S. Ganjefar, Morteza Tofighi
{"title":"Dynamic economic dispatch solution using an improved genetic algorithm with non‐stationary penalty functions","authors":"S. Ganjefar, Morteza Tofighi","doi":"10.1002/ETEP.520","DOIUrl":null,"url":null,"abstract":"This paper presents an improved genetic algorithm with non-stationary penalty functions (IGA-NSPF) to solve the dynamic economic dispatch (DED) problem of generating units while considering valve-point effects. The cost function of the generating units exhibits the non-convex characteristics, as the valve-point effects are modeled and imposed as rectified sinusoid components in the cost function. An improved evolution direction operator and gene swap operator are introduced in the proposed approach to improve the convergence characteristic of the genetic algorithm (GA). The non-stationary penalty functions (NSPF) are introduced to put more selective pressure on the GA to find a feasible solution, resulting in difficulty during solution searching. The non-stationary penalty is a function of the number of iterations that, in the proposed method, are based on a sigmoid function as the number of iteration increases so does the penalty. To illustrate the effectiveness of the proposed method, a dispatch case consisting of 10 units and 24 time intervals has been considered. Numerical results indicate that the performance of the IGA-NSPF presents the best results when compared with previous optimization methods in solving DED problems with the valve-point effect. Copyright © 2010 John Wiley & Sons, Ltd.","PeriodicalId":50474,"journal":{"name":"European Transactions on Electrical Power","volume":"21 1","pages":"1480-1492"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/ETEP.520","citationCount":"28","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Transactions on Electrical Power","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/ETEP.520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 28
基于非平稳惩罚函数的改进遗传算法求解动态经济调度
针对考虑阀点效应的机组动态经济调度问题,提出了一种改进的非平稳惩罚函数遗传算法(IGA-NSPF)。发电机组的成本函数表现出非凸特性,因为阀点效应被建模并作为成本函数中的整流正弦波分量施加。该方法引入了改进的进化方向算子和基因交换算子,提高了遗传算法的收敛性。引入非平稳惩罚函数(non-stationary penalty function, NSPF)对遗传算法施加更大的选择压力,使其难以找到可行解。非平稳惩罚是迭代次数的函数,在提出的方法中,迭代次数是基于s型函数的,随着迭代次数的增加,惩罚也会增加。为了说明所提方法的有效性,我们考虑了一个由10个单元和24个时间间隔组成的调度案例。数值结果表明,IGA-NSPF算法在求解具有阀点效应的DED问题时,与以往的优化方法相比,具有最佳的性能。版权所有©2010 John Wiley & Sons, Ltd
本文章由计算机程序翻译,如有差异,请以英文原文为准。