Michael Milligan, NREL (speaking for a large team at GE, 3TIER and NREL) Westconnect, Apr 21, 2009 Western Wind and Solar Integration Study Update

Overview Goal –To understand the costs and operating impacts due to the variability and uncertainty of wind, PV and concentrating solar power (CSP) on the grid –Not the cost of wind or solar generation Scope of study –Operations, not transmission study –Study year – 2017 to line up with WECC studies –Simulate load and climate of 2004, 2005, 2006 forecast to 2017

Scenario Overview Baseline – no new renewables In-Area – each transmission area meets its target from sources within that area –30% wind, 5% solar in footprint (20% wind, 3% solar in the rest of WECC) –20% wind, 3% solar (10% wind, 1% solar rest of WECC) –10% wind, 1% solar (10% wind, 1% solar rest of WECC) Mega Project – least cost of delivered energy Local Priority – similar to Mega Projects but with small bonus for in-area sites Plus other scenarios yet to be determined (high solar, high capacity value, high geographic diversity) Solar is 70% CSP and 30% PV. CSP has 6 hours of thermal storage. Penetrations are by energy

Mesoscale Modeling of Wind Data - 3TIER

Modeling such a large footprint is challenging Many terabytes of data “Seams” issues occurred in initial runs –Large wind ramps that were not real –Validated against meteorological towers Corrections improved the realism of the wind speed data  better estimates of wind power generation

All Wind Sites

Excluded Wind Sites

Available Wind Sites

Wind Selected for 30% In-Area Scenario 30% Wind In Footprint 20% Wind Out of Footprint 5,640 MW 18.5 TWh Legend: Wind MW Annual Energy 11,220 MW 29.9 TWh 900 MW 2.6 TWh 2,340 MW 8.4 TWh 2,790 MW 9.4 TWh 7,050 MW 17.3 TWh Total Installed MW: 29,940 MW (998 sites) Total Wind Capital Cost: $59.9 B Red dots = Pre-selected Blue dots = New sites

In-Area Scenario - Solar 700 MW 3.3 TWh Legend: CSPw/S MW PV MW Solar Annual Energy 1000 MW 5.3 TWh 200 MW 100 MW 0.5 TWh 0 MW 300 MW 0.4 TWh 400 MW 300 MW 1.6TWh 600 MW 500 MW 2.8 TWh Total In-footprint Installed MW: 2900 CSP w/S 2900 PV Total In-footprint Energy Solar: 15 TWh Total Solar Capital Cost: $23 B 5% Solar In Footprint 3% Solar Out of Footprint

30% In-Area Scenario Energy Summary In Footprint Out of Footprint 30% Wind, 5% Solar In Footprint 20% Wind, 3% Solar Out of Footprint

30% In-Area Scenario Power Summary In Footprint Out of Footprint Penetration = Wind Plant MW Rating Load MW

IN-AREA SCENARIO STATISTICAL ANALYSIS

Load, Wind, and Net Load Data for load, wind, and solar are time- synchronized For each MW of wind or solar that is generated, 1 MW of load need not be supplied by conventional generation Net load: Consumer load less –Wind generation –Solar generation Net load is what the system must operate to

Study Area Total, Load Wind, Solar and Net Load for Oct 8 th 2006 (30% In-Area Scenario) With old data With new data

Texas wind data validation Capacity Factor Actual31.2%33.0%34.1% Mesoscale34.6%32.1%33.8% 536 MW in 5 wind plants

Another site wind validation Mesoscale wind data capacity factor is off by 2-9%

Assessment of validation results NWP data has good overall match to expectation …but does not fully capture wind behavior and is not adequate for bankers or project assessment State of the art needs improving …but probably does a good job representing overall variability of wind over this large study footprint

Solar PV data – hourly and 10 min Satellite cloud cover model from R. Perez at SUNY/Albany produced 10 km hourly solar radiation data. R. George at NREL generated 10 minute data using measured PV output data.

Benefits of aggregated wind: Actual wind output vs. One-Hour delta as a Percentage of Installed Wind Capacity (30% Scenario) New Mexico (2006) Study area aggregation tends to mitigate relative impact of large ramps

Distribution of Extreme Hourly Wind Deltas 2004 – 2006 ( 30% In Area)

Study Area Monthly Energy from Wind and Solar for 2004 – 2006 (30% In Area Scenario)

Study Area Average Daily Energy from Wind and Solar for (30% In Area Scenario) Study Area Average Energy by hour, from Wind and Solar Study Area Average Percent Energy by hour, from Wind and Solar Hour of Day

State Monthly Energy from Wind and Solar for 2004 – 2006 (30% In Area Scenario)

Net Load Duration, Wind and Solar Penetration Over Year 2006 Min load MW CSP output for 60% of the year No PV production for half the year 113% Instantaneous penetration, based on load MW Below existing min load ~57% of year for 30% scenario 11.7% 7.3% 24 hours with over 100% penetration

Study Area Net Load Duration for 2004, 2005, 2006 (30% In Area Scenario)

Study Area Load and Wind Average Daily Profiles By Seasonal Month for 2006 (30% In Area Scenario) Jan Apr Jul Oct

Study Area CSPws and PV Average Daily Profiles By Seasonal Month for 2006 (30% In Area Scenario) Jan Apr Jul Oct

