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

A. S. Nazmul Huda, Rastko Živanovic

Research output: Contribution to journalArticlepeer-review

Abstract

ABSTRACT—: 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.

Original languageEnglish
Pages (from-to)810-822
Number of pages13
JournalElectric Power Components and Systems
Volume47
Issue number9-10
DOIs
Publication statusPublished - 15 Jun 2019

Keywords

  • Euler-Maruyama method
  • expected energy not supplied
  • multilevel Monte Carlo
  • power distribution systems
  • time-varying load models

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