Optimal bidding strategy for GENCOs based on parametric linear programming considering incomplete information

Feng Gao, Gerald B. Sheble, Kory Hedman, Chien Ning Yu

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Electric energy market participants face risks and uncertainties associated with the ever-changing market environment. A profit-driven bidding decision tool is thus crucial for generation companies (GENCOs) to maintain a competitive position. Although optimal bidding strategies have been extensively studied in the literature, most previous research assumes continuous and differentiable generation offer curves, whereas actual offer curves are piecewise staircase curves. Based on the foregoing, this paper presents an optimal bidding strategy for GENCOs, derived by using parametric linear programming, and extends the proposed method to consider incomplete information. We show that the proposed algorithm is able to utilize the characteristics of piecewise staircase energy offer curves in contrast to the findings of previous researchers.

Original languageEnglish (US)
Pages (from-to)272-279
Number of pages8
JournalInternational Journal of Electrical Power and Energy Systems
Volume66
DOIs
StatePublished - Mar 2015

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Keywords

  • Bidding strategy
  • Decision analysis
  • Incomplete information
  • Non-convex optimization
  • Parametric linear programming

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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