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 emi...
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creator | YU MIN DING BAOCANG HU CHEN ZHANG BO LIAO MENGTING LEI QIUYU DU MAOCHUN |
description | 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 |
format | Patent |
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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. 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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. 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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</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY GENERATION PHYSICS SYSTEMS FOR STORING ELECTRIC ENERGY |
title | Wind-solar-storage combined system optimization method based on multi-target grey wolf algorithm |
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