Curtailing Intermittent Generation in Electrical Systems

Energy generation from intermittent renewable sources introduces additional variability into electrical systems, resulting in a higher cost of balancing against the increased variabilities. Ways to balance demand and supply for electricity include using flexible generation resources, storage operations, and curtailing intermittent generation. This paper focuses on the operational and environmental impact of curtailing intermittent generation. We construct a stochastic dynamic optimization model that captures the critical components of the system operating cost and analyze how various generation resources should operate with and without curtailing intermittent generation. We find that the system cost reduction per unit of curtailed energy is consistently significant and the presence of storage may increase the cost saving per unit of curtailed energy. We also find that curtailing intermittent generation often leads to system emission reductions.

[1]  G. Brinkman,et al.  How Does Wind Affect Coal? Cycling, Emissions, and Costs (Presentation) , 2011 .

[2]  Kara Clark,et al.  Western Wind and Solar Integration Study , 2011 .

[3]  Pierre Ailliot,et al.  Markov-switching autoregressive models for wind time series , 2012, Environ. Model. Softw..

[4]  Mark Z. Jacobson,et al.  The Potential of Intermittent Renewables to Meet Electric Power Demand: Current Methods and Emerging Analytical Techniques , 2012, Proceedings of the IEEE.

[5]  Geothermal Energy.  Western Wind and Solar Integration Study , 2010 .

[6]  Erik Ela.  Using Economics to Determine the Efficient Curtailment of Wind Energy , 2009 .

[7]  Marc Prevosto,et al.  Survey of stochastic models for wind and sea state time series , 2007 .

[8]  B. Kirby,et al.  Operational Analysis and Methods for Wind Integration Studies , 2012, IEEE Transactions on Sustainable Energy.

[9]  M. J. Grubb,et al.  Value of variable sources on power systems , 1991 .

[10]  Meherwan P. Boyce,et al.  Handbook for Cogeneration and Combined Cycle Power Plants , 2010 .

[11]  Heike Brand,et al.  WILMAR: A Stochastic Programming Tool to Analyze the Large-Scale Integration of Wind Energy , 2009 .

[12]  M. O'Malley,et al.  Unit Commitment for Systems With Significant Wind Penetration , 2009, IEEE Transactions on Power Systems.

[13]  Erik Ela,et al.  The evolution of wind power integration studies: Past, present, and future , 2009, 2009 IEEE Power & Energy Society General Meeting.

[14]  E. D. Farmer,et al.  Economic and operational implications of a complex of wind-driven generators on a power system , 1980 .

[15]  Goran Strbac,et al.  QUANTIFYING THE SYSTEM COSTS OF ADDITIONAL RENEWABLES IN 2020 , 2002 .

[16]  Heike Brand,et al.  Advanced Unit Commitment Strategies in the United States Eastern Interconnection , 2011 .

[17]  E. Ela,et al.  Participation of Wind Power in LMP-Based Energy Markets , 2012, IEEE Transactions on Sustainable Energy.

[18]  M. Shahidehpour,et al.  Short-term scheduling of combined cycle units , 2004, IEEE Transactions on Power Systems.

[19]  Michael Grubb,et al.  The integration of renewable electricity sources , 1991 .

[20]  Bent Sørensen,et al.  On the fluctuating power generation of large wind energy converters, with and without storage facilities , 1978 .

[21]  M. Dempster,et al.  Optimal capacity expansion under uncertainty , 1987, Advances in Applied Probability.

[22]  E.A. DeMeo,et al.  Utility Wind Integration and Operating Impact State of the Art , 2007, IEEE Transactions on Power Systems.

[23]  Daniel P. Heyman,et al.  Stochastic models in operations research , 1982 .

[24]  Alex Pavlak.  The Economic Value of Wind Energy , 2008 .

[25]  Janice C. Eberly,et al.  Multi-Factor Dynamic Investment Under Uncertainty , 1996 .

[26]  Joseph Bockhorst,et al.  Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting , 2010, NIPS.

[27]  G. C. Varvaloucas,et al.  Capacity Expansion/Contraction of a Facility with Demand Augmentation Dynamics , 1984, Oper. Res..

[28]  Edward Kahn,et al.  The Compatibility of Wind and Solar Technology with Conventional Energy Systems , 1979 .

[29]  John Saintcross,et al.  THE EFFECTS OF INTEGRATING WIND POWER ON TRANSMISSION SYSTEM PLANNING, RELIABILITY, AND OPERATIONS , 2004 .

[30]  Bruce H. Krogh,et al.  Wind Integration in Power Systems: Operational Challenges and Possible Solutions , 2011, Proceedings of the IEEE.

[31]  S. Fink,et al.  Examples of Wind Energy Curtailment Practices , 2010 .

[32]  Henrik Madsen,et al.  Regime-switching modelling of the fluctuations of offshore wind generation , 2008 .

[33]  Ventyx.  Eastern Wind Integration and Transmission Study: Executive Summary and Project Overview (Revised) , 2011 .

[34]  G. Jordan,et al.  Analysis of Cycling Costs in Western Wind and Solar Integration Study , 2012 .

[35]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[36]  Jay Apt,et al.  Air emissions due to wind and solar power. , 2009, Environmental science & technology.

[37]  R. Newman.  Promotion of the use of energy from renewable sources , 2014 .

[38]  D. J. Swider,et al.  The costs of wind's intermittency in Germany: application of a stochastic electricity market model , 2007 .

[39]  Evan L. Porteus,et al.  Simultaneous Capacity and Production Management of Short-Life-Cycle, Produce-to-Stock Goods Under Stochastic Demand , 2002, Manag. Sci..