Efficient Assessment of Electricity Distribution Network Adequacy with the Cross-Entropy Method

J.N. Betge, Barbera Droste, Jacco Heres, S.H. Tindemans

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Identifying future congestion points in electricity distribution networks is an important challenge distribution system operators face. A proven approach for addressing this challenge is to assess distribution grid adequacy using probabilistic models of future demand. However, computational cost can become a severe challenge when evaluating large probabilistic electricity demand forecasting models with long forecasting horizons. In this paper, Monte Carlo methods are developed to increase the computational efficiency of obtaining asset overload probabilities from a bottom-up stochastic demand model. Cross-entropy optimised importance sampling is contrasted with conventional Monte Carlo sampling. Benchmark results of the proposed methods suggest that the importance sampling-based methods introduced in this work are suitable for estimating rare overload probabilities for assets with a small number of customers.
Original languageEnglish
Title of host publication2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings
Number of pages6
ISBN (Electronic)978-1-6654-3597-0
Publication statusPublished - 2021
Event2021 IEEE Madrid PowerTech - Virtual/online event
Duration: 28 Jun 20212 Jul 2021

Publication series

Name2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings


Conference2021 IEEE Madrid PowerTech
Abbreviated titlePowerTech 2021

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • adequacy assessment
  • cross-entropy method
  • demand modelling
  • distribution networks
  • importance sampling


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