IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i24p16429-d997463.html
   My bibliography  Save this article

An Energy Management System for PV Sources in Standalone and Connected DC Networks Considering Economic, Technical, and Environmental Indices

Author

Listed:
  • Luis Fernando Grisales-Noreña

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

  • Jauder Alexander Ocampo-Toro

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

  • Andrés Alfonso Rosales-Muñoz

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

  • Brandon Cortes-Caicedo

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

  • 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 research proposes an efficient energy management system for standalone and grid-connected direct current (DC) distribution networks that consider photovoltaic (PV) generation sources. A complete nonlinear programming model is formulated to represent the efficient PV dispatch problem while taking three different objective functions into account. The first objective function corresponds to the minimization of the operational costs with respect to the energy purchasing costs at terminals of the substation, including the maintenance costs of the PV sources. The second objective function is the reduction of the expected daily energy losses regarding all resistive effects of the distribution lines. The third objective function concerns the minimization of the total emissions of CO 2 into the atmosphere by the substation bus or its equivalent (diesel generator). These objective functions are minimized using a single-objective optimization approach through the application of the Salp Swarm Algorithm (SSA), which is combined with a matrix hourly power flow formulation that works by using a leader–follower operation scheme. Two test feeders composed of 27 and 33 nodes set for standalone and grid-connected operation are used in the numerical validations. The standalone grid corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá, and the grid-connected system is adapted to the operating conditions in the metropolitan area of Medellín, i.e., a rural area and a major city in Colombia. A numerical comparison with three additional combinatorial optimizers (i.e., particle swarm optimization (PSO), the multiverse optimizer (MVO), and the crow search algorithm (CSA)) demonstrates the effectiveness and robustness of the proposed leader–follower optimization approach to the optimal management of PV generation sources in DC grids while considering different objective function indices.

Suggested Citation

  • Luis Fernando Grisales-Noreña & Jauder Alexander Ocampo-Toro & Andrés Alfonso Rosales-Muñoz & Brandon Cortes-Caicedo & Oscar Danilo Montoya, 2022. "An Energy Management System for PV Sources in Standalone and Connected DC Networks Considering Economic, Technical, and Environmental Indices," Sustainability, MDPI, vol. 14(24), pages 1-25, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16429-:d:997463
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/24/16429/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/24/16429/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrés Alfonso Rosales-Muñoz & Jhon Montano & Luis Fernando Grisales-Noreña & Oscar Danilo Montoya & Fabio Andrade, 2022. "Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method," Sustainability, MDPI, vol. 14(20), pages 1-32, October.
    2. Andrés Alfonso Rosales-Muñoz & Luis Fernando Grisales-Noreña & Jhon Montano & Oscar Danilo Montoya & Alberto-Jesus Perea-Moreno, 2021. "Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luis Fernando Grisales-Noreña & Andrés Alfonso Rosales-Muñoz & Oscar Danilo Montoya, 2023. "An Effective Power Dispatch of Photovoltaic Generators in DC Networks via the Antlion Optimizer," Energies, MDPI, vol. 16(3), pages 1-28, January.
    2. Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Jesús C. Hernández, 2023. "Efficient Day-Ahead Dispatch of Photovoltaic Sources in Monopolar DC Networks via an Iterative Convex Approximation," Energies, MDPI, vol. 16(3), pages 1-14, January.
    3. Oscar Danilo Montoya & Federico Martin Serra & Walter Gil-González, 2023. "A Robust Conic Programming Approximation to Design an EMS in Monopolar DC Networks with a High Penetration of PV Plants," Energies, MDPI, vol. 16(18), pages 1-17, September.
    4. Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Diego Armando Giral-Ramírez, 2023. "Multi-Objective Dispatch of PV Plants in Monopolar DC Grids Using a Weighted-Based Iterative Convex Solution Methodology," Energies, MDPI, vol. 16(2), pages 1-20, January.
    5. Kimsrornn Khon & Chhith Chhlonh & Vannak Vai & Marie-Cecile Alvarez-Herault & Bertrand Raison & Long Bun, 2023. "Comprehensive Low Voltage Microgrid Planning Methodology for Rural Electrification," Sustainability, MDPI, vol. 15(3), pages 1-23, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhammad Riaz & Aamir Hanif & Haris Masood & Muhammad Attique Khan & Kamran Afaq & Byeong-Gwon Kang & Yunyoung Nam, 2021. "An Optimal Power Flow Solution of a System Integrated with Renewable Sources Using a Hybrid Optimizer," Sustainability, MDPI, vol. 13(23), pages 1-12, December.
    2. Andrés Alfonso Rosales-Muñoz & Jhon Montano & Luis Fernando Grisales-Noreña & Oscar Danilo Montoya & Fabio Andrade, 2022. "Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method," Sustainability, MDPI, vol. 14(20), pages 1-32, October.
    3. Daniel Sanin-Villa & Oscar Danilo Montoya & Walter Gil-González & Luis Fernando Grisales-Noreña & Alberto-Jesus Perea-Moreno, 2023. "Parameter Estimation of a Thermoelectric Generator by Using Salps Search Algorithm," Energies, MDPI, vol. 16(11), pages 1-16, May.
    4. Dong Yu & Shan Gao & Xin Zhao & Yu Liu & Sicheng Wang & Tiancheng E. Song, 2023. "Alternating Iterative Power-Flow Algorithm for Hybrid AC–DC Power Grids Incorporating LCCs and VSCs," Sustainability, MDPI, vol. 15(5), pages 1-22, March.
    5. Luis Fernando Grisales-Noreña & Andrés Alfonso Rosales-Muñoz & Brandon Cortés-Caicedo & Oscar Danilo Montoya & Fabio Andrade, 2022. "Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow," Mathematics, MDPI, vol. 11(1), pages 1-28, December.
    6. Daniel Sanin-Villa & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña, 2023. "Material Property Characterization and Parameter Estimation of Thermoelectric Generator by Using a Master–Slave Strategy Based on Metaheuristics Techniques," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    7. Luis Fernando Grisales-Noreña & Andrés Alfonso Rosales-Muñoz & Oscar Danilo Montoya, 2023. "An Effective Power Dispatch of Photovoltaic Generators in DC Networks via the Antlion Optimizer," Energies, MDPI, vol. 16(3), pages 1-28, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16429-:d:997463. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.