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Optimal Energy Management within a Microgrid: A Comparative Study

Author

Listed:
  • Luis Orlando Polanco Vasquez

    (Electrical Engineering Department, Campus Irapuato-Salamanca, University of Guanajuato, Guanajuato 36885, Mexico)

  • Cristian Andrés Carreño Meneses

    (Electrical Engineering Department, Campus Irapuato-Salamanca, University of Guanajuato, Guanajuato 36885, Mexico)

  • Alejandro Pizano Martínez

    (Electrical Engineering Department, Campus Irapuato-Salamanca, University of Guanajuato, Guanajuato 36885, Mexico)

  • Juana López Redondo

    (Department of Informatics, University of Almería, Agrifood Campus of International Excellence (ceiA3) CIESOL Joint Centre University of Almería-CIEMAT, 04120 Almería, Spain)

  • Manuel Pérez García

    (Department of Informatics, University of Almería, Agrifood Campus of International Excellence (ceiA3) CIESOL Joint Centre University of Almería-CIEMAT, 04120 Almería, Spain)

  • José Domingo Álvarez Hervás

    (Department of Informatics, University of Almería, Agrifood Campus of International Excellence (ceiA3) CIESOL Joint Centre University of Almería-CIEMAT, 04120 Almería, Spain)

Abstract

In this work, we focus on optimal energy management within the context of the tertiary control of a microgrid operating in grid-connected mode. Specifically, the optimal energy management problem is solved in a unified way by using the optimal power flow (OPF) and day-ahead concepts. The elements considered in the microgrid are a photovoltaic panel, a wind turbine, electric vehicles, a storage system, and a point of common coupling with the main grid. The aim of this paper consists of optimizing the economic energy dispatch within the microgrid considering known predictions of electricity demand, solar radiation, and wind speed for a given period of time. The OPF is solved using three different algorithms provided by the optimization toolbox of MATLAB ® (R2015a, MathWorks ® , Natick, MA, USA): the interior point method (IP), a hybrid genetic algorithm with interior point (GA-IP), and a hybrid direct search with interior point (patternsearch-IP). The efficiency and effectiveness of the algorithms to optimize the energy dispatch within the microgrid are verified and analyzed through a case study, where real climatological data of solar irradiance, wind speed in Almería city, photovoltaic system data, and room load from a bioclimatic building were considered.

Suggested Citation

  • Luis Orlando Polanco Vasquez & Cristian Andrés Carreño Meneses & Alejandro Pizano Martínez & Juana López Redondo & Manuel Pérez García & José Domingo Álvarez Hervás, 2018. "Optimal Energy Management within a Microgrid: A Comparative Study," Energies, MDPI, vol. 11(8), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2167-:d:164534
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    References listed on IDEAS

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    1. Ustun, Taha Selim & Ozansoy, Cagil & Zayegh, Aladin, 2011. "Recent developments in microgrids and example cases around the world—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 4030-4041.
    2. Kou, Peng & Liang, Deliang & Gao, Lin, 2017. "Distributed EMPC of multiple microgrids for coordinated stochastic energy management," Applied Energy, Elsevier, vol. 185(P1), pages 939-952.
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    1. Goran Jurišić & Juraj Havelka & Tomislav Capuder & Stjepan Sučić, 2018. "Laboratory Test Bed for Analyzing Fault-Detection Reaction Times of Protection Relays in Different Substation Topologies," Energies, MDPI, vol. 11(9), pages 1-14, September.
    2. Mohammad Jafar Hadidian Moghaddam & Akhtar Kalam & Mohammad Reza Miveh & Amirreza Naderipour & Foad H. Gandoman & Ali Asghar Ghadimi & Zulkurnain Abdul-Malek, 2018. "Improved Voltage Unbalance and Harmonics Compensation Control Strategy for an Isolated Microgrid," Energies, MDPI, vol. 11(10), pages 1-26, October.
    3. Solanke, Tirupati U. & Khatua, Pradeep K. & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao, 2021. "Control and management of a multilevel electric vehicles infrastructure integrated with distributed resources: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. Pabel Alberto Cárdenas & Maximiliano Martínez & Marcelo Gustavo Molina & Pedro Enrique Mercado, 2023. "Development of Control Techniques for AC Microgrids: A Critical Assessment," Sustainability, MDPI, vol. 15(21), pages 1-28, October.
    5. Masoud Dashtdar & Aymen Flah & Seyed Mohammad Sadegh Hosseinimoghadam & Hossam Kotb & Elżbieta Jasińska & Radomir Gono & Zbigniew Leonowicz & Michał Jasiński, 2022. "Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony," Sustainability, MDPI, vol. 14(11), pages 1-26, May.

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