Abstract: The economic dispatch of traditional power systems mainly revolves around centralized power sources, which makes it difficult to cope with the randomness and intermittency of output after the integration of distributed energy sources, resulting in significant deviations between dispatch results and actual operating conditions. To this end, research is being conducted on new economic dispatch optimization methods for power systems that consider distributed energy access. Firstly, construct an economic dispatch model that considers the characteristics of distributed energy, design a multi-objective function that includes power generation costs and pollutant emissions, and set constraints such as power balance, distributed energy output, and safe operation of the power grid; using intelligent optimization algorithms to optimize and solve the model, continuously iterating to search for the optimal scheduling solution. The experimental results show that after applying the proposed scheduling optimization method, the total scheduling cost of the new power system has been reduced by 53.1% compared to the benchmark. The average emissions under six operating conditions are significantly lower than traditional methods, with the highest not exceeding 800 kg, achieving the goal of synergistic optimization of power generation cost and pollutant emissions.