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Short-Term Congestion Forecasting in Wholesale Power Markets

Author

Listed:
  • Zhou, Qun
  • Tesfatsion, Leigh
  • Liu, Chen-Ching

Abstract

Short-term congestion forecasting is highly important for market participants in wholesale power markets that use Locational Marginal Prices (LMPs) to manage congestion. Accurate congestion forecasting facilitates market traders in bidding and trading activities and assists market operators in system planning. This study proposes a new short-term forecasting algorithm for congestion, LMPs, and other power system variables based on the concept of system patterns—combinations of status flags for generating units and transmission lines. The advantage of this algorithm relative to standard statistical forecasting methods is that structural aspects underlying power market operations are exploited to reduce forecast error. The advantage relative to previously proposed structural forecasting methods is that data requirements are substantially reduced. Forecasting results based on a NYISO case study demonstrate the feasibility and accuracy of the proposed algorithm.

Suggested Citation

  • Zhou, Qun & Tesfatsion, Leigh & Liu, Chen-Ching, 2010. "Short-Term Congestion Forecasting in Wholesale Power Markets," Staff General Research Papers Archive 31700, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:31700
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    File URL: http://www2.econ.iastate.edu/papers/p11700-2010-07-19.pdf
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    File URL: http://www2.econ.iastate.edu/tesfatsi/CongestionForecasting.ZTL.pdf
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    Citations

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    Cited by:

    1. Somani, Abhishek, 2012. "Financial risk management and market performance in restructured electric power markets: Theoretical and agent-based test bed studies," ISU General Staff Papers 201201010800003479, Iowa State University, Department of Economics.

    More about this item

    Keywords

    wholesale power market; locational marginal price; Congestion forecasting; load partitioning; convex hull algorithm; LMP forecasting; system patterns;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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