...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability >Design allocation of multistate series-parallel systems for power systems planning: a multiple objective evolutionary approach
【24h】

Design allocation of multistate series-parallel systems for power systems planning: a multiple objective evolutionary approach

机译：电力系统规划中多状态串并联系统的设计分配：多目标进化方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents an extension and application of a recent developed multiple objective evolutionary algorithm to solve design allocation problems commonly found in the power systems area. The evolutionary algorithm introduced is called MOMS-GA, a multiobjective genetic algorithm developed to solve multistate design allocation problems. MOMS-GA works under the assumption that both the system and its components can experience more than two possible states of performance. MOMS-GA uses the universal moment generating function (UMGF) approach to evaluate the different reliability indices of the system. Therefore, system availability is represented by a multistate availability function which extends the traditional binary state availability. Three different design allocation problems commonly found in power systems planning are solved to show the performance of the algorithm. The multiobjective formulation considered in the first two examples corresponds to the maximization of system availability, minimization of system investment cost, and maximization of expected system capacity. In the third example the multiobjective formulation seeks to maximize system availability, minimize system investment cost, and minimize expected unsupplied demand.
机译：本文介绍了最近开发的多目标进化算法的扩展和应用，以解决电力系统领域中常见的设计分配问题。引入的进化算法称为MOMS-GA，这是一种为解决多状态设计分配问题而开发的多目标遗传算法。 MOMS-GA的假设是，系统及其组件都可能会经历两种以上的性能状态。 MOMS-GA使用通用力矩生成函数（UMGF）方法来评估系统的不同可靠性指标。因此，系统可用性由多状态可用性功能表示，该功能扩展了传统的二进制状态可用性。解决了电力系统规划中常见的三种不同的设计分配问题，以显示算法的性能。前两个示例中考虑的多目标公式对应于系统可用性的最大化，系统投资成本的最小化和预期系统容量的最大化。在第三个示例中，多目标公式化试图最大化系统可用性，最小化系统投资成本以及最小化预期的未供应需求。

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