Risk-Aware Operating Regions for PV-Rich Distribution Networks Considering Irradiance Variability

Edgar Mauricio Salazar Duque*, Juan S. Giraldo, Pedro P. Vergara, Phuong H. Nguyen, Anne van der Molen, J. G. Slootweg

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review


This article proposes a framework to identify, visualize, and quantify risk of potential over/under voltage due to annual energy consumption and PV generation growth. The stochastic modeling considers the following: (i) Active and reactive power profiles for distribution transformers, dependent on annual energy consumption and activity in the serviced areas. (ii) Variable solar irradiance profiles that allow a broader range of PV generation scenarios for sunny, overcast, and cloudy days. The proposed framework uses multivariate-t copulas to model temporal correlations between random variables to generate synthetic scenarios. A probabilistic power flow is computed using the generated scenarios to define critical static operating regions. Results show that classical approaches may underestimate the maximum PV capacity of distribution networks when local irradiance conditions are not considered. Moreover, it is found that including annual energy consumption growth is critical to establishing realistic PV installation capacity limits. Finally, a sensitivity analysis shows that taking a 5% of overvoltage risk could increase up to 15% of the PV installed capacity limits.

Original languageEnglish
Pages (from-to)2092-2108
Number of pages17
JournalIEEE Transactions on Sustainable Energy
Issue number4
Publication statusPublished - 2023

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.


  • Multivariate copulas
  • stochastic modeling
  • load modeling
  • irradiance modeling
  • hosting capacity


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