摘要
基于免疫遗传算法,提出了一种抗体浓度新定义下的调节策略来求解电力系统无功优化问题:建立具有动态调整的罚因子的目标函数,在遗传操作中,引入人工免疫机制,并将各个抗体之间在编码上的相似性考虑进来,提出基于相似性矢量距的选择策略,以保存种群的多样性同时保证算法能够较快的收敛。通过IEEE30节点系统的仿真计算,并将本文算法与其它的算法进行了比较,结果表明该算法在计算速度和优化效果方面都具有明显的优势。
By integrating an immune genetic algorithm, a regulating strategy based on a new definition of antibody density for reactive power optimization in power system is proposed. Firstly, the penalty coefficient adjusted dynamically was applied to the objective function. Then artificial immunity mechanism is introduced into the genetic operation. It is similar to consider to be each antibody on encoding. And then based on similar vector distance choice tactics were proposed, which keep the population diversity. At the same time, it can guarantee algorithms faster convergence. Thus simple genetic algorithm was correspondingly improved. Finally, the proposed method is applied to IEEE30 buses test systems. The result of calculation illustrates that the proposed hybrid strategy is effective. It shows that compared with SGA in the same condition, this approach can reduce remarkably iterative times and improve rate of convergence of the algorithm for reactive power optimization.
出处
《电工技术学报》
EI
CSCD
北大核心
2008年第2期115-119,共5页
Transactions of China Electrotechnical Society
关键词
无功优化
遗传算法
免疫算法
相似性矢量距
Reactive power optimization, genetic algorithm, immune algorithm, similarity and vector distance