Study Area Total Load, Wind and Solar Variation Over Month of April (30% in Area Scenario) Substantial increase in net load variability driven largely by wind variation Minimum net load: –2887 MW Instantaneous penetration: 112%

WECC Total Load, Wind and Solar Variation Over Month of April (30% in Area Scenario) Impact of wind on WECC net load less dramatic over a larger control area Minimum net load 20,525 MW Instantaneous penetration: 73%

Variability Analysis - Deltas Statistics used to characterize variability: –Delta (∆) – The difference between successive data points in a series, or period-to-period ramp rate. Positive delta is a rise or up-ramp Negative delta is a drop or down-ramp –Mean (  ) – The average of the deltas (typically zero within a diurnal cycle) –Sigma (σ) – The standard deviation of the deltas; measures spread about the mean For a normal distribution of deltas, σ is related to the percentage of deltas within a certain distance of the mean

Wind Deltas vs Load Deltas by season for (30% in Area Scenario) (1199, -5926) (-4125, 2950) Increased L-W up-ramps Increased L-W down-ramps Load and wind deltas offset Load and Wind deltas offset Q1 Q2 Q4 Q3 (2985, -4372) MW MW MW MW MW (186, 7528) 29 hours (342 GWh) where wind pushes L-W delta beyond largest load delta

Wind Deltas vs Load Deltas by season for (30% in Area Scenario) Increased L-W up-ramps Increased L-W down-ramps Load and wind deltas offset

Load and Net Load Delta (MW) Total Load and Net Load(MW) Study Area Average Daily Profile of Deltas Over Year 2006 (30% In Area Scenario) (Avg. +/- sigma, Minimum, Maximum) Hour of Day 7874 MW MW

Study Area Total Load, Wind and Solar Variation for Selected Days (30% In Area Scenario) L-W-S Maximum Positive Delta Day - Jan L-W-S Maximum Negative Delta Day - Mar 26, 2006 Minimum Net Load Day - Apr Solar Maximum Negative Delta Day - Jan

Summary Statistics for

IN-AREA SCENARIO OPERATIONAL ANALYSIS

Study Assumptions 2017 Fuel Prices: Coal ~ $2.00/MBtu Natural Gas ~$8.00/MBtu Carbon Tax : $30/ton Energy Velocity Database ~24 GW capacity added timeframe to maintain reserve margins (~11GW not in plans) NERC ES&D Peak Load Projections Economically Rational, WECC-wide Commitment and Dispatch

Forecast Error Forecast error varied annually and regionally Reduced forecast 10% in study footprint and 20%outside “R” scenarios Also considered perfect forecasts “P” scenarios

Combined cycle units most displaced

Pumped storage has moderate increase

Weekly Operational Analysis Examined hourly operation for two specific weeks in mid-April and mid-July Results show hourly variation in generation by type as renewable penetration increases

Operational Observations Forecasts are critical Significant variations in impact for the same wind variability with different forecasts No significant issues at penetrations up to 20% wind in study footprint and 10% wind outside Impact more severe at 30% wind inside and 20% wind outside Operational impact dependent on what your neighbor is doing

ADDITIONAL SCENARIOS BEING ANALYZED CURRENTLY

Rationalize Site Distribution & Transmission Refine distribution identified by global algorithm to rational components Use whole 30 MW wind plants Use whole 100 MW solar plants Use typical transmission rating 345 or 500 kV AC for bulk interties 1000 or 1600 MW/circuit, respectively Select kV to match voltage level in vicinity HVDC for long distance and high power i.e. > 2 circuits of EHV AC Select in-footprint routes Disregard/consolidate small incremental ties to local transmission voltage level (e.g. 230kV/400 MW)

+2000 (300) 2 x 345kV (600) 2 x 345kV (800) 2 x 500kV (+11430) 1890 (-9330) 2490 (-3150) 4350 (+1560) 90 (-810) 1440 (-5610) Mega Project Scenario (2400 )MW 600kV DC Bipole (1600) 2 x 500kV Total Wind MW: (801 sites) [$46.2 B] Change from in-area MW: (-197 sites) (-$11.9B)(-20%) Total Solar MW: 5700 MW (-100 MW) [-$0.4 B] Total Additional Transmission: GW-miles [+$11 B] Total Change in Capital Cost: - $1B (900) 2 x 345kV (300) 1 x 345kV Legend: Final Wind MW (Change from In-Area MW) New Transmission MW (GW-miles)

+1600 (400) 1 x 500kV Local Priority Scenario 7380 (+5040) 7710 (-3510) 4650 (-990) 2970 (+180) 570 (-330) 3450 (-3600) (800) 1 x 500kV (150) 1 x 345kV (450) 1 x 345kV (300) 1 x 345kV Total Wind MW: (872 sites) [$52.3 B] Change from in-area MW: (-126 sites) (-$7.6B)(-13%) Total Solar MW: 5700 MW (-100 MW) [-$0.4 B] Total Additional Transmission: GW-miles [+$3.4 B] Total Change in Capital Cost: -$4.2B (-7.0%) Legend: Final Wind MW (Change from In-Area MW) New Transmission MW (GW-miles)

Next Steps Additional analysis of In-Area scenario Reserve requirements Quasi-steady-state analysis Analyze Mega-Project and Local Priority scenarios Develop two more proposed scenarios

Information WWSIS –Website at – –Western wind dataset at: – –Solar (and wind) dataset at: – Questions? –Debra Lew –