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Data Analytics-Based Multi-Objective Particle Swarm Optimization for Determination of Congestion Thresholds in LV Networks

Author

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  • Javier Leiva

    (Endesa, 28042 Madrid, Spain
    Department of Electrical Engineering, University of Málaga, 29016 Málaga, Spain)

  • Rubén Carmona Pardo

    (Endesa, 28042 Madrid, Spain)

  • José A. Aguado

    (Department of Electrical Engineering, University of Málaga, 29016 Málaga, Spain)

Abstract

A growing presence of distributed energy resources (DER) and the increasingly diverse nature of end users at low-voltage (LV) networks make the operation of these grids more and more challenging. Particularly, congestion and voltage management strategies for LV grids have usually been limited to some elemental criteria based on human experience, asset oversizing, or grid reinforcement. However, with the current massive deployment of sensors in modern LV grids, new approaches are feasible for distribution network assets operation. This article proposes a multi-objective particle swarm optimization (MOPSO) approach, combined with data analytics through affinity propagation clustering, for congestion threshold determination in LV grids. A real case study from the smart grid of Smartcity Malaga Living Lab is used to illustrate the proposed approach. Within this approach, distribution system operators (DSOs) can take decisions in order to prevent situations of risk or potential failure at LV grids.

Suggested Citation

  • Javier Leiva & Rubén Carmona Pardo & José A. Aguado, 2019. "Data Analytics-Based Multi-Objective Particle Swarm Optimization for Determination of Congestion Thresholds in LV Networks," Energies, MDPI, vol. 12(7), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1295-:d:219955
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    References listed on IDEAS

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    Cited by:

    1. Aleksandra Baczyńska & Waldemar Niewiadomski, 2020. "Power Flow Tracing for Active Congestion Management in Modern Power Systems," Energies, MDPI, vol. 13(18), pages 1-25, September.
    2. Yalcin, Ahmet Selcuk & Kilic, Huseyin Selcuk & Delen, Dursun, 2022. "The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.

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