基于改进微分进化算法的电力系统无功优化

提出了一种改进的微分进化算法求解电力系统无功优化问题。在进化过程中，该算法根据进化情况采用动态参数调整机制提高算法的搜索效率，并且对种群重叠状况进行实时监视，对重叠个体利用混沌搜索策略来进一步提高算法的全局寻优能力。通过对IEEE 6、IEEE 30、IEEE 118标准测试系统及某地区实际系统的无功优化问题计算及结果分析表明，文中提出的改进微分进化算法高效、且全局寻优能力强。

Power System Reactive Power Optimization Based on Improved Differential Evolution Algorithm

An improved differential evolution (IDE) algorithm is proposed to solve power system reactive power optimization. During the evolution, according to evolution condition in the proposed algorithm the dynamic parameter adjustment mechanism is adopted to enhance its search efficiency; the population overlap is monitored in real-time mode; for overlapped individual, by use of chaotic search strategy the global optimal searching ability of the proposed algorithm is further improved. By means of reactive power optimization of IEEE 6-bus, IEEE 30-bus and IEEE 118-bus standard testing systems as well as that of a practical power system in a certain region, the results of calculation and analyses show that the proposed algorithm is efficient and possesses strong global optimal searching ability.