首页> 外文期刊>Electric power systems research >Parallel micro genetic algorithm based on merit order loading solutions for constrained dynamic economic dispatch
【24h】

Parallel micro genetic algorithm based on merit order loading solutions for constrained dynamic economic dispatch

机译:约束动态经济调度的基于绩效顺序加载解的并行微遗传算法

获取原文
获取原文并翻译 | 示例
           

摘要

This paper proposes a parallel micro genetic algorithm based on merit order loading solutions (PMGA-MOL) to solve constrained dynamic economic dispatch (DED) problems for combined cycle (CC) units with linear decreasing and decreasing staircase incremental cost (IC) functions. To minimize the synchronization overheads, the PMGA-MOL employs the load balancing and migration strategies among processors. This PMGA-MOL algorithm is implemented on the eight-processor scalable multicomputer implementation using low-cost equipment (SMILE) Beowulf cluster with a fast ethernet switch network on the generating unit system size in the range of 5-80 units over the entire dispatch periods.
机译:本文提出了一种基于绩效排序加载解决方案(PMGA-MOL)的并行微遗传算法,以解决带有线性递减和递减阶梯增量成本(IC)功能的联合循环(CC)机组的约束动态经济调度(DED)问题。为了最大程度地减少同步开销,PMGA-MOL在处理器之间采用了负载平衡和迁移策略。该PMGA-MOL算法在八处理器可扩展多计算机实施中实施,该实施使用低成本设备(SMILE)Beowulf集群,并在整个调度周期内,发电机组系统大小在5-80单位范围内,具有快速以太网交换网络。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号