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Estimation of Distribution Systems Expected Energy Not Supplied Index by Multi-level Monte Carlo Method

机译:多层蒙特卡罗方法估算配电系统预期能源未供应指数

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摘要

The article presents the estimation of power distribution systems Expected Energy Not Supplied (EENS) index by incorporating time-varying load models of different customer sectors. An application of a new and efficient advanced Monte Carlo simulation (MCS) with controllable accuracy called Multilevel Monte Carlo (MLMC) method is proposed for this estimation. The purpose of the proposed method is to increase the simulation speed of EENS estimation. The method could be easily replaced by the traditional MCS-based estimation which requires huge computational effort for achieving high level of simulation accuracy. Five distribution networks with seven different load models of Roy Billinton Test System are chosen as test distribution systems. To verify the effectiveness of the proposed method, computational time and estimated values of EENS using MLMC method are compared to the results from MCS. The computation performance of EENS estimation can be influenced by different factors and criteria which are also explored in this study. The results presented in the article show that acceptable results can be obtained using the proposed method while substantial reduction of computational effort is also achieved.
机译:本文通过结合不同客户部门的时变负载模型,对配电系统的预期未供应能源(EENS)指数进行了估算。提出了一种新的高效,精度可控的先进蒙特卡洛模拟(MCS)的应用,称为多级蒙特卡洛(MLMC)方法。该方法的目的是提高EENS估计的仿真速度。该方法可以轻松地替换为基于MCS的传统估算,该估算需要大量的计算工作才能实现高水平的仿真精度。选择具有Roy Billinton测试系统的七个不同负载模型的五个配电网络作为测试配电系统。为了验证所提方法的有效性,将使用MLMC方法的EENS的计算时间和估计值与MCS的结果进行了比较。 EENS估计的计算性能可能受不同因素和标准的影响,本研究也将对此进行探讨。文章中提供的结果表明,使用所提出的方法可以获得可接受的结果,同时还可以大大减少计算量。

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