analysis
Network-based optimization
Incremental network expansion
analysis
–adding DER and DR including
microgrids, wind farms, community
storage and solar at both non-utility
(kW) and utility (MW) scale
Grid360 DA: A New Approach to Grid Edge Planning
Study 2014

14. Years into the
future
Hours into the
future
Present
Months into the
future
Near/Short/Medium/Long-term Planning
Operations
1. Next day/week with short-term load and
renewable forecasts based on weather and
DER availability
2. Next month/season/year with annual load
growth & using different DER penetrations
Grid360 Distribution Analytics for Grid Edge

15. Numerical Analysis for Distribution Networks with DER
Study 2014
Short-term load forecast
3-phase topology processing
Topology estimation
Unbalanced state estimation
Unbalanced power flow
Voltage/VAR Optimization and Conservation Voltage Reduction
Capacitor placement optimization
Short-circuit analysis, Contingency analysis
Financial impact analysis, feeder capacity analysis with DERs
What-if near-term planning simulations & prescriptive analysis
Mid- and long-term planning and analysis with varying DERs

16. The Road to DER Optimization
Study 2014
1. Visualization
– Network data from GIS or DMS
– AMI and/or SCADA data
– DER/DR data
̶ The more data available, the more data than can be displayed
2. Analysis
– Weather forecast data
– Historical load data - for accurate load and renewable forecasting
– Demographic data - for long-term forecasting
3. Optimization
– Secure control capability
– DER response acknowledgement

17. Use Case 1: Network development & enhancement
Use Case 2: DER impact analysis
Use Case 3: Microgrid analysis
Use Cases for Near-term Distribution Planning

18. 3-phase topology builder to build connectivity & impedance model
Distribution state estimation via load curves and measurements
Improvement of voltage profile via CVR, VVO, optimal capacitor
placement
Use Case 1: Network development & enhancement

19.  Analysis and Optimization of PV, Wind, EV, Storage, DR
Use Case 2: DER Impact Analysis

20.  Analysis of Microgrid Load/Generation Changes
Use Case 3: Microgrid Analysis

21. • Ongoing push to integrate DER’s into planning,
operations, and markets
• Grid investments are driven by specific operational drivers
• DER placement typically based on peaking risk
• Essential to consider electrical impacts of DER on
distribution systems
• Goal is to optimize DER within your network
• Utility Owned
• Customer Owned
• Third-Party Aggregated
Conclusion

22. John Dirkman, P.E.
Sr. Director, Product Management
Optimizing Generation, Distribution,
Renewables, and Demand
Response for a Smarter Grid
Confidential
July, 2015
Thank You