本文针对某微电网运行模型，设计了考虑运行成本、排放成本、柔性负荷成本和碳交易机制成本的多目标函数，针对不同目标的组合方式，设计了微网运行的四种方案。仿真优化时，针对传统引力搜素算法进行了改进，为防止算法寻优过程中陷入局部最优，过早收敛，设计了多种群引力搜素算法。仿真结果表明，多种群引力搜素算法的优化结果明显优于遗传、粒子群和狼群等经典算法。此外，对四种方案的优化结果的比较，也说明了在微网系统中引入柔性负荷和碳交易机制，可有效提升微网运行的经济性。

This work focuses on the operation model of a microgrid, and designed a multi-objective function that considers operating costs, emission costs, flexible load costs, and carbon trading mechanism costs. Then, Four schemes for microgrid operation have been designed for different combinations of objectives. During simulation optimization, improvements were made to the traditional gravity search algorithm. To prevent the algorithm from falling into local optima and premature convergence during the optimization process, various swarm gravity search algorithms were designed. The simulation results show that the optimization results of the multi-population gravity search algorithm are significantly better than classical algorithms such as genetic algorithm, particle swarm optimization algorithm, and grey wolf optimization algorithm. In addition, the comparison of optimization results for the four scenaros also demonstrates that introducing flexible loads and carbon trading mechanisms in microgrid systems can effectively improve the economic efficiency of microgrid operation.

江苏省产学研合作项目（BY2022863）