IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i18p5976-d639572.html
   My bibliography  Save this article

Energy Management of Microgrids for Smart Cities: A Review

Author

Listed:
  • Muhammad Salman Sami

    (Department of Electrical Engineering, Bahauddin Zakariya University, Multan 66000, Pakistan)

  • Muhammad Abrar

    (Department of Electrical Engineering, Bahauddin Zakariya University, Multan 66000, Pakistan)

  • Rizwan Akram

    (Department of Electrical Engineering, College of Engineering, Qassim University, Qassim 51452, Saudi Arabia)

  • Muhammad Majid Hussain

    (Faculty of Computing, Engineering and Sciences, University of South Wales, Cardiff CF37 1DL, UK)

  • Mian Hammad Nazir

    (Faculty of Computing, Engineering and Sciences, University of South Wales, Cardiff CF37 1DL, UK)

  • Muhammad Saad Khan

    (Department of Electrical Engineering, Bahauddin Zakariya University, Multan 66000, Pakistan)

  • Safdar Raza

    (Department of Electrical Engineering, NFC Institute of Engineering and Technology (NFC-IET), Multan 60000, Pakistan)

Abstract

Electric power reliability is one of the most important factors in the social and economic evolution of a smart city, whereas the key factors to make a city smart are smart energy sources and intelligent electricity networks. The development of cost-effective microgrids with the added functionality of energy storage and backup generation plans has resulted from the combined impact of high energy demands from consumers and environmental concerns, which push for minimizing the energy imbalance, reducing energy losses and CO 2 emissions, and improving the overall security and reliability of a power system. It is now possible to tackle the problem of growing consumer load by utilizing the recent developments in modern types of renewable energy resources (RES) and current technology. These energy alternatives do not emit greenhouse gases (GHG) like fossil fuels do, and so help to mitigate climate change. They also have in socioeconomic advantages due to long-term sustainability. Variability and intermittency are the main drawbacks of renewable energy resources (RES), which affect the consistency of electric supply. Thus, utilizing multiple optimization approaches, the energy management system determines the optimum solution for renewable energy resources (RES) and transfers it to the microgrid. Microgrids maintain the continuity of power delivery, according to the energy management system settings. In a microgrid, an energy management system (EMS) is used to decrease the system’s expenses and adverse consequences. As a result, a variety of strategies and approaches are employed in the development of an efficient energy management system. This article is intended to provide a comprehensive overview of a range of technologies and techniques, and their solutions, for managing the drawbacks of renewable energy supplies, such as variability and load fluctuations, while still matching energy demands for their integration in the microgrids of smart cities.

