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TO:Joint Guidance Committee (JGC)

FROM:Variable Generation Subcommittee (VGS)

DATE:March 26, 2012

SUBJECT:Variable Generation Capacity Assignment

There have been many studies performed to estimate a capacity assignment of wind and solar power for adequacy planning. The capacity value attributed to variablegeneration (VG)is dependent on several factors, including weather patterns, local-grid topography, resource mix, and overall VG penetration. Because of these factors, it is difficult to provide a capacity-credit value that can be used for all balancing authorities (BAs) in the Western Interconnection. To estimate the capacity credit attributable to wind and solar power, each BA would need to perform studies based on their own specific system.

The VGS has reviewed three reports that summarize different methods of determining capacity value of wind and solar power for resource planning purposes.

  • Methods to Model and Calculate Capacity Contributions of Variable Generation for Resource Adequacy Planning[1] (produced by the National Renewable Energy Laboratory (NREL))
  • Summary of Time Period-Based and Other Approximation Methods for Determining the Capacity Value of Wind and Solar in the United States[2] (produced by NREL)
  • Determining the Capacity Value of Wind: An Updated Survey of Methods and Implementation[3] (produced by the North American Electric Reliability Corporation (NERC) Integrating Variable Generation Task Force)

The table below lists some of the capacity assignments used by different North American Entities. These are summarized based on information in the two NREL reports listed above. The table is provided to help readers visualize the range of capacity-credit values that different North American Entities have given to wind and solar power plants. It is possible that some of the Entities in the table have updated their capacity-credit calculations since the publication of the NREL reports.

Entity / Wind Capacity Credit / Solar Capacity Credit / Notes
Arizona Public Service / N/A / 45.2% - residential PV, 18.4% tilt, south-facing
47.4% - commercial PV,10% tilt south-facing
70.2% - commercial PV, north-south single axis tracking / Average between 2003 and 2007.
BC Hydro / 24% / N/A / Applies to onshore wind, offshore wind, and solar power. Based on effective load carrying capability.
Bonneville Power Administration / 0% / N/A
Hydro-Quebec / 30% / N/A / Determined through the FEPMC model.
PJM / 13% for new projects, rolling three-year average capacity value for existing projects. / 38% for new projects, rolling one-year average capacity value for existing projects. / Based on average capacity factor from 2-6 p.m. between June and August.
Portland General Electric / 5% / 5% / From 2009 Integrated Resource Plan.
New York ISO / New onshore projects: 10% (summer); 30% (winter).
New offshore projects: 38% for summer and winter.
Existing projects: Capacity factor from 2-6 p.m. between June and August (summer credit) and from 4-8 p.m. between December and February (winter credit) of the prior year. / 51%-90% at two percent solar penetration (using ELCC method). / Solar capacity credits come from Energy and Capacity Valuation of Photovoltaic Power Generation in New York.
ISO New England / Five-year rolling average from 1-6 p.m. between June and August of the previous year (summer) or from 5-7 p.m. between October and May (winter). / N/A / The report New England Wind Integration Study suggested capacity values between 28% and 36%.
MISO / 12.9% for 2011 planning and 14.7% for 2012 planning / N/A / MISO reviews capacity credits annually
Southwest Power Pool / Typically around 10% / N/A / SPP uses a monthly method for 12 capacity values for wind plants, examining the highest 10% of load hours in the month.
Minnesota Department of Commerce/Xcel / 5% - 20% / N/A / Based on a study performed in 2006. Capacity values depend on penetration level of wind.
PacifiCorp / 8.53% / N/A / From 2011 Integrated Resource Plan, using ELCC.
ERCOT / 8.7% / N/A / ERCOT is performing a new LOLP study, to be completed Q3 2012, which may provide a new value.
Mid-Continent Area Power Pool / Median value of 4-hour peak period (using up to 10 years of historic data). / N/A / Any contiguous 4-hour period is fine as long as the peak is within the period.
Nebraska Public Power District / 0% based on Southwest Power Pool criteria, 8% based on Midwest Reliability Organization long-term reliability assessments / N/A
NorthWestern Energy / 0% / N/A
Ontario Independent Electric System Operator / Estimate of peak demand capacity contribution, based on historic and simulated wind data. / N/A
Idaho Power / 5% / N/A / From 2011 Integrated Resource Plan, based on peak hour planning.
Pacific Northwest (Northwest Resource Adequacy Forum) / 5% / N/A / Derived anecdotally from historic wind generation data in the BPA wind fleet.
California PUC / Set at the minimum output achieved historically in 70% or more of the hours for each month. Based on three years of historic data from 1-6 p.m. between April and October and from 4-9 p.m. between November and March. / N/A / This methodology was implemented in June 2009.
State legislation requires the CPUC to revise wind and solar capacity values based on effective load carrying capability.
Public Service of New Mexico / 5% / 55% / From 2011 integrated resource plan.
Tri-State Generation and Transmission / Less than 2% / 20% - 57% / From 2010 integrated resource plan.
Public Service Company of Colorado / 12.5% / 55% / Wind capacity credit used in the 2007 IRP plan. Solar capacity credit used in the 2011 electric resource plan.

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[1] M. Milligan, K. Porter “Determining the Capacity Value of Wind: An Updated Survey of Methods and Implementation.” National Renewable Energy Laboratory, June 2008.

[2] J. Rogers, K. Porter “Summary of Time Period-Based and Other Approximation Methods for Determining the Capacity Value of Wind and Solar in the United States.” National Renewable Energy Laboratory, March 2012.

[3]“Methods to Model and Calculate Capacity Contributions of Variable Generation for Resource Adequacy and Planning.” NERC, May 2011.