摘要
差异进化算法(DE)是一种新的进化算法,近年来的研究和应用已经展示出很大的应用潜力,但其中的某些参数需通过试验确定,影响了实用性。提出一种自适应差异进化算法(FADE),能使算法的控制参数根据求解问题的不同在优化过程中自适应发生改变,并应用于无功优化问题。通过IEEE-30节点算例系统的仿真结果证明,与DE和GA算法相比,模糊差异进化算法具有很强的自适应性及通用性。
The Differential evolution （DE） algorithm is a new evolutionary computation method. It has been proved to be powerful but needs parameters predefined for a given problem by users. A fuzzy adaptive differential evolution （FADE） algorithm is proposed in this paper. It can adjust parameters automatically in optimization process to find the global optimum. The reactive power optimization of IEEE--30 power system has been tested. Simulation results of the proposed approach, compared with DE and GA algorithms, show that the FADE algorithm is more efficient in searching global optimization solution.
出处
《计算技术与自动化》
2009年第4期32-36,共5页
Computing Technology and Automation
关键词
差异进化
进化计算
无功优化
电力系统
differential evolution
evolutionary computation
reactive power optimization
power systems
