Optimal configuration of distributed photovoltaic generation based on improved multi-objective swarm optimization algorithm
Aiming at the problems such as voltage quality reduction and power inversion,etc,caused by unreasonable distributed photovoltaic generation location and capacity,a multi-objective location and capacity model for distribu-ted network is proposed,which takes into consideration least network loss,least voltage deviation,lowest investment cost and solar radiation.An improved multi-objective particle swarm optimization algorithm(IMOPSO)is proposed to solve the model.The algorithm uses nonlinear inertia weight and learning factor to improve the convergence accu-racy of the algorithm,and the premature disturbance factor is introduced to enhance the ability of the algorithm to es-cape the local optimization,then a crowding distance update strategy is adopted to ensure the uniformity and diversity of Pareto front distribution.Benchmark functions are used to verify the superiority of the IMOSPSO.Finally,the simu-lation based on the IEEE-69 distribution network is implemented.The results prove that the model can effectively deploy distributed PV in areas with rich solar irradiance resources while taking into account the economic and securi-ty requirements of the distribution network.
distributed photovoltaic generationlocation and capacitymulti-objective particle swarm optimization algorithmdistributed network
NETL
NSTL
万方数据
维普
