Grid Connection Planning of Distributed Photovoltaic Based on Improved Multi-Objective Particle Swarm Optimization Algorithm
Considering the temporal characteristics of distribution network load and photovoltaic output,a siting and sizing model for distributed photovoltaic based on the standard deviation of voltage active power sensitivity is proposed.The proposed method determines a set of candidate nodes for distributed photovoltaic based on the time series of voltage active power sensitivity.The objective function,which includes investment cost,active power loss and voltage deviation,is solved by the modified multi-objective particle swarm optimization algorithm(IMOPSO).The algorithm guides the value of inertia weight based on the euclidean distance of fitness value between particles and the global optimal particle,to improve the global search capability of algorithms.Update the Pareto solution set through the density of particles,introduce the maxmin function to guide the selection of the global optimal value,and ensure the uniformity and global distribution of the Pareto solution set.To avoid the subjectivity of decision-makers,the method of maximizing fuzzy satisfaction is adopted to determine the optimal access plan.Finally,simulation verification is conducted based on the IEEE-33 node distribution system,and the results show the effectiveness and superiority of this method in solving the distributed photovoltaic siting and sizing determination problem.
distributed photovoltaicsiting and sizingmulti-objective particle swarm optimization algorithmtime series of voltage active power sensitivity
万方数据
维普
