Short-Term Congestion Forecasting in Wholesale Power Markets
AbstractShort-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 patternsâ€”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.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 31700.
Date of creation: 19 Jul 2010
Date of revision:
Publication status: Published in IEEE Transactions on Power Systems, November 2011, vol. 26 no. 4, pp. 2185-2196
Contact details of provider:
Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
Phone: +1 515.294.6741
Fax: +1 515.294.0221
Web page: http://www.econ.iastate.edu
More information through EDIRC
wholesale power market; locational marginal price; Congestion forecasting; load partitioning; convex hull algorithm; LMP forecasting; system patterns;
Find related papers by 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 and Pricing
- L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
- Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-07-31 (All new papers)
- NEP-ENE-2010-07-31 (Energy Economics)
- NEP-FOR-2010-07-31 (Forecasting)
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