A robust optimal scheduling method for active distribution network resources based on improved non inferior sorting genetic algorithm and game theory

To reduce power supply costs, minimize energy losses, and meet the requirements of active distribution network resource optimization scheduling, a robust optimization scheduling method for active distribution network resources based on improved Non Inferior Sorting Genetic Algorithm (NSGA-II) and game theory is proposed. A multi-objective model is established with the goal of minimizing the total expected cost and load variance of the main distribution grid, combined with constraints such as power flow equations and controllable distributed power output. Combine NSGA-II with Nash equilibrium theory to obtain a unique mean even for scheduling. Experiments have shown that this method can achieve robust optimization scheduling of the main network, stabilize voltage, and reduce losses and costs.