基于免疫算法的多目标无功优化

Multi-objective Reactive Power Optimization Based on Immune Algorithm

在详细分析无功优化约束条件和目标函数以及研究无功优化免疫算法中抗体产生及其编码和解码的基础上,针对目前无功优化目标函数大多是基于权重系数基础多目标函数的组合,提出了基于免疫算法的多目标无功优化算法, 即用整体亲和力和部分亲和力概念来表示抗体对抗原的亲和程度,然后通过分别计算抗体的局部和整体亲和力来对抗体进行排序,依据此顺序选择抗体进行克隆、交叉变异等操作,并反复进行以求取系统无功优化的Pareto解集。对 IEEE14节点系统和IEEE118节点系统进行了多次无功优化计算,结果表明了该算法的有效性。

To avoid the optimal algorithm shortcoming based on the weight value, this paper presents a new multi-objective reactive power optimization algorithm based on Immune Algorithm which is a new heuristic algorithm whose objective are maximization of voltage stability margin and minimization of active power loss and bias voltage. Not only the constraint conditions and the multi-objective functional mathematical model are analyzed, but also the antibody generation and its encoding and decoding are studied. The global affinity and the partly affinity are defined to express the affinity degree of the antibody to the antigen, this algorithm can obtain the Pareto optimal solutions through the antibodies clone, crossover and mutation according to their global affinity. The proposed algorithm is tested in the IEEE 14-bus system and IEEE 118-bus system and compared with the other optimization algorithm, the results demonstrate that the new algorithm is a feasible and effective way to solve the reactive power optimization problem.