摘要
应用一种新型的遗传算法——基于免疫原理的改进遗传算法设计了统一潮流控制器,以提高多机电力系统的稳定性。本文所应用的免疫遗传算法利用免疫遗传学基本思想和理论,模拟生物体的免疫系统及其行为,如二次免疫应答,免疫记忆、免疫选择、浓度控制、新陈代谢等过程。与传统遗传算法的区别在于,本算法除了采用基因重组和基因变异思想外,还引入了隔离小生境技术和混沌增殖思想,使得所提出的算法更加接近实际免疫行为。对许多经典函数的优化结果表明,所提出的免疫遗传算法比普通遗传算法具有更强的全局优化能力。将该算法应用到新英格兰系统中统一潮流控制器的优化设计中,时域仿真结果表明,基于免疫遗传算法设计的统一潮流控制器能有效阻尼系统的低频振荡,提高电力系统的稳定性。
A novel optimization algorithm--immune genetic algorithm （IGA） is proposed to design an Unified Power Flow Controller （UPFC） for improing the stability of multi-machine power systems. The proposed IGA is based on immune genetic theory of creature and can simulate the immune system and its behavior of organism, such as second-time immune response, immune memory, immune selection, concentration control and metabolism. Compared with common genetic algorithms, the proposed IGA adopts the following techniques to improve the global searching ability and converge speed： gene recombination, gene mutation, isolated niche and chaos production. Several typical functions are used to verify the excellent performance of IGA. Finally, IGA is applied to optimize the parameters of UPFC to improve the stability of the New England Test Power System （NETPS）. Numerical simulation results demonstrate the validity of the optimized UPFC controller.
出处
《电工技术学报》
EI
CSCD
北大核心
2006年第7期60-68,74,共10页
Transactions of China Electrotechnical Society
基金
国家自然科学基金资助项目(50507018)
