Bidding Strategy of Thermal Power Plants in Carbon Electricity Market Based on Hybrid Quantum Particle Swarm Optimization Whale Algorithm

This paper proposed a bidding strategy for thermal power plants in the carbon electricity market environment. Firstly, the dual impact of the carbon market and the electricity market on thermal power units was considered to provide decision support for thermal power enterprises to formulate market bidding strategies and help thermal power plants achieve maximum efficiency in the dual market environment. At the same time, a bidding strategy optimization method based on hybrid quantum particle swarm optimization whale algorithm (HQPW) is used to solve the bidding strategy of thermal power plants. The research results can provide reference for improving the coordination mechanism between the carbon market and the electricity market, and optimizing the design of market rules and relevant policies. Case studies verify the effectiveness of the method proposed in the paper.