Wind-solar-storage combined system optimization method based on multi-target grey wolf algorithm

The invention requests to protect a wind-solar-storage combined system optimization scheduling method based on an improved multi-objective grey wolf algorithm, and the method comprises the steps: taking the minimum economic cost, the minimum grid-connected power difference and the maximum carbon emission reduction as optimization objectives, and improving the multi-objective grey wolf optimization algorithm through introducing Tent chaotic mapping, a nonlinear convergence factor and a dynamic weight. And the improved multi-target grey wolf optimization algorithm is used to research the scheduling optimization of the wind-solar-storage combined system, so that the utilization rate of renewable energy sources is improved, the quality of a grid-connected power grid is improved, the random fluctuation of wind power and photovoltaic output is stabilized, and the wind-solar-storage complementary system outputs a relatively smooth supply curve so as to enhance the stability of the power grid. In addition, the method