An energy storage configuration method for new energy power station suitable for consumption and active support scenarios
New energy power stations,while balancing the promotion of consumption and active support of scenario demand configuration for energy storage,will face problems such as random and complex appearances in different scenarios,cross coupling in time series,long solving time of traditional multi-objective optimization algorithms,slow convergence speed,and susceptibility to getting stuck in local solutions.Based on this,this article proposes a new energy storage configuration method suitable for multiple scenarios in new energy power plants.Based on the output data of new energy power stations,daily power prediction data,grid frequency data,etc.,typical operating condition curves of energy storage demand are extracted,and an energy storage optimization configuration model is constructed.An improved multi-objective particle swarm optimization algorithm is proposed to solve the optimal energy storage configuration of new energy power stations.Finally,simulation analysis was conducted on actual new energy power plants to verify the effectiveness and practicality of the method proposed in this paper.
energy storage configurationmulti objective optimizationparticle swarm optimization algorithmnew energy consumptionactive support
万方数据
维普
