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Sayyad Nojavan

Sayyad Nojavan

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex: 0/00
Faculty: Faculty of Engineering
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Phone: 09148903379

Research

Title
Optimal bidding strategy of generation station in power market using information gap decision theory (IGDT)
Type
JournalPaper
Keywords
Optimal bidding strategy Information gap decision theory (IGDT) Uncertainty
Year
2013
Journal ELECTRIC POWER SYSTEMS RESEARCH
DOI
Researchers Sayyad Nojavan ، Kazem Zare ، Mohammadreza Feyzi

Abstract

This paper considers a profit-maximizing thermal unit producer that participates in a day-ahead market. The producer behaves as a price-taker in the day-ahead electricity market. This paper provides the information gap decision theory for determining the optimal bidding strategies for the day-ahead market. While making bidding strategy, factors such as characteristics of the generator and market price uncertainty need to be considered as they have direct impact on the expected profit and bidding curve. In this paper, a method of building an optimal bidding strategy is presented under market price uncertainty using information gap decision theory (IGDT). Information gap decision theory is a non-probabilistic decision theory that seeks to optimize robustness to failure – or opportunity to windfall – under severe uncertainty. It is shown that risk-aversion and risk-taker may influence the expected profit and bidding curve of a producer. The proposed method is illustrated through a realistic case study.