A Review of Large-Scale Renewable Electricity Integration Studies

1. A Review of Large-Scale Renewable Electricity Integration Studies Paulina Jaramillo, Carnegie Mellon University And Paul Hines, University of Vermont

2. Introduction • 33 States have developed Renewable Portfolio Standards • Many RPS call for large percentages (~20%) of Renewable electricity • Wind is the fastest growing renewable source • Wind: Intermittent and Variable www.renewelec.org

3. Integration Studies • Several recent studies evaluate the impacts of renewables on grid operations, and identify strategies to mitigate these impacts. • We performed a systematic review of recent integration studies, focusing on wind Goals of our review • What grid, wind data were used? • Evaluate methodology for estimating • Wind power variation • Reserves requirements • Regulation requirements • Identify research gaps

4. NYSERDA 2005 • 3,300 MW of Wind in New York State. • The analysis separates among different time scales. • Brief analysis of forecast value. • Main recommendation: Wind farms build voltage controls and low voltage ride through capability. • Major Concern: Use of Gaussian methods for reserve calculations • Conclusions based largely on measured standard deviation and mean

5. Empirical comparison of real wind data and “Normal” wind data Real wind data, 31% CF, Std. Dev. ΔP = 21 MW Gaussian data, 31% CF, Std. Dev. ΔP = 21 MW The Gaussian assumption dramatically underestimates the probability of multiple sequential large changes in the same direction.

6. 2006 Minnesota Wind Integration Study • 15%, 20%, and 25% wind integration in MISO for the year 2020. • Conclusion: • Penalty for variability between $2 and $4 per MWh. • Increasing spatial diversity reduces the number of “no-wind power” events, reserves requirements. • Concerns: • Gaussian methods for reserves calculations. • Analysis gap for short term modeling.

7. 2007 CAISO Wind Integration Study • Modeled theoretical wind plants in California and identified transmission requirements. • Conclusion: • Using Types 3 and 4 turbines will allow for reliable wind integration. • Concern: • Use of Gaussian methods for reserve calculations.

8. 2008 NREL’s 20% Wind by 2020 • Not really an integration study, but a projection of technology and economic requirements to achieve 20% wind by 2030. • Good comparison of available wind power at various wind speed class levels. • Recommendation: Build transmission • Concern: Transmission system modeling not based on Kirchhoff’s & Ohm’s laws

9. 2008 ERCOT Wind Integration • Analysis of impact of wind generation on net load. • Conclusions: • Wind AND load are variable and out-of-phase. • Seasonal variations exist. • Reserve and regulation requirements increase with increased wind power. • Concern: • Use of Gaussian methods for reserve calculations. • No grid model.

10. 2009 Trade Wind Integration Study - Europe • Study focused on transmission flows to identify transmission needs. • Assumes that regional diversity is sufficient to deal with the variability of wind power. • No discussion about reliability and reserves. • Potentially erroneous finding: “Wind and Load are positively correlated.”

11. 2010 Eastern Wind Integration and Transmission Study • 4 different scenarios with different percentage of wind generation and different wind production locations. • Use of DC power flow model allows them to identify transmission investment that will be needed at larger wind generation percentages. • Estimated reserved requirements, forecast error, curtailment and impacts of geographic diversity.

12. 2010 SW Power Pool (CRA) • Study 10%, 20% and (limited) 40% wind penetration. • Detailed contingency study. • Based on hourly and limited high-resolution data. • Conclude that no additional contingency reserves needed.

13. 2010 CEC/KEMA study of reserves and regulation • Analyze 20% and 33% renewable scenarios. • First large-scale study to include dynamic generator models. • Conclude that fast-ramping storage is needed to manage ACE and frequency deviations.

14. 2010 studies by NERC, CAISO NERC analysis of renewables & reliability CAISO analysis of 20% renewable in 2012 (PNNL) 1-minute wind data data Monte-Carlo model to model forecasts Regulation estimates based on 1-minute data One of the most careful studies reviewed (but still use standard deviations) Emphasize need to better understand load-following in morning/evening. • Qualitative study of reliability risks, given renewables, DSM, storage • Emphasize the need for more load-following during morning and evening ramps • New technology will require changes to operating policies.

15. Research gaps • Gaussian statistical methods Frequently conclusions are drawn from the mean and standard deviation of sampled wind data. • Need better models. • Larger control areas Several studies conclude that aggregating control areas reduces costs. • Further analysis needed.

16. Research gaps • Meteorological vs. anemometer data • Need empirical research to find the appropriate role for each. • Estimation of regulation requirements • Need new methods, for estimating regulation needs, given accurate wind and solar data. • Morning and evening ramping • Wind and load are generally anti-correlated during the morning and evening. Need new operating policies and technology