【24h】

Smart grid reconfiguration using simple genetic algorithm and NSGA-II

机译:使用简单遗传算法和NSGA-II进行智能电网重新配置

获取原文
获取原文并翻译 | 示例

摘要

Increased penetration of distributed generators (DGs) is one of the characteristics of smart grids. Distribution grid reconfiguration is one of the methods of accommodating more DG into the electric grid, which is illustrated with the help of a 16 node test network in this paper. The reconfiguration of the distribution grid involves changing the grid topology thereby optimizing a few objectives. In addition to the inclusion of DGs, grid reconfiguration also helps in achieving minimal power loss, minimal voltage deviation etc. In this paper the grid reconfiguration problem is formulated as an optimization problem. Simple genetic algorithm (GA) and its variant NSGA-II are used for solving the optimization problem. For a simple test system like the 16 node system discussed in this paper, simple GA is efficient enough to find the global optimum for a single objective optimization. The paper also illustrates the advantage of NSGA-II compared to simple GA when multiple objectives are considered.
机译:分布式发电机(DG)的普及率提高是智能电网的特征之一。配电网重构是将更多的DG容纳到电网中的方法之一,本文借助16节点测试网络进行了说明。配电网格的重新配置涉及更改网格拓扑,从而优化一些目标。除了包括DG,电网重新配置还有助于实现最小的功率损耗,最小的电压偏差等。本文将电网重新配置问题表述为优化问题。简单遗传算法(GA)及其变体NSGA-II用于解决优化问题。对于像本文讨论的16节点系统这样的简单测试系统,简单的GA足以为单个目标优化找到全局最优值。当考虑多个目标时,本文还说明了NSGA-II与简单GA相比的优势。

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