Title

Short-term congestion forecasting in wholesale power markets

Campus Units

Economics, Electrical and Computer Engineering

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2011

Journal or Book Title

IEEE Transactions on Power Systems

Volume

26

Issue

4

First Page or Article ID Number

2185

Last Page

2196

DOI

10.1109/TPWRS.2011.2123118

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.

JEL Classification

C1, C53, C6, D4, L1, Q4

Comments

This is a working paper of an article published in IEEE Transactions on Power Systems, Vol. 26 no. 4 (November 2011): 2185-2196.