...
首页> 外文期刊>Electric power systems research >Blackouts risk evaluation by Monte Carlo Simulation regarding cascading outages and system frequency deviation
【24h】

Blackouts risk evaluation by Monte Carlo Simulation regarding cascading outages and system frequency deviation

机译:通过蒙特卡洛模拟评估连锁停电和系统频率偏差的停电风险

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper, a blackout risk assessment method is proposed considering the effects of cascading outages, the active power and frequency response of the system. Here, the Monte Carlo Simulation (MCS) is used to analyze the risk of blackouts by generating rare event scenarios. In the proposed model the cascading outages are considered as the result of transmission equipments overloading and hidden failure of the protection system, which they can increase the probability of large blackouts. The primary frequency control of the generators and the frequency sensitivity of the loads are also modeled in each step of cascading outages. A DC OPF model is used as the operator remedial action to minimize the lost load. The obtained lost load data are used to calculate Expected Load Not Served (ELNS) and Complementary Cumulative Density Function (CCDF) to analyze the risk of blackout. The CCDF of the lost load data is directly calculated from the lost load data and Gaussian Mixture Method (GMM) is applied to estimate the Probability Distribution Function (PDF) and the smoothed CCDF of the lost load data. Based on the proposed method, the power law distribution of the blackout size is studied by looking at the IEEE 118 bus test case.
机译:本文提出了一种考虑级联中断,系统的有功功率和频率响应的影响的停电风险评估方法。在这里,蒙特卡罗模拟(MCS)用于通过生成罕见事件场景来分析停电的风险。在所提出的模型中,级联故障被认为是传输设备过载和保护系统隐患的结果,它们可以增加大停电的可能性。在级联中断的每个步骤中,还对发电机的主要频率控制和负载的频率灵敏度进行了建模。 DC OPF模型用作操作员的补救措施,以最大程度地减少损失的负载。所获得的损失负载数据用于计算预期的未服务负载(ELNS)和互补累积密度函数(CCDF),以分析停电风险。直接从失载数据计算失载数据的CCDF,然后应用高斯混合法(GMM)来估计概率分布函数(PDF)和失载数据的平滑CCDF。基于提出的方法,通过查看IEEE 118总线测试案例研究了停电大小的幂律分布。

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