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Optimal Placement and Sizing of PV Sources in Distribution Grids Using a Modified Gradient-Based Metaheuristic Optimizer

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  • Oscar Danilo Montoya

    (Grupo de Compatibilidad e Interferencia Electromagnética, 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)

  • Luis Fernando Grisales-Noreña

    (Facultad de Ingeniería, Campus Robledo, Institución Universitaria Pascual Bravo, Medellín 050036, Colombia)

  • Diego Armando Giral-Ramírez

    (Facultad Tecnológica, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia)

Abstract

The problem of the optimal placement and sizing of renewable generation sources based on photovoltaic (PV) technology in electrical distribution grids operated in medium-voltage levels was studied in this research. This optimization problem is from the mixed-integer nonlinear programming (MINLP) model family. Solving this model was achieved by implementing a master–slave optimization approach, where the master–slave corresponded to the application of the modified gradient-based metaheuristic optimizer (MGbMO) and the slave stage corresponded to the application of the successive approximation power flow method. In the master stage, the problem of the optimal placement and sizing of the PV sources was solved using a discrete–continuous codification, while the slave stage was used to calculate the objective function value regarding the energy purchasing costs in terminals of the substation, as well as to verify that the voltage profiles and the power generations were within their allowed bounds. The numerical results of the proposed MGbMO in the IEEE 34-bus system demonstrated its efficiency when compared with different metaheuristic optimizers such as the Chu and Beasley genetic algorithm, the Newton metaheuristic algorithm, the original gradient-based metaheuristic optimizer, and the exact solution of the MINLP model using the general algebraic modeling system. In addition, the possibility of including meshed distribution topologies was tested with excellent numerical results.

Suggested Citation

  • Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Diego Armando Giral-Ramírez, 2022. "Optimal Placement and Sizing of PV Sources in Distribution Grids Using a Modified Gradient-Based Metaheuristic Optimizer," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3318-:d:769346
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    References listed on IDEAS

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    1. 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.
    2. Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Alberto-Jesus Perea-Moreno, 2021. "Optimal Investments in PV Sources for Grid-Connected Distribution Networks: An Application of the Discrete–Continuous Genetic Algorithm," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    3. 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.
    4. Francesc Girbau-Llistuella & Francisco Díaz-González & Andreas Sumper & Ramon Gallart-Fernández & Daniel Heredero-Peris, 2018. "Smart Grid Architecture for Rural Distribution Networks: Application to a Spanish Pilot Network," Energies, MDPI, vol. 11(4), pages 1-35, April.
    5. Tao Shen & Yanjun Li & Ji Xiang, 2018. "A Graph-Based Power Flow Method for Balanced Distribution Systems," Energies, MDPI, vol. 11(3), pages 1-11, February.
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    Cited by:

    1. David Steveen Guzmán-Romero & Brandon Cortés-Caicedo & Oscar Danilo Montoya, 2023. "Development of a MATLAB-GAMS Framework for Solving the Problem Regarding the Optimal Location and Sizing of PV Sources in Distribution Networks," Resources, MDPI, vol. 12(3), pages 1-19, March.
    2. Dara Eam & Vannak Vai & Chhith Chhlonh & Samphors Eng, 2023. "Planning of an LVAC Distribution System with Centralized PV and Decentralized PV Integration for a Rural Village," Energies, MDPI, vol. 16(16), pages 1-19, August.
    3. Ghareeb Moustafa & Mostafa Elshahed & Ahmed R. Ginidi & Abdullah M. Shaheen & Hany S. E. Mansour, 2023. "A Gradient-Based Optimizer with a Crossover Operator for Distribution Static VAR Compensator (D-SVC) Sizing and Placement in Electrical Systems," Mathematics, MDPI, vol. 11(5), pages 1-30, February.
    4. Julián David Pradilla-Rozo & Julián Alejandro Vega-Forero & Oscar Danilo Montoya, 2023. "Application of the Gradient-Based Metaheuristic Optimizerto Solve the Optimal Conductor Selection Problemin Three-Phase Asymmetric Distribution Networks," Energies, MDPI, vol. 16(2), pages 1-29, January.
    5. Oscar Danilo Montoya & Carlos Andrés Ramos-Paja & Luis Fernando Grisales-Noreña, 2022. "An Efficient Methodology for Locating and Sizing PV Generators in Radial Distribution Networks Using a Mixed-Integer Conic Relaxation," Mathematics, MDPI, vol. 10(15), pages 1-17, July.

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