首页> 外文期刊>Electric power systems research >A comparative analysis of different dual problems in the Lagrangian Relaxation context for solving the Hydro Unit Commitment problem
【24h】

A comparative analysis of different dual problems in the Lagrangian Relaxation context for solving the Hydro Unit Commitment problem

机译:拉格朗日松弛环境中解决水电机组承诺问题的不同对偶问题的比较分析

获取原文
获取原文并翻译 | 示例
           

摘要

One of the most attractive methods to solve large-scale combinatorial optimization problems is the Lagrangian Relaxation (LR). The LR can be seen as a broad range of techniques which supplies a lower bound of the objective function and good starting points for heuristic searches to obtain feasible primal solutions. In this paper, we are interested in one of the most intriguing questions related to LR which is the construction of the dual problem. To accomplish this task, we use the Hydro Unit Commitment and Loading (HUCL) problem. Two reasons justify the choice: (ⅰ) it is a large-scale nonlinear 0-1 programming problem; (ⅱ) the problem is highly relevant to use the energy resources in an electrical energy system efficiently. By means of the HUCL, we apply different kinds of decompositions, in the LR context, to construct two distinct dual problems. The analyses are strictly based on numerical experiments and the ideas here presented are intended to encourage researchers in the optimization community to explore LR dualization in other practical and relevant problems.
机译:拉格朗日松弛(LR)是解决大规模组合优化问题的最有吸引力的方法之一。 LR可以看作是广泛的技术,它们提供了目标函数的下限和启发式搜索以获得可行的原始解的良好起点。在本文中,我们对与LR有关的最引人入胜的问题之一感兴趣,即对偶问题的构造。为了完成此任务,我们使用了水电机组的承诺和负荷(HUCL)问题。有两个理由证明了选择的正确性:(ⅰ)这是一个大规模的非线性0-1编程问题; (ⅱ)该问题与有效利用电能系统中的能源高度相关。通过HUCL,我们在LR上下文中应用了不同种类的分解来构造两个不同的对偶问题。这些分析严格基于数值实验,此处提出的想法旨在鼓励优化社区的研究人员在其他实际和相关问题中探索LR对偶。

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