基于链式遗传-模拟退火混合算法的电网扩展规划  

A Chain Algorithm of Genetic-simulated Annealing Hybrid for Transmission Network Expansion Planning

作　　者：王淳[1] 龚娇龙[1] 李祥硕[1] 花宁[1] 

机构地区：[1]南昌大学信息工程学院,江西南昌330031

出　　处：《南昌大学学报（工科版）》2010年第3期277-280,286,共5页Journal of Nanchang University(Engineering & Technology)

基　　金：国家自然科学基金资助项目(50747025);江西省教育厅科学技术研究基金资助项目(200635);江西省自然科学基金资助项目(2009GZS0016)

摘　　要：将模拟退火机制引入到食物链生态进化算法,提出了链式遗传-模拟退火混合算法(CAGSAH),对种群执行并行退火操作,弥补食物链生态进化算法爬山能力不足,提高算法全局寻优能力。给出了链式遗传-模拟退火混合算法的详细计算流程,并将其应用到求解电网扩展规划问题,实际计算结果显示链式遗传-模拟退火混合算法在搜索效率及收敛性能上明显优于食物链生态进化算法。A simulated annealing（SA） is introduced to ecology evolutionary algorithm of food chain,and the chain algorithm of genetic-simulated annealing hybrid（CAGSAH） is proposed.Populations on the food chain were performed with parallel simulated annealing to strengthen the climbing ability and global search ability of EEAFC.The flow chart based on the chain algorithm of genetic-simulated annealing hybrid is showed,and the applications of the chain algorithm of genetic-simulated annealing hybrid in transmission network expansion planning（TNEP） indicate that the proposed method is of better convergence and higher retrieval efficiency than the ecology evolutionary algorithm of food chain.

关 键 词：全局优化 电网扩展规划 遗传算法 模拟退火算法 食物链生态进化算法 链式遗传-模拟退火混合算法 

分 类 号：TM714[电气工程—电力系统及自动化]