The scheduling of microgrid entails multiple source and load factors,and has a relatively high difficulty.Aiming at promoting microgrid scheduling,the present work made an attempt at establishing optimization strategy of each supply system of a microgrid and improving charging willingness of EV users by employing time-differential pricing.The intro-duction of mutation strategy and migration strategy to the conventional particle swarm optimization algorithm brought a-bout improved optimization ability,and the full consideration of diversity of particle population effectively ensured the model's ability of solving optimization objectives.Furthermore,an optimization model with multiple objectives,including operation cost,user satisfaction,and EV user expenditure,was established and solved by migration mutation particle swarm algorithm.The proposed method was indicated effective in improving user satisfaction,as it achieved obvious re-ductions in both system operation cost(from 2563000 Yuan to 2258000 Yuan)and EV user expenditure(from 32500 Yuan to 21300 Yuan).Compared with the previously proposed algorithms,this algorithm is superior in optimization effi-ciency and utility,and may become a potential solution for similar problems.
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