首页> 外文期刊>Generation, Transmission & Distribution, IET >Data clustering-based approach for optimal capacitor allocation in distribution systems including wind farms
【24h】

Data clustering-based approach for optimal capacitor allocation in distribution systems including wind farms

机译:基于数据聚类的方法可在包括风电场在内的配电系统中优化电容器分配

获取原文
获取原文并翻译 | 示例
           

摘要

Optimal placement and sizing of shunt capacitors are important issues to improve voltage profile and reduce power losses in distribution networks. In this regard, dealing with stochastic nature of wind farms (WFs), the issue becomes more complex in wind-integrated radial distribution networks. This study aims at optimal siting and sizing of shunt capacitors considering wind uncertainty. Application of probabilistic approach causes to access more real and extensive information about the network. To do so, Monte Carlo simulation (MCS) is employed to assess stochastic variation of wind farm output. As the salient feature of this research, K-means-based data clustering approach is utilised, in which all data-points of the output power of WFs are bunched into desired clusters to ease the solving of simple MCS. The voltage profile and power losses are analysed to do the optimal siting and sizing of capacitors. In order to assess the effectiveness of the proposed method, results are compared with the simple MCS that proves the efficiency of the proposed method from the viewpoint of computation time.
机译:并联电容器的最佳放置和尺寸调整是改善电压分布并减少配电网络中功率损耗的重要问题。在这方面,考虑到风电场(WF)的随机性,在集成风的径向分布网络中,该问题变得更加复杂。这项研究旨在考虑风的不确定性来优化并联电容器的位置和尺寸。概率方法的应用导致访问有关网络的更多真实且广泛的信息。为此,采用蒙特卡洛模拟(MCS)评估风电场输出的随机变化。作为这项研究的显着特征,使用了基于K均值的数据聚类方法,该方法将WF的所有输出功率数据点聚集成所需的聚类,以简化简单MCS的求解。分析电压曲线和功率损耗,以实现电容器的最佳位置和尺寸。为了评估该方法的有效性,将结果与简单的MCS进行了比较,该方法从计算时间的角度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