Short-Term Congestion Forecasting in Wholesale Power Markets
Qun Zhou,
Leigh Tesfatsion () and
Chen-Ching Liu
Staff General Research Papers Archive from Iowa State University, Department of Economics
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.
Keywords: wholesale power market; locational marginal price; Congestion forecasting; load partitioning; convex hull algorithm; LMP forecasting; system patterns (search for similar items in EconPapers)
JEL-codes: C1 C53 C6 D4 L1 Q4 (search for similar items in EconPapers)
Date: 2010-07-19
New Economics Papers: this item is included in nep-ene and nep-for
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Published in IEEE Transactions on Power Systems, November 2011, vol. 26 no. 4, pp. 2185-2196
Downloads: (external link)
http://www2.econ.iastate.edu/papers/p11700-2010-07-19.pdf (application/pdf)
http://www2.econ.iastate.edu/tesfatsi/CongestionForecasting.ZTL.pdf (application/pdf)
Related works:
Working Paper: Short-term congestion forecasting in wholesale power markets (2011) 
Working Paper: Short-term congestion forecasting in wholesale power markets (2011) 
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Persistent link: https://EconPapers.repec.org/RePEc:isu:genres:31700
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