IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i8p2167-d164534.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/8/2167/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/8/2167/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. 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.

    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. Bullich-Massagué, Eduard & Díaz-González, Francisco & Aragüés-Peñalba, Mònica & Girbau-Llistuella, Francesc & Olivella-Rosell, Pol & Sumper, Andreas, 2018. "Microgrid clustering architectures," Applied Energy, Elsevier, vol. 212(C), pages 340-361.
    2. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    3. Hosseini, Seyed Amir & Abyaneh, Hossein Askarian & Sadeghi, Seyed Hossein Hesamedin & Razavi, Farzad & Nasiri, Adel, 2016. "An overview of microgrid protection methods and the factors involved," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 174-186.
    4. Li, Qiang & Gao, Mengkai & Lin, Houfei & Chen, Ziyu & Chen, Minyou, 2019. "MAS-based distributed control method for multi-microgrids with high-penetration renewable energy," Energy, Elsevier, vol. 171(C), pages 284-295.
    5. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    6. Thomas Sachs & Anna Gründler & Milos Rusic & Gilbert Fridgen, 2019. "Framing Microgrid Design from a Business and Information Systems Engineering Perspective," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(6), pages 729-744, December.
    7. Kinnon, Michael Mac & Razeghi, Ghazal & Samuelsen, Scott, 2021. "The role of fuel cells in port microgrids to support sustainable goods movement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    8. Yong Long & Yu Wang & Chengrong Pan, 2018. "Incentive Mechanism of Micro-grid Project Development," Sustainability, MDPI, vol. 10(1), pages 1-19, January.
    9. Adil, Ali M. & Ko, Yekang, 2016. "Socio-technical evolution of Decentralized Energy Systems: A critical review and implications for urban planning and policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1025-1037.
    10. Bracco, Stefano & Delfino, Federico & Pampararo, Fabio & Robba, Michela & Rossi, Mansueto, 2013. "The University of Genoa smart polygeneration microgrid test-bed facility: The overall system, the technologies and the research challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 442-459.
    11. Younes Zahraoui & Ibrahim Alhamrouni & Saad Mekhilef & M. Reyasudin Basir Khan & Mehdi Seyedmahmoudian & Alex Stojcevski & Ben Horan, 2021. "Energy Management System in Microgrids: A Comprehensive Review," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    12. Juanpera, M. & Ferrer-Martí, L. & Pastor, R., 2022. "Multi-stage optimization of rural electrification planning at regional level considering multiple criteria. Case study in Nigeria," Applied Energy, Elsevier, vol. 314(C).
    13. José Luis Ruiz Duarte & Neng Fan, 2022. "Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies," Energies, MDPI, vol. 15(7), pages 1-24, March.
    14. Hare, James & Shi, Xiaofang & Gupta, Shalabh & Bazzi, Ali, 2016. "Fault diagnostics in smart micro-grids: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1114-1124.
    15. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    16. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    17. Mehdizadeh, Ali & Taghizadegan, Navid & Salehi, Javad, 2018. "Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management," Applied Energy, Elsevier, vol. 211(C), pages 617-630.
    18. de la Hoz, Jordi & Martín, Helena & Alonso, Alex & Carolina Luna, Adriana & Matas, José & Vasquez, Juan C. & Guerrero, Josep M., 2019. "Regulatory-framework-embedded energy management system for microgrids: The case study of the Spanish self-consumption scheme," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    19. Zhuang, Minghao & Lu, Xi & Peng, Wei & Wang, Yanfen & Wang, Jianxiao & Nielsen, Chris P. & McElroy, Michael B., 2021. "Opportunities for household energy on the Qinghai-Tibet Plateau in line with United Nations’ Sustainable Development Goals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    20. Taylan G. Topcu & Konstantinos Triantis, 2022. "An ex-ante DEA method for representing contextual uncertainties and stakeholder risk preferences," Annals of Operations Research, Springer, vol. 309(1), pages 395-423, February.

    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:jeners:v:11:y:2018:i:8:p:2167-:d:164534. 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.