改进灾变遗传算法及其在无功优化中的应用

针对灾变遗传算法的早熟和稳定性问题,提出了一种改进灾变遗传算法,设计了与进化代数相关的改进灾变算子;为了兼顾算法的全局性能和收敛速度,设计了与进化代数相关的交叉概率和与个体适应度相关的变异概率.IEEE14节点和IEEE30节点无功优化算例表明,该改进算法具有良好的全局性能和收敛速度,适合求解电力系统的无功优化问题.

Improved Catastrophic Genetic Algorithm and Its Application to Reactive Power Optimization

To overcome the conflict of the instability with the global astringency on Catastrophic Genetic Algorithms (CGA), a new Improved Catastrophic Genetic Algorithm (ICGA) is proposed in this paper. In the ICGA, an improved catastrophic model depending on the number of generations is designed. Others, it is designed a new probability algorithm of crossover depending on the number of generations, and a new probability algorithm of mutation depending on the fitness value. By this way, the convergence performance is greatly enhanced. ICGA is used in power system reactive power optimization, and the calculation example on IEEE14 and IEEE30 shows that the ICGA has good stable searching capacity and convergence speed.