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Energy Loss Allocation in Smart Distribution Systems with Electric Vehicle Integration

Author

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  • Paulo M. De Oliveira-De Jesus

    (Department of Electrical and Electronic Engineering, School of Engineering, Los Andes University, Bogotá 111711, Colombia)

  • Mario A. Rios

    (Department of Electrical and Electronic Engineering, School of Engineering, Los Andes University, Bogotá 111711, Colombia)

  • Gustavo A. Ramos

    (Department of Electrical and Electronic Engineering, School of Engineering, Los Andes University, Bogotá 111711, Colombia)

Abstract

This paper presents a three-phase loss allocation procedure for distribution networks. The key contribution of the paper is the computation of specific marginal loss coefficients (MLCs) per bus and per phase expressly considering non-linear load models for Electric Vehicles (EV). The method was applied in a unbalanced 12.47 kV feeder with 12,780 households and 1000 EVs under peak and off-peak load conditions. Results obtained were also compared with the traditional roll-in embedded allocation procedure (pro rata) using non-linear and standard constant power models. Results show the influence of the non-linear load model in the energy losses allocated. This result highlights the importance of considering an appropriate EV load model to appraise the overall losses encouraging the use and further development of the methodology

Suggested Citation

  • Paulo M. De Oliveira-De Jesus & Mario A. Rios & Gustavo A. Ramos, 2018. "Energy Loss Allocation in Smart Distribution Systems with Electric Vehicle Integration," Energies, MDPI, vol. 11(8), pages 1-19, July.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:1962-:d:160471
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    References listed on IDEAS

    as
    1. Manvir Kaur & Smarajit Ghosh, 2017. "Effective Loss Minimization and Allocation of Unbalanced Distribution Network," Energies, MDPI, vol. 10(12), pages 1-17, November.
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    3. Hernández, J.C. & Ruiz-Rodriguez, F.J. & Jurado, F., 2017. "Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems," Energy, Elsevier, vol. 141(C), pages 316-332.
    4. Yuttana Kongjeen & Krischonme Bhumkittipich, 2018. "Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis," Energies, MDPI, vol. 11(6), pages 1-16, June.
    5. Francisco J. Ruiz-Rodríguez & Jesús C. Hernández & Francisco Jurado, 2017. "Probabilistic Load-Flow Analysis of Biomass-Fuelled Gas Engines with Electrical Vehicles in Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-23, October.
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    Cited by:

    1. Thomas I. Strasser & Sebastian Rohjans & Graeme M. Burt, 2019. "Methods and Concepts for Designing and Validating Smart Grid Systems," Energies, MDPI, vol. 12(10), pages 1-5, May.
    2. Sadiq Ahmad & Ayaz Ahmad & Muhammad Naeem & Waleed Ejaz & Hyung Seok Kim, 2018. "A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid," Energies, MDPI, vol. 11(10), pages 1-33, October.
    3. Jean-Michel Clairand & Javier Rodríguez-García & Carlos Álvarez-Bel, 2018. "Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation," Energies, MDPI, vol. 11(11), pages 1-21, November.

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