Economic Capacity Allocation of Grid-connected Microgrid Based on Improved Hybrid Genetic Algorithm

Abstract

For the wind and solar diesel storage grid-connected microgrid, in order to meet the minimum investment cost of the microgrid at the initial stage and have certain economic benefits. The objective function of this paper is the annual average economic cost, the number of each micro-power source is used as the optimization variable, the constraints of micro-grid operation are considered, the capacity optimization configuration model of grid-connected micro-grid is established, and then the improved genetic algorithm can be used to solve this problem. Finally, the annual average economic cost, the utilization rate of new energy and the redundancy rate are used as evaluation indicators. By comparing the configuration results of genetic algorithm, wolf pack algorithm and mixed wolf pack genetic algorithm, the capacity allocation scheme of microgrid under economic indicators is obtained.

Research on capacity optimization of grid-connected microgrid

“…The output power of the photovoltaic power generation system in the microgrid is closely related to the solar radiation intensity and the temperature of the photovoltaic panel surface, so the influence of both on the output power of the photovoltaic system should be considered in the establishment of the output model of the photovoltaic system. In practical engineering research, to facilitate calculation, photovoltaic unit output model can be simplified as [6]:…”