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首页> 外文期刊>Electric Power Components and Systems >Hybridization of Artificial Immune Systems and Sequential Quadratic Programming for Dynamic Economic Dispatch
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Hybridization of Artificial Immune Systems and Sequential Quadratic Programming for Dynamic Economic Dispatch

机译：动态经济调度的人工免疫系统与顺序二次规划的混合

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摘要

Dynamic economic dispatch deals with the scheduling of online generator outputs with predicted load demands over a certain period of time so as to operate an electric power system most economically. This article proposes a hybrid methodology integrating artificial immune systems with sequential quadratic programming for solving the dynamic economic dispatch problem of generating units considering valve-point effects. This hybrid method incorporates artificial immune systems as a base level search, which can give good direction to the optimal region and sequential quadratic programming as a local search procedure, which is used to fine tune that region for achieving the final solution. Numerical results of a ten-unit system have been presented to demonstrate the performance and applicability of the proposed algorithm. The results obtained from the proposed algorithm are compared with those obtained from a hybrid of particle swarm optimization and sequential quadratic programming and a hybrid of evolutionary programming and sequential quadratic programming.
机译：动态经济调度处理在一定时间段内具有预测负载需求的在线发电机输出的调度，从而最经济地运行电力系统。本文提出了一种混合方法，将人工免疫系统与顺序二次规划相结合，以解决考虑阀点效应的发电机组的动态经济调度问题。这种混合方法将人工免疫系统作为基础级搜索，可以为最佳区域提供良好的指导，并可以将顺序二次规划作为本地搜索程序，从而可以对该区域进行微调以实现最终解决方案。提出了一个十单元系统的数值结果，以证明该算法的性能和适用性。从提出的算法获得的结果与从粒子群优化和顺序二次规划的混合以及进化规划和顺序二次规划的混合获得的结果进行了比较。

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