会议专题

Reactive Power Optimization Based on SA-NLWPSO algorithm

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 co-evolution 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.

reactive power optimization power loss Inertia Weight SA-NLWPSO

Chen Suang-Ye Ren Lei

Beijing University of Technology Electronic information and control engineering institute Beijing, China

国际会议

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics 第4届智能人机系统与控制论国际会议 IHMSC 2012

南昌

英文

101-105

2012-08-26(万方平台首次上网日期,不代表论文的发表时间)