电子学报2017，Vol.45Issue(1)：220-224,5.DOI:10.3969/j.issn.0372-2112.2017.01.030
类进化算法驱动的动态电力经济调度优化
Cluster Evolutionary Algorithm Driven Dynamic Economic Dispatch Optimization
摘要
Abstract
Dynamic economic dispatch (DED) is a multi-stage decision problem with space and time coupling.In order to get the global optimal solution,a DED problem generally has been transformed into a nigh-dimensional constrained numerical optimization problem to solve.In this study,a novel global optimization algorithm,cluster evolutionary algorithm (CEA),is proposed to solve DED problem.In CEA,a virtual cluster organization is constructed among individuals so as to dynamically adjust the searching process of simulated evolutionary system while improving the optimization efficiency of population.In simulations,CEA is applied to 2 DED testing systems for verifying its feasibility.Meanwhile,a comparative study is carried out with other existing methods.Results clarify the significance of the proposed algorithm and verify its performance.Considering the quality of the solution obtained,CEA seems to be a promising alternative approach for solving the DED problem.关键词
进化算法/类搜索机制/动态电力经济调度Key words
evolutionary algorithm/cluster searching mechanism/dynamic economic dispatch分类
信息技术与安全科学引用本文复制引用
陈皓,潘晓英..类进化算法驱动的动态电力经济调度优化[J].电子学报,2017,45(1):220-224,5.基金项目
国家自然科学基金(No.61203311,No.61105064) （No.61203311,No.61105064）
陕西省教育厅科研计划(No.2013JK1183,No.2014JK1667) （No.2013JK1183,No.2014JK1667）
厦门市科技计划(No.3502Z20141164) （No.3502Z20141164）