Suggested Citation

  • Muhammad Salman Sami & Muhammad Abrar & Rizwan Akram & Muhammad Majid Hussain & Mian Hammad Nazir & Muhammad Saad Khan & Safdar Raza, 2021. "Energy Management of Microgrids for Smart Cities: A Review," Energies, MDPI, vol. 14(18), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5976-:d:639572
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/18/5976/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/18/5976/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rui Yang & Yupeng Yuan & Rushun Ying & Boyang Shen & Teng Long, 2020. "A Novel Energy Management Strategy for a Ship’s Hybrid Solar Energy Generation System Using a Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 13(6), pages 1-14, March.
    2. Onur Hınçal & A. Altan-Sakarya & A. Metin Ger, 2011. "Optimization of Multireservoir Systems by Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1465-1487, March.
    3. Hossain, Md Alamgir & Pota, Hemanshu Roy & Squartini, Stefano & Abdou, Ahmed Fathi, 2019. "Modified PSO algorithm for real-time energy management in grid-connected microgrids," Renewable Energy, Elsevier, vol. 136(C), pages 746-757.
    4. Sen, Souvik & Ganguly, Sourav, 2017. "Opportunities, barriers and issues with renewable energy development – A discussion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1170-1181.
    5. Sarshar, Javad & Moosapour, Seyyed Sajjad & Joorabian, Mahmood, 2017. "Multi-objective energy management of a micro-grid considering uncertainty in wind power forecasting," Energy, Elsevier, vol. 139(C), pages 680-693.
    6. Nemati, Mohsen & Braun, Martin & Tenbohlen, Stefan, 2018. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming," Applied Energy, Elsevier, vol. 210(C), pages 944-963.
    7. Keshtkar, Azim & Arzanpour, Siamak, 2017. "An adaptive fuzzy logic system for residential energy management in smart grid environments," Applied Energy, Elsevier, vol. 186(P1), pages 68-81.
    8. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Mendoza, Franklin, 2009. "Design and economical analysis of hybrid PV-wind systems connected to the grid for the intermittent production of hydrogen," Energy Policy, Elsevier, vol. 37(8), pages 3082-3095, August.
    9. Benedetti, Miriam & Cesarotti, Vittorio & Introna, Vito & Serranti, Jacopo, 2016. "Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study," Applied Energy, Elsevier, vol. 165(C), pages 60-71.
    10. Balderrama, Sergio & Lombardi, Francesco & Riva, Fabio & Canedo, Walter & Colombo, Emanuela & Quoilin, Sylvain, 2019. "A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community," Energy, Elsevier, vol. 188(C).
    11. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    12. Coelho, Vitor N. & Coelho, Igor M. & Coelho, Bruno N. & de Oliveira, Glauber C. & Barbosa, Alexandre C. & Pereira, Leo & de Freitas, Alan & Santos, Haroldo G. & Ochi, Luis S. & Guimarães, Frederico G., 2017. "A communitarian microgrid storage planning system inside the scope of a smart city," Applied Energy, Elsevier, vol. 201(C), pages 371-381.
    13. Sukumar, Shivashankar & Mokhlis, Hazlie & Mekhilef, Saad & Naidu, Kanendra & Karimi, Mazaher, 2017. "Mix-mode energy management strategy and battery sizing for economic operation of grid-tied microgrid," Energy, Elsevier, vol. 118(C), pages 1322-1333.
    14. Du, Wen-Bo & Gao, Yang & Liu, Chen & Zheng, Zheng & Wang, Zhen, 2015. "Adequate is better: particle swarm optimization with limited-information," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 832-838.
    15. Liu, Nian & Tang, Qingfeng & Zhang, Jianhua & Fan, Wei & Liu, Jie, 2014. "A hybrid forecasting model with parameter optimization for short-term load forecasting of micro-grids," Applied Energy, Elsevier, vol. 129(C), pages 336-345.
    16. Amponsah, Nana Yaw & Troldborg, Mads & Kington, Bethany & Aalders, Inge & Hough, Rupert Lloyd, 2014. "Greenhouse gas emissions from renewable energy sources: A review of lifecycle considerations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 461-475.
    17. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    18. Marzband, Mousa & Ghadimi, Majid & Sumper, Andreas & Domínguez-García, José Luis, 2014. "Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode," Applied Energy, Elsevier, vol. 128(C), pages 164-174.
    19. Xuejie Wang & Yanchao Ji & Jianze Wang & Yuanjun Wang & Lei Qi, 2020. "Optimal energy management of microgrid based on multi-parameter dynamic programming," International Journal of Distributed Sensor Networks, , vol. 16(6), pages 15501477209, June.
    20. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    21. Jafari, Mohammad & Malekjamshidi, Zahra, 2020. "Optimal energy management of a residential-based hybrid renewable energy system using rule-based real-time control and 2D dynamic programming optimization method," Renewable Energy, Elsevier, vol. 146(C), pages 254-266.
    22. Panwar, N.L. & Kaushik, S.C. & Kothari, Surendra, 2011. "Role of renewable energy sources in environmental protection: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1513-1524, April.
    23. Ahmad, Jameel & Imran, Muhammad & Khalid, Abdullah & Iqbal, Waseem & Ashraf, Syed Rehan & Adnan, Muhammad & Ali, Syed Farooq & Khokhar, Khawar Siddique, 2018. "Techno economic analysis of a wind-photovoltaic-biomass hybrid renewable energy system for rural electrification: A case study of Kallar Kahar," Energy, Elsevier, vol. 148(C), pages 208-234.
    24. Roy, Kallol & Mandal, Kamal Krishna & Mandal, Atis Chandra, 2019. "Ant-Lion Optimizer algorithm and recurrent neural network for energy management of micro grid connected system," Energy, Elsevier, vol. 167(C), pages 402-416.
    25. Tina, Giuseppe Marco & Gagliano, Salvina, 2011. "Probabilistic modelling of hybrid solar/wind power system with solar tracking system," Renewable Energy, Elsevier, vol. 36(6), pages 1719-1727.
    26. Caspary, Georg, 2009. "Gauging the future competitiveness of renewable energy in Colombia," Energy Economics, Elsevier, vol. 31(3), pages 443-449, May.
    27. Dias, César Luiz de Azevedo & Castelo Branco, David Alves & Arouca, Maurício Cardoso & Loureiro Legey, Luiz Fernando, 2017. "Performance estimation of photovoltaic technologies in Brazil," Renewable Energy, Elsevier, vol. 114(PB), pages 367-375.
    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. Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
    2. Jihed Hmad & Azeddine Houari & Allal El Moubarek Bouzid & Abdelhakim Saim & Hafedh Trabelsi, 2023. "A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids," Energies, MDPI, vol. 16(13), pages 1-41, June.
    3. Tatiana Tucunduva Philippi Cortese & Jairo Filho Sousa de Almeida & Giseli Quirino Batista & José Eduardo Storopoli & Aaron Liu & Tan Yigitcanlar, 2022. "Understanding Sustainable Energy in the Context of Smart Cities: A PRISMA Review," Energies, MDPI, vol. 15(7), pages 1-38, March.
    4. Nemanja Mišljenović & Matej Žnidarec & Goran Knežević & Damir Šljivac & Andreas Sumper, 2023. "A Review of Energy Management Systems and Organizational Structures of Prosumers," Energies, MDPI, vol. 16(7), pages 1-32, March.

