细菌觅食差分粒子群算法的无功优化方法

电力系统无功优化是以网损最小化且保持良好电压水平为目的。提出了细菌觅食差分粒子群算法（DEBFO），并首次应用于电力系统无功优化问题。趋化操作的交叉算子可提高局部搜索能力，变异算子可加强全局搜索能力，繁殖操作使细菌寻优速度加快，迁徙操作避免了细菌早熟。Matlab仿真结果表明DEBFO具有较强的全局寻优能力，收敛速度快，鲁棒性好，能够更有效地解决电力系统无功优化问题。

Reactive power optimization based on bacterial foraging-DE -particle swarm optimization

Power system reactive power optimization is aiming at minimum network loss and keeping goodvoltage level. DEBFO is proposed in this paper and first applied in reactive power optimization. Inchemotaxis operation, the crossover operator can improve the local search ability and mutation operatorcan strengthen the global search ability. Breeding operation makes the speed of optimization faster. Themigration operation avoids premature. The simulation result of MATLAB show that DEBFO has strongerglobal optimal searching ability, faster convergence speed and better stability and can solve power systemreactive power optimization problem more effectively.