Inter-Provincial Power Spot Trading Strategy Based on Quantum Genetic Algorithm

The expansion of power market reforms has significantly increased the number and variety of market participants, complicating the game scenarios in the electricity spot market. The effectiveness of declaration strategies directly determines the participants’ returns in the market. However, existing research on strategy bidding treats power purchasers as passive price takers, neglecting the impact of their strategy bids on the market. This oversight fails to accurately reflect the competitive bidding environment among market participants. Therefore, this paper proposes a strategic bidding model based on dynamic games for all market participants. It uses a quantum genetic algorithm to optimize declaration strategies and generate strategic analysis samples. Subsequently, it constructs a market equilibrium point solving model based on spectral clustering and multi-party static games, aiming to provide a more realistic market game environment for participants.