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Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks

Author

Listed:
  • Luis Fernando Grisales-Noreña

    (Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile)

  • Brandon Cortés-Caicedo

    (Departamento de Mecatrónica y Electromecánica, Facultad de Ingeniería, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia)

  • Gerardo Alcalá

    (Centro de Investigación en Recursos Energéticos y Sustentables, Universidad Veracruzana, Coatzacoalcos, Veracruz 96535, Mexico)

  • Oscar Danilo Montoya

    (Grupo de Compatibilidad e Interferencia Electromagnética (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia
    Laboratorio Inteligente de Energía, Facultad de Ingeniería, Universidad Tecnológica de Bolívar, Cartagena 131001, Colombia)

Abstract

This paper presents an efficient master–slave methodology to solve the problem of integrating photovoltaic (PV) generators into DC grids for a planning period of 20 years. The problem is mathematically formulated as Mixed-Integer Nonlinear Programming (MINLP) with the objective of minimizing the total annual operating cost. The main stage, consisting of a discrete-continuous version of the Crow search algorithm (DCCSA), is in charge of determining the installation positions of the PV generators and their corresponding power ratings. On the other hand, at the slave level, the successive approximation power flow method is used to determine the objective function value. Numerical results on 33- and 69-bus test systems demonstrate the applicability, efficiency and robustness of the developed approach with respect to different methodologies previously discussed in the scientific literature, such as the vortex search algorithm, the generalized normal distribution optimizer and the particle swarm optimization algorithm. Numerical tests are performed in the MATLAB programming environment using proprietary scripts.

Suggested Citation

  • Luis Fernando Grisales-Noreña & Brandon Cortés-Caicedo & Gerardo Alcalá & Oscar Danilo Montoya, 2023. "Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks," Mathematics, MDPI, vol. 11(2), pages 1-18, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:2:p:387-:d:1032559
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    References listed on IDEAS

    as
    1. Luis Fernando Grisales-Noreña & Oscar Danilo Montoya & Edward-J. Marín-García & Carlos Andres Ramos-Paja & Alberto-Jesus Perea-Moreno, 2022. "Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO," Energies, MDPI, vol. 15(20), pages 1-20, October.
    2. López, Andrea Ruíz & Krumm, Alexandra & Schattenhofer, Lukas & Burandt, Thorsten & Montoya, Felipe Corral & Oberländer, Nora & Oei, Pao-Yu, 2020. "Solar PV generation in Colombia - A qualitative and quantitative approach to analyze the potential of solar energy market," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 148, pages 1266-1279.
    3. Beasley, J. E. & Chu, P. C., 1996. "A genetic algorithm for the set covering problem," European Journal of Operational Research, Elsevier, vol. 94(2), pages 392-404, October.
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    5. López, Andrea Ruíz & Krumm, Alexandra & Schattenhofer, Lukas & Burandt, Thorsten & Montoya, Felipe Corral & Oberländer, Nora & Oei, Pao-Yu, 2020. "Solar PV generation in Colombia - A qualitative and quantitative approach to analyze the potential of solar energy market," Renewable Energy, Elsevier, vol. 148(C), pages 1266-1279.
    6. Oscar Danilo Montoya & Walter Gil-González & Luis Grisales-Noreña & César Orozco-Henao & Federico Serra, 2019. "Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models," Energies, MDPI, vol. 12(23), pages 1-20, November.
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