摘要
介绍以目标函数为抗原,以问题解为抗体,利用进化策略进行群体更新的免疫遗传算法。讨论环境经济负荷调度多目标函数优化问题,给出利用免疫遗传算法解决这一问题的主要步骤。利用一个含有5个电力生产单元的燃煤电力系统模型验证了该算法的可行性和有效性。并与遗传算法和Hop fie ld神经网络进行比较分析,证实了该算法解决该类问题的优化性和快速收敛性。
This paper introduces a kind of immune genetic algorithm, which regards objective function as antigen, solution as antibody and updates the population using evolutionary strategy. After discussing economic emission load dispatch, which belongs to multi-objective constrained optimization problem, the main process of solving this problem by immune genetic algorithm is given. The feasibility and validity of this algorithm are proved by case study on a power system with five coal-burning generating units. The performance is compared with those of general genetic algorithm and Hopfield neural network. Fast convergence of this algorithm is proved.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2006年第1期98-103,共6页
Proceedings of the CSU-EPSA
基金
黑龙江省自然科学基金资助项目(F0210)
哈尔滨工程大学校基础研究基金资助项目(HEUF04076)
关键词
免疫遗传算法
环境经济负荷调度
电力系统
immune genetic algorithm （IGA）
economic emission load dispatch （EELD）
electric power system
