# 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 1

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, 20152Simulated dispatch for high solar period in FRCC Simulated dispatch for high wind period in SPP 

# Balance

# Transmission FlowsSimulated 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 14

Very large inter

regional transmission expansion used in ERGIS ITx30 scenario

# Modeling Tools

• ReEDS

– Regional Energy Deployment System

– Capacity expansion

– V ariability in wind and solar

– A ncillary 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 16

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 17

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 18

Category Minimum Generation Level 1 (% of Maximum Capacity) Average Heat Rate at Minimum Generation Level 1 (% of Full

- Load Average Heat Rate) Minimum Up Time 1 (Hours) Minimum Down Time 1 (Hours) Ramp Rate 2 (% of Maximum Capacity per Minute) Startup Cost 3 ($/MW of Maximum Capacity) Variable Operations and Maintenance Cost 3 ($/MWh) Annual Outage Rates 4 (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 19

# 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 23

# Annual Results

• High regional and interconnection

- wide penetrations levels

• Lower production costs

• Thermal plant displacement 24

# 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 25

# Regional Dispatch

• ISO

- NE during peak wind

• Canadian imports change

• DA Hydro schedules 26

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. 27

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 30

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 31

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 32

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 33

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 34

# Regional Transmission

Exports from NYISO to PJM for all four scenarios 35

# 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 36

# 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 37

# Research Team 38

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