Integrating Renewable Electricity on the Grid. Jim Misewich Associate Laboratory Director

Transcription

1 Integrating Renewable Electricity on the Grid Jim Misewich Associate Laboratory Director

2 Renewable Portfolio Standards 30 states and DC have RPS typically 20% renewable power by 2020 or 2030 most aggressive: CA -33% by 2020 NY 30% by 2015, 80% by 2050 Drivers for RPS reduced carbon emission encourage alternative energy prepare for electrification of transportation replace foreign oil with renewable electricity jobs and economic growth

3 Executive Order 24: 80% Carbon Reduction by % of US population 4.1% of primary energy VISIONING 2050 Effort (NY Energy Policy Institute): All scenarios suggest great increase in use of electricity 2050 Visioning Document (draft) Patterns and Trends: New York State Energy Profiles , New York State Energy Research and Development Authority.

4 NYS Smart Grid Vision One of the most promising ways we can empower customers to lower their energy costs while achieving greater energy efficiency is what has come to be known as the "smart grid". Andrew M. Cuomo, Governor of New York Utilities: NY Power Authority LI Power Authority Con Edison National Grid NYSEG NYISO Government: NYSERDA NYSTAR Public Service Commission Integration of Renewables Industry: General Electric IBM Computer Associates Research: SUNY Advanced Energy Center Brookhaven National Lab Syracuse University RIT University of Rochester Clarkson NYU Polytechnic CUNY Consumers: NY Energy Consumers Council NY Business Council 4 Confidential

5 American Physical Society Panel on Public Affairs (POPA) Co-chairs: George Crabtree (ANL) and Jim Misewich (BNL) Committee: Ron Ambrosio(IBM), Kathryn Clay (Auto Alliance), Paul DeMartini(Southern California Edison), RevisJames (EPRI), Mark Lauby(NERC), VivekMohta(MA Dept of Energy Resources), John Moura(FERC), Peter Sauer (UIUC), HumayunTai (McKinsey), Kris Larsen (APS), Jodi Lieberman (APS), Francis Slakey (APS) January 2011

6 Abundant Wind and Solar Resources Concentrating Solar Power Direct Sun State Available Resource Area Potential Wind Resource (mi 2 ) (GW) Arizona 19,300 2,468 California 6, Colorado 2, Nevada 5, New Mexico 15,200 1,940 Texas 1, Utah 3, Total 53,900 6,877 Mehosand Kearney (2007) PV Solar Resource Indirect Sun Roof area ~ 6B m 2 ~ 600 GW Urban footprint ~ 3% of land ~ 2300 GW Solar Technologies Market Report EERE (2008) 2009 electricity use ~ 450 GW (ave) ~ 1000 GW (peak) 2030 projection ~ 660 GW (ave) Black and Veatch (2007) wind and solar resources far exceed RPS 6

7 Variability Xcel Wind Farm, Minnesota 1.5 GW Wind in 10 GW Peak System Solar PV 6 Load 3 GW 4 2 Load -Wind Wind MW Day Wind variability: up to 100% of capacity on calm days Load variability: 30% -50% of peak predictable to a few percent Minutes since start of day Generation variability < load variability: compensate ~ with existing reserves Generation variability > load variability: reserves ~ renewable capacity Solar variability: up to 70% of capacity due to clouds Penetration beyond load variation requires high reserves Accurate weather forecasts are critical 20% Wind Energy by 2030, Energy Efficiency and Renewable Energy, DOE/GO (2008) Johan Enslin, Quantum Technology, Grid Impacts and Solutions of Renewables at High Penetration Levels, APS Grid Study (2009)

8 Forecasting 400 Alberta Electric System Operator Forecasting Pilot Project 24 hours beginning Midnight Apr 14, 2008 MW Forecasts disagree by 50% to factor of 20 Wind shifts from lowest to highest in 3 hrs 100 0:00 4:00 8:00 12:00 16:00 20:00 24:00 1 Actual Wind Fcst 1 Fcst 2 Fcst 3 Improve accuracy by enlarging forecast area Confidence level as important as accuracy Low confidence level higher reserves σensemble/σsingle Region size (km) Improve accuracy and confidence level of forecasts Uniform standards for preparing and delivering forecasts

9 Responding to Weather Fraction of rated output (%) Power Curve of Typical Wind Turbine Wind speed (m/s) 20% error in wind speed (2 m/s) = 41% error in power output thresholds: start-up: 3 m/s curtailment: 25 m/s output depends on air density temperature, humidity local topography local air flows output ceases Operating Procedures standard responses to generation up-ramp at low load generation down-ramp at peak load contingency usual: loss of largest generator renewable: no largest generator Better translation of wind speed to power generation Develop and codify operational responses to forecasts Define contingencies and response plan

10 Large-scale energy storage is critical for renewable penetration and grid stability and reliability Size of the challenge How much storage is needed? Over 200GWh of balancing resource (e.g. storage) needed to meet DOE 20% Wind by 2030 goal (20% of wind output) 15,000 PHEV batteries required to shift 4 hours of wind from one 100MW project Drivers for Large Scale Energy Storage Renewable Generation Grid Reliability Management Power quality Load leveling, shifting

11 Energy Storage Options Okinawa Seawater Pumped Storage Compressed Air Energy Storage Huntorf Germany (290 MW), McIntosh Alabama (110 MW) Sodium Sulfur batteries at Wind Farm Xcel Energy, Luverne, MN Molten salt thermal storage Andasol, Spain ow-to-use-solar-energy-at-night Flow batteries Conventional batteries: Lead acid Southern California Edison Chino facility (10 MW, 4 hr) develop an overall strategy for storage options, regulatory guidance, value for generation and transmission conduct technological review of battery chemistries increase R&D in basic electrochemistry

12 Brookhaven Collaborative Approach Basic Research, Applied Research, and Industry Working Together BNL Resources CFN/Nanoscience BNL Research NY State Consortia/Resources ENERGY CHALLENGES: New York and Beyond Electric Systems Sustainable Fuels DOE ALIGNMENT/LEVERAGE DOE Priority Research Directions 4 Energy Frontier Research Centers NSLS/ NSLS II Collaborators/Joint Appointments New York Blue SYRACUSE

13 Electric Grid Research and Development Generation Organic photovoltaics Inexpensive for large scale deployment Issue of efficiency Transmission Superconducting Lines Power density driver Storage Batteries X-ray probes, materials BNL Contribution Nano-structured PV with double the efficiency per active unit area BNL Contribution Reel-to-reel growth of superconducting materials BNL Contribution X-ray tools probing real batteries in operation SMES Grid scale storage

14 New York State Opportunity Key Consortia Established NYBEST: New York Battery and Energy Storage Technology Consortium NY Smart Grid Connection NYSERDA: a unique asset Support Seed Resources Industrial Base Outstanding R&D Assets A National Laboratory The KEY: New York Institutions working together 14