首页> 外文会议>International Association of Science and Technology for Development International Conference on Modelling, Simulation and Identification >UNIT COMMITMENT WITH AN EFFICIENT FORMULATION AND ALGORITHM BASED ON IDENTIFICATION METHOD FOR VALID OPTIMIZING SPACE
【24h】

UNIT COMMITMENT WITH AN EFFICIENT FORMULATION AND ALGORITHM BASED ON IDENTIFICATION METHOD FOR VALID OPTIMIZING SPACE

机译:基于识别方法的有效优化空间识别方法的高效配方和算法的单位承诺

获取原文

摘要

Unit Commitment is one of the most important issues in power system operation, and solving this problem with mature optimizing algorithms has been the general trend now. However, too many integers which are needed to be branched are the biggest trouble to obtain the optimal solution in limited time. Different from most of the published papers, which mainly focused on the improvement of a certain optimizing algorithm, a novel notion of optimizing space of unit commitment and its scientific identification method are proposed in this paper from the perspective of model optimization. Based on the analysis on both units and binary variables of each time interval, this method can identify the invalid integer variables which need not to be branched, and turn them into continuous variables. Besides, in response to the failure of the traditional formulation of mixed integer linear programming, a novel one based on the valid optimizing space is proposed. Based on the work in this paper, the optimizing range is narrowed efficiently, and the calculating efficiency is improved greatly, under the premise of guaranteeing feasibility and optimality of original problem. The effectiveness of this method is demonstrated by the theoretical analysis and numerical experiments.
机译:单位承诺是电力系统运行中最重要的问题之一,并解决了成熟优化算法的这个问题现在是现在的一般趋势。然而,需要分支需要的整数是在有限时间内获得最佳解决方案的最大麻烦。与大多数公布的论文不同,主要专注于改进一定的优化算法,从模型优化的角度提出了一种优化单位承诺空间的新颖概念及其科学识别方法。基于每个时间间隔的两个单位和二进制变量的分析,此方法可以识别不需要分支的无效整数变量,并将它们转换为连续变量。此外,响应于混合整数线性规划的传统配方的故障,提出了一种基于有效优化空间的新颖。在本文的工作基础上,优化范围有效缩小,计算效率大大提高,在保证可行性和原始问题的最优性的前提下。通过理论分析和数值实验证明了该方法的有效性。

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