The economic and environmental protection is set as optimization objectives of microgrid optimal scheduling in order to promote their collaborative optimization. In the algorithm

traditional MOPSO adopts the crowding distance method to find an optimum position

which presents satisfactory local property but poor global property. To enhance global search capability of the algorithm

FMOPSO is proposed by introducing a fuzzy similarity matrix method into MOPSO. In order to combine the advantages of the two algorithms

an improved MOPSO called Hybrid Strategy MOPSO（HSMOPSO） is put forward. Then

a typical European microgrid is set as the object of optimal scheduling. The results show that the non-dominated solutions obtained from HSMOPSO algorithm are closer to the true Pareto-optimal fronts and also distributed widely and evenly and maintained with good diversity. After the introduction of energy storage technology in microgrid

the optimization results can be closer to the origin of the coordinates

thus achieving the improvement of Pareto. Consequently

it can be concluded that the proposed algorithm has both satisfactory local and global search capability. In addition

it is also verified that the introduction of energy storage technology can significantly promote the collaborative optimization of economic and environment in microgrid.