Supplier’s Strategic Bidding for Profit Maximization with Solar Power in a Day-Ahead Market

Abstract

The rapid globalization of solar-based technologies has enabled widespread utilization of solar energy. This has created a new prospect of operation in modern power system due to their dependency on environmental factors, which cause uncertain landscape in day-ahead power market. In real-time operations, compromises have been made in cost and power to balance the power which reduces suppliers’ benefits. Therefore, beta probability distribution function is used to handle the adverse impact of solar irradiation uncertainty and scenarios are reduced using forward-reduction algorithm. Moreover, to measure the deviation of solar power, underestimation and overestimation cost function are used. The paper proposes a suitable bidding strategy to maximize the suppliers’ benefit to handle uncertain rivals’ behavior and uncertainty of solar power. The formulated problem is solved by gravitational search algorithm and simulation results are obtained in absence and presence of solar power on IEEE standard 30-bus test system. The obtained result proves the suitability of the proposed bidding strategy in the presence of uncertainty of solar power.