A Multi-Participant Benefit Maximization Model and Strategy Optimization in Market Transactions Incorporating Game Theory

This topic discusses the problem of maximizing the interests of multiple participants in the trading market based on game theory.Taking the electric power market as a study case, an interest maximization model of multi-party trading strategy in the electric power market is constructed, and the ADMM algorithm is used to solve the model.The rationality and effectiveness of the described model are verified through experimental analysis and arithmetic simulation.Compared with other algorithms, the ADMM algorithm in this paper has a faster convergence speed, and the benefits of the grid company, the benefits of the new entities and the benefits of the users under different numbers of users are all closest to the ideal Nash equilibrium state, which shows the superiority of the ADMM algorithm in this paper.The constructed model is used to solve the conflict of interests among the grid company, new entities and users, and the existence and uniqueness of the game equilibrium is proved through analysis and derivation, and has good convergence results.After the optimization of the strategy in this paper, the revenue of the added entity increases by 6.76%, the power purchase cost of the users decreases by 10.29%, and the consumption surplus increases by 4.50%.Through price-guided output, the load curve is realized to shift peaks and fill valleys, so that the grid company, the added entities and the users get higher benefits.