Particle swarm optimization algorithm was applied to reduce power loss and to prevent the decline of the power supply quality caused by the imbalance of reactive power, but reactive power optimization is a mixed non-linear programming problem with lots of variables and uncertain parameters, PSO algorithm also has some limitations such as premature convergence, which causes the bad accuracy of convergence. And then the coevolution of Particle Swarm Optimization (PSO) with nonlinear inertia weight factor (w) and Simulated Annealing algorithm (SA) is established to improve the original algorithm which is named as SA-NLWPSO. Compared with the algorithms such as PSO, SA-PSO and SA-WPSO, SA-NLWPSO is better for global convergence and higher accuracy of reactive power optimization by using IEEE-10 bus system as a model for the simulation.
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