Reactive power optimization using second mutation genetic algorithm

By introducing fine individual pool and second mutation to adaptive genetic algorithm, a second mutation genetic algorithm is presented for the reactive power optimization and voltage control of power system. A fine individual pool with the same size as the group is established to store the detailed data of individual codes, fitness values, etc.. The individuals of each generation compete with the individuals in fine individual pool and the finer stays in pool. The next generation is produced from the fine individual pool. After genetic operation, the same individuals are picked out and mutated for the second time to produce adjacent differed individuals, thus avoiding repeated calculation, enhancing local search ability and speeding up the convergence. Both the proposed method and the adaptive genetic algorithm are applied to IEEE 30-bus system for comparison. Results show that, the average transmission loss optimized by the second mutation adaptive genetic algorithm is lower, with better optimization performance and smaller area of optimized transmission loss values.