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DIMACS Workshop on Algorithmic Decision Theory for the Smart Grid Challenges of Generation from Renewable Energy on Transmission and Distribution Operations. James T. Reilly Consultant October 25, 2010. Evolution of Smart Grid. IntelliGrid Architecture

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james t reilly consultant october 25 2010
DIMACS Workshop on Algorithmic Decision Theory for the Smart GridChallenges of Generation from Renewable Energy on Transmission and Distribution Operations

James T. Reilly

Consultant

October 25, 2010

evolution of smart grid
Evolution of Smart Grid
  • IntelliGrid Architecture

Integration of the power and energy delivery system and the information system (communication, networks, and intelligence equipment) that controls it.

  • Demand Response / Smart Meters

Customers reduction or shift in use during peak periods in response to price signals or other types of incentives.

Smart meters with two way communications

  • Integration of Renewable Energy

Renewable Portfolio Standards

intelligrid 2000
IntelliGrid(2000)

Electrical

Infrastructure

Intelligence Infrastructure

Integrated Energy and Communications System Architecture – 2001

Rev 0 Architecture – 2004

intelligrid vision power system of the future
IntelliGrid VisionPower System of the Future
  • A power system made up of numerous automated transmission and distribution systems, all operating in a coordinated, efficient and reliable manner.
  • A power system that handles emergency conditions with ‘self-healing’ actions and is responsive to energy-market and utility business-enterprise needs.
  • A power system that serves millions of customers and has an intelligent communications infrastructure enabling the timely, secure and adaptable information flow needed to provide reliable and economic power to the evolving digital economy.
smart grid domains 2010
Smart Grid Domains(2010)

Source: NIST Smart Grid Framework 1.0, September 2009

direction of smart grid
Direction of Smart Grid

To date, the smart grid in the United States has been dominated by smart metering and as an enabler for demand management.

Now, the direction is turning towards being an enabler for the integration of renewables into distribution networks and the bulk power system.

us electric power industry net generation 2008
US Electric Power Industry Net Generation (2008)

Sources:U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report.”

renewable portfolio standards
Renewable Portfolio Standards

ME: 30% x 2000

New RE: 10% x 2017

VT: (1) RE meets any increase in retail sales x 2012; (2) 20% RE & CHP x 2017

WA: 15% x 2020*

MN: 25% x 2025

(Xcel: 30% x 2020)

MT: 15% x 2015

NH: 23.8% x 2025

MI: 10% + 1,100 MW x 2015*

MA: 22.1% x 2020 New RE: 15% x 2020(+1% annually thereafter)

ND: 10% x 2015

OR: 25% x 2025(large utilities)*

5% - 10% x 2025 (smaller utilities)

WI: Varies by utility; 10% x 2015 statewide

SD: 10% x 2015

RI: 16% x 2020

NY: 29% x 2015

CT: 23% x 2020

NV: 25% x 2025*

IA: 105 MW

OH: 25% x 2025†

PA: ~18% x 2021†

CO: 30% by 2020(IOUs)

10% by 2020 (co-ops & large munis)*

WV: 25% x 2025*†

IL: 25% x 2025

NJ: 22.5% x 2021

CA: 33% x 2020

KS: 20% x 2020

UT: 20% by 2025*

VA: 15% x 2025*

MD: 20% x 2022

MO: 15% x 2021

DE: 20% x 2020*

AZ: 15% x 2025

DC

NC: 12.5% x 2021(IOUs)

10% x 2018 (co-ops & munis)

DC: 20% x 2020

NM: 20% x 2020(IOUs)

10% x 2020 (co-ops)

TX: 5,880 MW x 2015

HI: 40% x 2030

29 states + DC have an RPS

(6 states have goals)

State renewable portfolio standard

Minimum solar or customer-sited requirement

*

State renewable portfolio goal

Extra credit for solar or customer-sited renewables

Solar water heating eligible

Includes non-renewable alternative resources

Source: Interstate Renewable Energy Council (June 2010)

8

variable generation impact on bulk power system dispatch no renewables
Variable Generation Impact on Bulk Power SystemDispatch – No Renewables

Study Area Dispatch – Week of April 10th – No Renewables

variable generation impact on bulk power system dispatch 10 renewables
Variable Generation Impact on Bulk Power System Dispatch – 10% Renewables

