Optimal bidding strategy of generation station in power market using information gap decision theory (IGDT)

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.

► A new model for optimal bidding strategy of generation companies is proposed based on IGDT.
► This methodology is not based on profit maximization; however, it results in a risk-averse and risk-taking issue.
► The generating company can maximize the robustness of its bidding strategy against low market prices.
► Also it can be gained from the opportunity of increasing the market prices.