Information Gap Decision Theory-Based Risk-Constrained Bidding Strategy of Price-Taker GenCo in Joint Energy and Reserve Markets

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This paper presents an optimal bidding strategy for price-taker generation companies (GenCos), which participate in a day-ahead joint energy and reserve market. Moreover, this problem is formulated as a Mixed-Integer Quadratic Constrained Program (MIQCP) to maximize the profit. Also, the price uncertainties of energy and reserve markets prices have direct impacts on the expected profit and bidding curves. This optimization problem is modeled with utilization of information gap decision theory (IGDT) for optimizing robustness to failure—or opportunity to windfall—under uncertainty conditions. IGDT assesses the robustness/opportunity of bidding strategy in the face of price uncertainties to determine whether a decision is risk-averse or risk-taking. Correlations among the prices of energy and reserve markets are properly modeled based on the concept of weighted average squared error using a variance–covariance matrix. It is shown that the risk-averse decisions, as well as risk-taking decisions, will affect both expected profit and bidding curves. The proposed method is verified in simulation studies on a GenCo comprising 5-unit thermal that participates in a day-ahead joint energy and reserve markets. Also, the proposed model is applied to a 54-unit thermal GenCo of IEEE-118 bus to validate the computational effectiveness of the proposed model in large system.