有限元结合粒子群和微分进化算法应用于电缆电场优化

Applying Particle Swarm and Differential Evolution Algorithm Combined with Finite Element to Optimize Electric Field of Cable

粒子群算法和微分进化算法是一类模拟自然界生物、生态系统等优胜劣汰行为的仿生智能算法,作为启发式随机算法,具有自适应、自组织、自学习等特点,能够解决传统计算方法难于求解的各类复杂问题。研究基于商业有限元软件平台,对单相和三相同轴电缆进行参数化编程,将有限元计算与粒子群算法和微分进化算法相结合,实现对电缆内部绝缘层最大电场强度的优化计算。这为有限元结合仿生智能算法应用于高压设备电磁场优化设计提供借鉴和启示。

Particle swarm optimization（PSO）and differential evolution（DE）algorithm are biologically inspired computing,which simulate the behavior of survival of the fittest from the systems nature biology,ecology,etc.As heuristic random algorithms,they have characteristics of self-adaptation,self-organization,self-learning,etc.PSO and DE algorithm can be used to solve various complex problems,which are difficult by using traditional calculation method.Base on the platform of commercial finite element soft,parametric programming of single-phase and three-phase coaxial cable is finished in the research.Optimization calculation of maximum electric field strength of insulating layer within cable is realized by finite element method combined with PSO and DE algorithm.That finite element method combined with biologically inspired computing provides reference and enlightenment for optimizing high voltage equipment in aspects of electromagnetic field.