Revista UIS Ingenierías

Vol. 22 No. 4 (2023): Revista UIS Ingenierías
Articles

New data-based load modeling for active distribution networks

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  • Daladier Osorio-Vásquez ,
  • Sandra Pérez-Londoño ,
  • Juan Mora-Flórez
Daladier Osorio-Vásquez
Universidad Tecnológica de Pereira
Sandra Pérez-Londoño
Universidad Tecnológica de Pereira
Juan Mora-Flórez
Universidad Tecnológica de Pereira
DOI: https://doi.org/10.18273/revuin.v22n4-2023009

Published 2023-11-15

Keywords

  • active distribution network,
  • data-based models,
  • distributed energy resources,
  • dynamic models,
  • load modeling,
  • measurement-based models’ parameterization,
  • static models
    • ...More
    Less

How to Cite

Osorio-Vásquez , D. ., Pérez-Londoño , S. ., & Mora-Flórez , J. . (2023). New data-based load modeling for active distribution networks. Revista UIS Ingenierías, 22(4), 93–102. https://doi.org/10.18273/revuin.v22n4-2023009

Copyright (c) 2023 Revista UIS Ingenierías

Creative Commons License

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

Abstract

Electric systems are experiencing fast development, mainly motivated by the carbon reduction policies in the energy sector and the technological developments that introduce new elements and processes. The transition to active distribution networks (ADNs) represents a significant technological advancement in this ever-evolving context. Accurate models for each device present in ADNs are crucial for adequately representing their dynamics; however, load modeling poses challenges due to the vast diversity of load components, variations over time, and dependence on several factors. Despite these challenges, understanding load behavior is fundamental for efficient planning and operation of ADNs. Therefore, precise load models are indispensable for conducting preventive and forensic studies. This paper analyzes various scientific documents from the most relevant scientific databases, explicitly focusing on the challenge of measurement-based load modeling in ADNs. The main contribution of this document lies in enhancing the representation and understanding of loads in ADNs through the analysis of current approaches, challenges, and measurement-based modeling strategies. Additionally, it serves as a reference for future research in the field of load modeling.

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