免疫算法及其在电力系统无功优化中的应用

提出一种用于电力系统无功优化的免疫算法(Immune Algorithm,IA).该算法是根据生物免疫原理提出的,与遗传算法相比,它具有抗原识别、记忆、抗体的抑制和促进等显著特点.IA将目标函数和约束条件比作抗原,将问题的解比作抗体.通过亲和度的计算来评价抗体并促进或抑制抗体的产生,减小了进化过程陷入局部最优解的可能性;通过抗原记忆,提高了局部搜索能力,加快了计算速度.将IA用于69节点实际电力系统的无功优化计算,并与传统遗传算法的计算结果进行了比较.结果表明IA能够以更快的速度得到最优解,其性能明显优于遗传算法.

IMMUNE ALGORITHM AND ITS APPLICATION IN POWER SYSTEM REACTIVE POWER OPTIMIZATION

An immune algorithm (IA) is proposed which can be applied to power system reactive power optimization. Comparing with the genetic algorithm, the proposed algorithm based on immune principle exists following salient features such as antigen recognition, memory mechanism, the boost or restriction of antibody generations, etc. In immune algorithm the objective function and the constraints are assimilated to the antigens and the solution of the problem is assimilated to the antibody. Through the calculation of affinity the antibody is evaluated and the the boost or restrain of its generation is determined, thus, the possibility of the evolutionary process falls into local optima is decreased. Through the memory mechanism the ability of local search is improved, therefore, the calculation is speeded up. The IA is used to the calculation of reactive power optimization in an actual 69-bus system and the calculation results by IA is compared with that by traditional genetic algorithm (GA), the comparison results show that the more optimal solution can be obtained by IA and the performance of IA is far better than that of GA.