Multi-objective reactive power co-optimization based on the MOPSO algorithm considering wind power integration

Abstract

Abstract With the proposal of the “double carbon” policy, the installed capacity of new energy wind power is further expanded. Focusing on the uncertainty of a high proportion of wind power output, wind power integration will aggravate power quality problems such as active network losses; however, it is effective in improving system network losses that optimize reactive power. Therefore, this study adopts a multi-objective reactive power optimization method, which regards minimum network losses and node voltage deviation as objective function. Unlike the traditional sensitivity analysis method, the reactive power margin method selects the nodes to be compensated, this study adopts multi-objective particle swarm optimization (MOPSO) to resolve the practical problem in the IEEE33 node system. The results show that the nodes selected can play a better role in reactive power compensation aspect. The network losses and voltage deviation of the wind power distribution system can be significantly reduced by comparing the algorithm pre and post of optimization.