Document Type

Working Paper

Publication Date


Working Paper Number

WP #10025, July 2010 revised January 2011


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.

Publication Status

Published in IEEE Transactions on Power Systems, Vol. 26 no. 4 (November 2011): 2185-2196.

JEL Classification

C1, C53, C6, D4, L1, Q4

File Format



14 pages

File Function

Latest revision: 20 January 2011 (Original version: July 2010)

Included in

Economics Commons