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Technical Review Committee Meeting May 16, 2011

Debra Lew

National Renewable Energy LaboratoryGolden, Colorado USA

Western Wind and Solar Integration Study:

Scenarios and Data Inputs

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Agenda

• Status update• Scenarios• Data refinements

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Status

• Contracts underway or being processed with Wind Wear, and Intertek/APTECH (cost shared with WECC)

• GE contract being scoped• DOE approval of wind/solar scenarios• Plexos model up and running• WECC 2020 database completed and being tested

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Scenarios

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Proposed Scenarios

Penetration by Energy

High Wind Intermediate High Solar

11% WECC TEPPC 20208% wind3% solar

22%

33% 25% wind8% solar

16.5% wind16.5% solar

8% wind25% solar

Use NREL ReEDS model to expand generation fleet subject to geographical and electric power system constraints (and select regional distribution)

Solar consists of 40% CSP and 60% PVCSP has 10 hours of storage

*note that related side sensitivity analyses in FY12 may include Plexos runs of various penetrations of solar with various PV/CSP ratios

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High wind (25% wind, 4.8% PV, 3.2% CSP)

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Intermediate (16.5% wind, 9.9% PV, 6.6% CSP)

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High solar (8% wind, 15% PV, 10% CSP)

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Scenario Development Tasks

• Select locations of wind and solar sites based on capacity factor and proximity to transmission

• Map sites to HV buses• Run unconstrained and constrained transmission cases

in Plexos• Develop transmission expansion plan to accommodate

33% wind/solar• Run a final iteration in Plexos to determine if

transmission expansion is adequate

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Transmission zones

• Run zonally initially. Nodal runs at a later date for deeper dives.

• Propose to use these 20 TEPPC zones. Aiming at more rather than less zones to better approximate actual current operations.

• Commit and dispatch within each zone with hurdle rates between zones to allow for interzone transfers.

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Data Refinements

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Wind “Actuals” Dataset3TIER Western Wind Resources Dataset• Increased variability at 3-day seams – was not found to be a problem with hourly

MAPS simulations in WWSIS1. Every 3rd day was removed from statistical analysis in WWSIS1. We will use this for hourly Plexos simulations for WWSIS2. Subhourly analysis will have to be evaluated to see if seams create problems.

• Capacity factors differ from measurements in some areas, eg CO – Impact will be on geographic diversity because more sites will be needed to get at the same energy penetration. This is not deemed to have significant impact.

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Wind Forecast Dataset

x < -4500-4500 <= x < -4000-4000 <= x < -3500-3500 <= x < -3000-3000 <= x < -2500-2500 <= x < -2000-2000 <= x < -1500-1500 <= x < -1000-1000 <= x < -500-500 <= x < 00 <= x < 500500 <= x < 10001000 <= x < 15001500 <= x < 20002000 <= x < 25002500 <= x < 30003000 <= x < 35003500 <= x < 40004000 <= x < 4500x >= 4500

0

500

1000

1500

2000

2500

MW Error

Num

ber o

f Hou

rs

Western wind dataset has a positive bias in the day-ahead forecasts

Use measured wind forecast error distributions to correct bias

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Solar “Actuals” Dataset

• Utility-scale PV• Existing WECC PV dataset has 50 MW PV plants modeled for

10km grid cells• Filter function under development to model utility-scale PV

plants up to 500 MW. We will need to size and site these. Propose 50/50 split between metropolitan and remote areas.

• DG PV• Use DG rooftop PV dataset from WWSIS1• Distribute generation identical to load in each load bubble

• CSP• Rerun CSP profiles for 10 hours of storage• Select best sites

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Solar Forecasts Dataset

• Obtaining solar forecast error distributions• Check existing solar forecast dataset against measured

forecast error distributions• Refine existing solar forecast dataset as necessary to

match measured distributions

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Heat rate penalties (heat input or CO2)

Unit type Part-load penalty

Ramping penalty

Startup penalty

Coal 5.1% 0.4% 110%

Gas CC 15.6% 0.3% 32%

Gas CT 12.4% 0.3% 32%

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Other emissions (NOx,SO2)

Unit type Part-load penalty

Ramping penalty

Startup penalty

Coal (NOx) 1.2% 2.8% 290%

Gas CC 30%** 0.7% 950%**

Gas CT 19% 0.8% 670%**

Coal (SO2) 5.4% 13.4% 270%

**These numbers are highly sensitive to input assumptions (percent loading) and/or a small number of extreme outliers (some are bad fits).

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Retirement Scenarios

• Other analysis shows plant retirements to have significant impact on cycling/ramping costs

• Data options• WECC TEPPC DWG retirements are based on CAISO 33%

study• GE analysis on plant retirements