摘要
通过对人类社会文化知识演变过程的研究,将一种新的智能优化算法———文化算法(Cultural Algorithms,CA)应用到电力系统无功优化中。该算法是一个多进化过程的演化算法,它通过模拟微观(群体)与宏观(信仰知识)层面的相互进化,最终形成"双演化双促进"的机制。简要介绍了其生物演变过程,详细描述了算法的机理,并结合进化规划的算法步骤,以网损最小为目标,建立了电力系统无功优化数学模型。通过对IEEE30标准系统节点进行测试,与改进遗传算法(SGA)和改进粒子群算法(CPSO)比较,得到了比较理想的结果,从而表明文化算法是一个值得进一步深入研究的方向。
It is a traditional reactive power optimization method that proceeds to make of power system with the target to minimize the power loss. Based on the research on the evolving process of human social culture and knowledge, the Culture Algorithm （CA） is proposed, and it is a new intelligent optimization algorithm of multi-evolving processes. A mechanism for double evolving and promoting is formed through simulating the mutual evolvements between microcolony and macro-belief. The explanation of CA in biology is introduced briefly, then a detailed show is given on the basic principium of CA and its every step combined with the Evolution Programming. This proposed algorithm is applied to the IEEE 30-bus system whose mathematic model is built and the optimizing result with CA is acceptable. Compared with those results of using SGA and CPSO algorithm, it is shown that CA is a valuable research direction.
出处
《现代电力》
2008年第3期36-41,共6页
Modern Electric Power
关键词
文化算法
无功优化
电力系统
进化算法
遗传
算法
culture algorithm
reactive power optimization
power system
evolvement algorithm
genetic algorithm
