The Eastern Renewable 

Generation Integration Study: 

Flexibility and High Penetrations 

of Wind and Solar

Aaron Bloom, Aaron Townsend, and David Palchak

The National Renewable Energy Laboratory

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NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable 

Energy, operated by the Alliance for Sustainable Energy, LLC.

NREL/PR-6A20-64795

IEEE PES General Meeting

Denver, Colorado

July 26-30, 2015
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Simulated dispatch for high wind period in SPP Simulated dispatch for high solar period in FRCC

Balance
Transmission Flows
Simulated commitment and dispatch for PJM in April

Commitment and Dispatch
Answering Critical Questions

• How might power system operations be 

impacted by wind and solar power 

generation? 

• Could the operational impacts differ based on 

policy decisions about regional versus national 

deployment strategies?

• How might high penetrations of wind and 

solar impact current regional practices?
Study Limitations

• We lack:

– Bilateral power purchase and other contractual agreement 

data

– Detailed operational constraints and/or complete unit- specific data in the generation models

– Capability to simultaneously model different dispatch 

intervals in different balancing authority areas

• Uncertainties:

– Future cooperation and/or sub-hourly dispatch across the 

interconnection

– The amount and location of variable generation

– Transmission system additions

– Generation additions and retirements

– Gas and coal prices
The Eastern Interconnection

• Generating capacity:

700 GW

• Generating units:

7,500

• Load: 

3,000 TWh

• Population: 

240 million people

• 70% of US Load

• Transmission length: 

459,000 miles

• Nodes:

60,000

• Transmission lines:

50,000
The Eastern Interconnection

• Generating capacity:

700 GW

• Generating units:

7,500

• Load: 

3,000 TWh

• Population: 

240 million people

• 70% of US Load

• Transmission length: 

459,000 miles

• Nodes:

60,000

• Transmission lines:

50,000
Technical Review Committee

• Industry experts:

– RTO/ISO

– Utilities

– Cooperatives

– National Laboratories

• Provide guidance on:

– Scenarios

– Methods 

– Assumptions

– Results

Leading Research

Tools

Leading 

Data

Industry 

Experts
Scenarios

Generator Type Installed Capacity (GW)

2010 LowVG RTx10 RTx30 ITx30

Wind 7 24 104 183 222

PV 0 1 5 219 110

Nuclear 105 102

Coal 298 230

Gas CC 165 173

CT/Gas Boiler 166 148

Hydro 85 87

Other 55 22

• Low VG

– Renewables in service in 2010, 

modest transmission upgrades

• RTx10

– Regional Transmission, 10% VG 

penetration, mostly wind.

• RTx30

– Regional Transmission, 30% 

penetration, 20% wind, 10% 

solar

• ITx30

– Inter-regional Transmission, 30% 

penetration, 25% wind, 5% solar

Non-wind and solar 

fleet remains 

constant
EIPC Transmission Expansions

12

Eastern Interconnection Planning Collaborative (EIPC) is a industry driven, DOE funded, organization that 

studies transmission planning scenarios

Modest 

transmission 

expansion, 

used in ERGIS 

Low VG 

Scenario
EIPC Transmission Expansions

13

Large regional 

transmission 

expansions 

used in ERGIS 

RTx10 and 

RTx30 

scenarios
EIPC Transmission Expansions

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Very large interregional 

transmission 

expansion used 

in ERGIS ITx30 

scenario
Modeling Tools

• ReEDS

– Regional Energy Deployment 

System

– Capacity expansion

– Variability in wind and solar 

– Ancillary service requirements

• PLEXOS

– Unit commitment and economic 

dispatch

– Nodal DC power flow

– Day-ahead (hourly)

– Real-time (5-minute)

– Mixed-integer

U.S. Department of Energy. (2015). “WindVision: A New Era for Wind 

Power in the United States.” DOE/GO-102015-4557. Washington, DC: 

DOE.

PLEXOS Integrated Energy Model version 6.400 R02 x64 Edition [compute 

software]. (2014). Accessed May 20, 2015: http://energyexemplar.com/. 
High Resolution Data

• Eastern Wind Data Set

– Simulated power data

– Sites: 1,326

– Years: 2004–2006

– Capacity: 580 GW

– 2-km resolution

http://www.nrel.gov/electricity/transmission/eastern_wind_methodology.html

Solar Data Set

– Simulated power data

– Sites: 4,089

– Years: 2006 

– Time: 5-minute resolution

– Capacity: 174 GW

http://www.nrel.gov/electricity/transmission/solar_integration_methodology.html

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Meteorologically 

synchronized data 

sets!
High Resolution Data

• ERGIS Load Data Set

– 5-minute variability statistics extracted from industry data

• ERGIS Hydro Data Set

– Calculate energy limits based on annual energy generation 

and monthly or daily flow data

– Monthly and daily energy limits 

– US EI hydro generating capacity: 30 GW

– Canadian EI and HQ hydro generating capacity: 60 GW

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2006 U.S. EI Load 2,913 TWh

2026 U.S. EI Load 3,238 TWh

U.S. EI Load Growth 2006–2026 11.14%

ERGIS Load Growth Summary
Detailed Thermal Assumptions

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Category Minimum 

Generation 

Level1

(% of Maximum 

Capacity)

Average Heat 

Rate at Minimum 

Generation 

Level1

(% of Full-Load 

Average Heat 

Rate)

