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Localization and Sizing of Distributed Generation through a Genetic Algorithm to Improve Voltage Profile Using Ecuadorian Standards

Author

Listed:
  • David Calvachi

    (Engineering Department, South Campus, Av. Rumichaca and Av. M. Valverde, Universidad Politecnica Salesiana, Quito 170702, Ecuador
    These authors contributed equally to this work.)

  • Luis Tipán

    (Engineering Department, South Campus, Av. Rumichaca and Av. M. Valverde, Universidad Politecnica Salesiana, Quito 170702, Ecuador
    These authors contributed equally to this work.)

  • Manuel Jaramillo

    (Engineering Department, South Campus, Av. Rumichaca and Av. M. Valverde, Universidad Politecnica Salesiana, Quito 170702, Ecuador
    These authors contributed equally to this work.)

Abstract

The approach proposed for the development of this research work was based on the integration of Distributed Energy Generation (DG) into an energy distribution network, improving the voltage profile by establishing an optimal location and sizing of DG power plants, for which the use of a heuristic optimization method known as Genetic Algorithm (GA), which has several restrictions to limit its operation and thus achieve an optimal solution to the planned optimization problem, was resorted to. The development of a power flow allowed having the voltage measurement in the bars of the network before incorporating DG, allowing to verify that the voltage fluctuations present an improvement after the incorporation one by one of each DG central defined by the GA. The systems in which the voltage measurement was performed, as well as the verification of its fluctuations with and without DG once the GA was used, were the IEEE systems of 9 and 14 busbars, the latter the one used to demonstrate the scalability of the GA to locate and dimension DG without considering the number of busbars in a system.

Suggested Citation

  • David Calvachi & Luis Tipán & Manuel Jaramillo, 2023. "Localization and Sizing of Distributed Generation through a Genetic Algorithm to Improve Voltage Profile Using Ecuadorian Standards," Energies, MDPI, vol. 16(10), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4139-:d:1148932
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    References listed on IDEAS

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    1. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
    2. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    3. Huy, Phung Dang & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao & Ekanayake, Janaka B., 2020. "Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage," Energy, Elsevier, vol. 195(C).
    4. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
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    Cited by:

    1. Matheus Diniz Gonçalves-Leite & Edgar Manuel Carreño-Franco & Jesús M. López-Lezama, 2023. "Impact of Distributed Generation on the Effectiveness of Electric Distribution System Reconfiguration," Energies, MDPI, vol. 16(17), pages 1-20, August.
    2. Husam A. Neamah & Mohammed Dulaimi & Alaa Silavinia & Aminu Babangida & Péter Tamás Szemes, 2024. "Development of a Volkswagen Jetta MK5 Hybrid Vehicle for Optimized System Efficiency Based on a Genetic Algorithm," Energies, MDPI, vol. 17(5), pages 1-25, February.
    3. Leonardo Chabla-Auqui & Danny Ochoa-Correa & Edisson Villa-Ávila & Patricio Astudillo-Salinas, 2023. "Distributed Generation Applied to Residential Self-Supply in South America in the Decade 2013–2023: A Literature Review," Energies, MDPI, vol. 16(17), pages 1-30, August.

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