...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Optimal Control Applications and Methods >Optimal location of micro-phasor measurement units in distribution system control, monitoring, and protection using hybrid technique
【24h】

Optimal location of micro-phasor measurement units in distribution system control, monitoring, and protection using hybrid technique

机译：Optimal location of micro-phasor measurement units in distribution system control, monitoring, and protection using hybrid technique

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

摘要

This manuscript proposes a hybrid technique for the optimum location of micro-phasor measurement units (mu-PMUs) in the distribution system(DS).The proposed hybrid approach is the wrapper of dwarf mongoose optimizer (DMO) and pelican optimization algorithm (POA). The updating behavior of DMO is improved by the POA; therefore, it is called DMO-POA approach. The main aim of the proposed approach is to avoid discontinuity of supply and minimizes the count of PMDs to reduce cost and attain the maximal count of measurement-redundancy that is limited to full-system observability for IEEE bus-system in zero injection nodes (ZINs) and tie-switches. The proposed approach considered the optimum count of mu-PMUs is needed for the thorough distribution system economy, observability, and the reliability measure. The proposed approach considers the distribution of PMUs in the reconfiguration of smart-distribution-grids, ZINs and communication system requirements. Here, the objective-function is aiming at minimizing the costs of reliability and capital. The proposed method uses the infrastructure of communication cost to simultaneously co-optimize the system switching strategy and find the optimal sites for PMUs. The performance of the proposed technique is tested in different test-systems, like IEEE-14 bus, 13, 34, 37, and 123 buses and the performance is executed by comparing it with the existing approaches. Furthermore, the proposed system is effectual to find an optimal solution with less computation and decreases the complexity of the algorithm.

著录项

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