Minimum Up 

Time1

(Hours)

Minimum Down 

Time1

(Hours)

Ramp Rate2

(% of Maximum 

Capacity per 

Minute)

Startup Cost3

($/MW of 

Maximum 

Capacity)

Variable 

Operations and 

Maintenance 

Cost3

($/MWh)

Annual Outage 

Rates4 (Sum of 

Forced and 

Maintenance 

Outages) 

(% of Year)

CT 60 100 0 0 8 69 0.6 7.6–12.0

CC 50 113 6 8 5 79 1 10.9

Coal 50 (<600 MW)

30 (>600 MW)

106 24 12 2 129 2.8 12.1–17.1

Oil/Gas 

Boiler

30 (<600 MW) 

20 (>600 MW)

110 10 8 4 129 0.9 9.8–26.0

Nuclear 100 100 NA NA NA 0 2.8 8.9–14.1 a Adopted from EIPC with minor changes (see text for details).

b From Black and Veatch 2012.

c From Kumar et al. 2012.

d From GADS, 2015
Transmission Constraints

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Computational Challenge

• As resolution and system size increase simulation becomes 

computationally intractable

• Multi-week simulation solve times led to a variety of model 

simplifications

• Initial estimated solve time for ERGIS over 500 days!
Rethinking Unit Commitment and Dispatch

• A decision at time t is not 

dependent on the state of 

the system at previous 

time intervals, given a 

delay of n time periods.

Photo by Steven Hammond, NREL

Barrows, C.; Hummon, M.; Jones, W.; Hale, E. (2014). Time Domain 

Partitioning of Electricity Production Cost Simulations. TP-6A20-60969. 

Golden, CO: National Renewable Energy Laboratory. 
Simulation Time Comparison
ERGIS Simulations

• One-year of simulations

• 8,760 one-hour time 

steps

• 105,120 5-minute time 

steps

• Hurdle rates 

=$10/MWh between 

regions

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Annual Results

• High regional and 

interconnection-wide 

penetrations levels

• Lower production costs

• Thermal plant displacement

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ERGIS Peak Wind

• US EI results for 3 days 

in April 

• Shifts in timing of 

thermal and hydro use

• Wind and PV 

curtailment across the 

day

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Regional Dispatch

• ISO-NE during peak 

wind

• Canadian imports 

change

• DA Hydro schedules

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Imports

Curtailments because of Solar Forecast 

Error + DA Hydro constraints
Regional Commitment and Dispatch

FRCC commitment and dispatch for PV, wind, CT, CC, and coal during high PV generation in the U.S. EI.

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CT startup

Solar forecast error

CC and coal are at 

minimums, only 

options for model 

is curtailment
SPP Highest Wind and Solar Day

ITx30

RTx30
FRCC High Solar Period

FRCC

SERC

RTx30

Pumped 

Storage 

changes 

operational 

pattern
Thermal Flexibility

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Number of ramps for the total U.S. EI as well as all 

U.S. regional fleets divided by the energy produced.

Capacity factors of thermal units for the total fleet 

in the U.S. EI (top), Average output of committed 

units (middle) and percent of online time at 

minimum generation (bottom)
Wind and PV Curtailment

• Curtailment is a reduction in the 

output of a wind or PV 

generator from what it could 

otherwise produce for given 

meteorological conditions

• A form of flexibility, though not 

a very desirable one 

• Causes:

– Transmission

– Forecast Errors

– Thermal and Hydro limits

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Scenario Curtailment (%)

LowVG 0.3

RTx10 2.9

RTx30 6.5

ITx30 3.8

Annual average daily profiles of curtailment for the whole U.S. EI and for each U.S. region
Hydro and Pumped Storage

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Average daily pumped hydro operation in all 

scenarios.

Average daily hydro generation in all 

scenarios
Reserves

• Spinning and Regulation 

reserves were held for 

all regions

• Did not simulate 

deployment of reserves

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Distribution of regulation reserve by region and scenario

Scenario Contingency (TW-h) Regulation (TW-h)

LowVG 97.1 33.0

RTx10 97.1 38.8

RTx30 97.1 50.2

ITx30 97.1 51.1
Transmission

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Regional Transmission

Exports from NYISO to PJM for all four scenarios

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What we learned about flexibility

• Thermal and hydro facilities can inherently provide 

lots of system flexibility 

• Room for improvement in modeling

– Hydro constraints, DA schedules fixed in RT in ERGIS

– Transmission ramp rate limits

– Regional differences in operational sequences

– Soft Constraints

• Thermal limit exceptions

– Market impacts on system capacity

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Study Findings

• Simulated levels of wind and PV generation can be balanced 

during normal operations in the Eastern Interconnection

• Efficient utilization of available wind and PV depends upon 

transmission availability and characteristics of the generation 

fleet

• Annual wind and PV penetrations of 30% decrease production 

costs and emissions by approximately 30%

• Wind and PV affect the operation of conventional generation 

sources in the Eastern Interconnection 

• Avenues for achieving 30% penetrations of wind and PV in the 

U.S. EI is possible through multiple pathways

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Research Team

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Aaron Bloom

Project Manager

Aaron.bloom@nrel.gov

Dr. Aaron Townsend

Technical Lead

Aaron.townsend@nrel.gov

David Palchak

Analysis Lead

David.palchak@nrel.gov