中文摘要：

采用蜜蜂进化机制与遗传算法相结合的蜜蜂进化型遗传算法（beeevolutionarygeneticalgo—rithm，BEGA）对电力系统进行无功优化计算．该算法以一定概率将蜂王（最优个体）与雄蜂（被选的个体）2部分进行交叉，因此对最优个体包含信息的开采能力得以增强．随机种群的引入，降低了算法出现过早收敛的可能性，保持了种群多样性．应用BEGA对IEEE6节点系统进行无功优化计算的结果表明：较其他算法，BEGA具有更强的全局寻优能力和更快的收敛速度．

英文摘要：

A method based on bee evolution modifying genetic algorithm（BEGA）is presented for power system reactive power optimization. In this algorithm, the best chromosome called queen-bee among the current population is crossover with drones selected according to a certain crossover probability, which en- hances the exploitation of searching global optimum. In order to avoid premature convergence, BEGA intro- duces a random population that extends search area. Consequentially it keeps the diversity of population. The presented method has been tested in IEEE6 bus systems, compared with other algorithms, the results show that. the ability of overall searching optimal solution is better and convergence speed is higher.