Study Area Dispatch – Week of April 10th – 10% R

variable generation impact on bulk power system dispatch 20 renewables
Variable Generation Impact on Bulk Power SystemDispatch – 20% Renewables

Study Area Dispatch – Week of April 10th – 20% R

variable generation impact on bulk power system dispatch 30 renewables
Variable Generation Impact on Bulk Power System Dispatch – 30% Renewables

Study Area Dispatch – Week of April 10th – 30% R

tehachapi wind generation april 2005
Tehachapi Wind GenerationApril 2005

Could you predict the energy production for this wind park,

either day-ahead or 5 hours in advance?

700

Each Day is a different color.

600

  • Day 29

500

  • Day 9

400

  • Day 5
  • Day 26

Megawatts

300

  • Average

200

100

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

-100

Hour

Source: CAISO

variable generation impact on bulk power system
Variable Generation Impact on Bulk Power System
  • Output can be counter to load ramps or faster than system ramp
  • Unpredictable patterns – wind variability and large imbalances, esp. during disturbances and restoration efforts
  • Low capacity factor – can be zero at times of peak
  • Voltage issues – low voltage ride through (LVRT)
  • Reactive & real power control issues
  • Frequency & Inertial Response issues
  • Oversupply conditions
operational issues
Operational Issues

The operational issues created by variable generation result from the uncertainty created by the variable output and the characteristics of the generators themselves, such as the inertial response and dynamic response during fault conditions. The impacts are also affected by factors specific to the particular variable generation site, its interconnection to the power system, the characteristics of the conventional generators within the system being operated, and the rules and tools used by the particular system operator.

The operational issues created by variable generation can be considered in terms of various time frames: seconds to minutes, minutes to hours, hours to day, day to week, and week to year and beyond.

Source:

Integration of Variable Generation into the Bulk Power System, NERC. July 2008.

operational issues time scale
Operational Issues – Time Scale

Source: John Adams, GE

operational practices to accommodate variable generation
Operational Practices to Accommodate Variable Generation
  • Substantially increase balancing area cooperation or consolidation, either real or virtual
  • Increase the use of sub-hourly scheduling for generation and interchanges
  • Increase utilization of existing transmission
  • Enable coordinated commitment and economic dispatch of generation over wider regions
  • Incorporate state of the art wind and solar forecasts in unit commitment and grid operations
  • Increase the flexibility of dispatchable generation where appropriate (e.g., reduce minimum generation levels, increase ramp rates, reduce start/stop costs or minimum down time)
  • Commit additional operating reserves as appropriate
  • Build transmission as appropriate to accommodate renewable energy expansion
  • Target new or existing demand response or load participation programs to accommodate increased variability and uncertainty
  • Require wind plants to provide down reserves

Source: Western Wind and solar integration study, May 2010 Prepared for NREL by GE Energy. May 2010.

The technical analysis performed in this study shows that it is operationally feasible for WestConnect to accommodate 30% wind and 5% solar energy penetration, assuming these changes to current practice are made over time.

der interconnection
DER Interconnection

Distributed Energy Technologies

Interconnection Technologies

Electric Power Systems

  • Functions
  • Power Conversion
  • Power Conditioning
  • Power Quality
  • Protection
  • DER and Load Control
  • Ancillary Services
  • Communications
  • Metering

Utility System

Fuel Cell

PV

Inverter

Micro grids

Micro turbine

Wind

Loads

Local Loads

PHEV; V2G

Energy Storage

Load Simulators

Switchgear, Relays, & Controls

Generator

technologies to accommodate renewable generator behaviors
Technologies to Accommodate Renewable Generator Behaviors
  • Energy Storage & Intelligent Agent (temporal power flow control)
  • Solar and Wind Forecasting Tools
  • Power Flow Control (spatial)
  • Demand Response
  • Distributed Generation
  • Generator and Load Modeling
  • Statistical and Probabilistic Forecasting Tools
  • Advanced Intelligent Protection Systems
  • Synchrophasor Monitoring
smart grid reliability system restoration
Smart Grid

Reliability

System Restoration

  • Reilly Associates
  • PO Box 838
  • Red Bank, NJ 07701
  • Telephone: (732) 706-9460
  • Email: [email protected]
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