{"title":"基于迁移和优序加载的约束经济调度微遗传算法","authors":"W. Ongsakul, J. Tippayachai","doi":"10.1109/DRPT.2000.855717","DOIUrl":null,"url":null,"abstract":"In this paper, a micro genetic algorithm based on migration and merit order loading solutions (MGAM-MOL) for solving the ramp rate constrained economic dispatch (ED) problems for combined cycle (CC) units with linear decreasing and staircase incremental cost (IC) functions is proposed. MGAM-MOL uses a merit order loading (MOL) solution as a base solution in order to reduce the micro genetic algorithm (MGA) search effort towards the optimal solution region. As transmission losses are included, the solutions are near the optimal solutions and are less expensive than those obtained from MGA, simple genetic algorithm (SGA), and MOLs especially for a large number of CC units, thereby leading to substantial fuel cost savings. Moreover, MGAM-MOL can easily facilitate the parallel implementation to reduce the computing expenses without sacrificing the quality of the solution.","PeriodicalId":127287,"journal":{"name":"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Constrained economic dispatch by micro genetic algorithm based on migration and merit order loading solutions\",\"authors\":\"W. Ongsakul, J. Tippayachai\",\"doi\":\"10.1109/DRPT.2000.855717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a micro genetic algorithm based on migration and merit order loading solutions (MGAM-MOL) for solving the ramp rate constrained economic dispatch (ED) problems for combined cycle (CC) units with linear decreasing and staircase incremental cost (IC) functions is proposed. MGAM-MOL uses a merit order loading (MOL) solution as a base solution in order to reduce the micro genetic algorithm (MGA) search effort towards the optimal solution region. As transmission losses are included, the solutions are near the optimal solutions and are less expensive than those obtained from MGA, simple genetic algorithm (SGA), and MOLs especially for a large number of CC units, thereby leading to substantial fuel cost savings. Moreover, MGAM-MOL can easily facilitate the parallel implementation to reduce the computing expenses without sacrificing the quality of the solution.\",\"PeriodicalId\":127287,\"journal\":{\"name\":\"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DRPT.2000.855717\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DRPT.2000.855717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
摘要
本文提出了一种基于迁移和优序加载解的微遗传算法,用于求解具有线性递减和阶梯增量成本函数的联合循环机组的斜坡率约束经济调度问题。为了减少微遗传算法(MGA)向最优解区域搜索的工作量,MGAM-MOL采用了一种优序加载(merit order loading, MOL)解作为基本解。考虑到传输损失,该方法接近于最优解,并且比MGA、简单遗传算法(SGA)和MOLs方法更便宜,特别是对于大量CC单元,从而大大节省了燃料成本。此外,MGAM-MOL可以很容易地促进并行实现,在不牺牲解决方案质量的情况下降低计算费用。
Constrained economic dispatch by micro genetic algorithm based on migration and merit order loading solutions
In this paper, a micro genetic algorithm based on migration and merit order loading solutions (MGAM-MOL) for solving the ramp rate constrained economic dispatch (ED) problems for combined cycle (CC) units with linear decreasing and staircase incremental cost (IC) functions is proposed. MGAM-MOL uses a merit order loading (MOL) solution as a base solution in order to reduce the micro genetic algorithm (MGA) search effort towards the optimal solution region. As transmission losses are included, the solutions are near the optimal solutions and are less expensive than those obtained from MGA, simple genetic algorithm (SGA), and MOLs especially for a large number of CC units, thereby leading to substantial fuel cost savings. Moreover, MGAM-MOL can easily facilitate the parallel implementation to reduce the computing expenses without sacrificing the quality of the solution.