A R EVIEW OF L ARGE -S CALE R ENEWABLE E LECTRICITY I NTEGRATION S TUDIES Paulina Jaramillo, Carnegie Mellon University And Paul Hines, University of Vermont

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 2

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 3

NYSERDA ,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 4

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

Minnesota Wind Integration Study 15%, 20%, and 25% wind integration in MISO for the year 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.

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.

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 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 8

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. 9

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.” 10

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. 11

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. 12

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. 13

2010 studies by NERC, CAISO NERC analysis of renewables & reliability 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. 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. 14

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. 15

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 16