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Enhancing LV system resilience through probabilistic forecasting of interdependent variables: voltage, reactive and active power

forecasting
probabilistic
machine learning

Anthony Faustine and Pereira, Lucas, “Enhancing LV system resilience through probabilistic forecasting of interdependent variables: voltage, reactive and active power,” CIRED Chicago Workshop 2024: Resilience of Electric Distribution Systems, Chicago, USA, 2025, pp. 27-31, doi: 10.1049/icp.2024.2555

Authors
Affiliations

Anthony Faustine

Center for Intelligent Power (CIP), Eaton Corporation, Dublin, Ireland

Pereira, Lucas

ITI, LARSyS, Técnico Lisboa, 1049-001 Lisboa, Portugal

Published

July 2024

Other details

Presented at the CIRED Chicago Workshop 2024: Resilience of Electric Distribution Systems

Abstract

This paper presents a probabilistic forecasting approach tailored for low voltage (LV) substations, offering short-term predictions for three crucial variables: voltage, reactive power, and active power. These parameters play a vital role in the resilience of distribution systems, especially in the presence of Distributed Energy Resources (DERs). Evaluation with simulated data shows that active and reactive power forecasts degrade notably with higher EV penetration, whereas voltage forecasting experiences less degradation across all scenarios.

Figure

Figure 5: Predicted ODA (foreign aid) across a range of differences from average number of anti-NGO laws in an average country; dark line shows average of 500 draws from posterior distribution.

Figure 5: Predicted ODA (foreign aid) across a range of differences from average number of anti-NGO laws in an average country; dark line shows average of 500 draws from posterior distribution.

BibTeX citation

@INPROCEEDINGS{10916091,
  author={Faustine, Anthony and Pereira, Lucas},
  booktitle={CIRED Chicago Workshop 2024: Resilience of Electric Distribution Systems}, 
  title={Enhancing LV system resilience through probabilistic forecasting of interdependent variables: voltage, reactive and active power}, 
  year={2025},
  volume={2024},
  number={},
  pages={27-31},
  keywords={},
  doi={10.1049/icp.2024.2555}}