首页> 外文会议>China International Conference on Electricity Distribution >A Quasi Monte Carlo probabilistic load flow method of distribution system containing distributed generation and electric vehicle charging load based on Sobol sequence
【24h】

A Quasi Monte Carlo probabilistic load flow method of distribution system containing distributed generation and electric vehicle charging load based on Sobol sequence

机译:一种基于Sobol序列的分布式发电和电动车充电载荷的分配系统准蒙特卡罗概率载荷方法

获取原文

摘要

To calculate probabilistic load flow of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), at first the effect on load flow for distribution system after connecting DG and EVCL is analyzed, and the stochastic characteristics of power output of wind generation and photovoltaic power generation as well as basic load and EVCL are researched, meanwhile a probabilistic load flow (PLF) calculation model of distribution system containing DG and EVCL is built. According to this basis and based on these drawback that the traditional Latin hypercube sampling method is of low accuracy for its incapability of generating sampling sequences of low discrepancy, a Quasi Monte Carlo simulation method (QMCSM) based on Sobol sequence is put forward. The simulation results on IEEE30 bus system and IEEE118 bus system have demonstrated the validity of the proposed method. In contrast to the method based on Latin hypercube sampling, the proposed method is of high efficiency, accuracy and speed.
机译:为了计算含有分布式发电(DG)和电动车辆充电负荷(EVCL)的分配系统的概率负荷流量,分析了DG和EVCL后的分配系统对配电系统的效果,以及风电输出的随机特性研究了一代和光伏发电以及基本负载和EVCL,同时建立了包含DG和EVCL的分配系统的概率负荷流(PLF)计算模型。根据这一基础并基于这些缺点,传统的拉丁杂交采样方法具有低精度,以产生低差异的采样序列,提出了一种基于Sobol序列的准蒙特卡罗模拟方法(QMCSM)。 IEEE30总线系统和IEEE118总线系统的仿真结果表明了该方法的有效性。与基于拉丁超立体采样的方法相比,所提出的方法具有高效率,准确性和速度。

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