    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. Danny Espín-Sarzosa & Rodrigo Palma-Behnke & Oscar Núñez-Mata, 2020. "Energy Management Systems for Microgrids: Main Existing Trends in Centralized Control Architectures," Energies, MDPI, vol. 13(3), pages 1-32, January.
    2. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    3. Pinciroli, Luca & Baraldi, Piero & Compare, Michele & Zio, Enrico, 2023. "Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning," Applied Energy, Elsevier, vol. 352(C).
    4. Velik, Rosemarie & Nicolay, Pascal, 2014. "Grid-price-dependent energy management in microgrids using a modified simulated annealing triple-optimizer," Applied Energy, Elsevier, vol. 130(C), pages 384-395.
    5. 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.
    6. Raya-Armenta, Jose Maurilio & Bazmohammadi, Najmeh & Avina-Cervantes, Juan Gabriel & Sáez, Doris & Vasquez, Juan C. & Guerrero, Josep M., 2021. "Energy management system optimization in islanded microgrids: An overview and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    7. Álex Omar Topa Gavilema & José Domingo Álvarez & José Luis Torres Moreno & Manuel Pérez García, 2021. "Towards Optimal Management in Microgrids: An Overview," Energies, MDPI, vol. 14(16), pages 1-25, August.
    8. Tayab, Usman Bashir & Lu, Junwei & Yang, Fuwen & AlGarni, Tahani Saad & Kashif, Muhammad, 2021. "Energy management system for microgrids using weighted salp swarm algorithm and hybrid forecasting approach," Renewable Energy, Elsevier, vol. 180(C), pages 467-481.
    9. Mohammed Amine Hoummadi & Manale Bouderbala & Hala Alami Aroussi & Badre Bossoufi & Najib El Ouanjli & Mohammed Karim, 2023. "Survey of Sustainable Energy Sources for Microgrid Energy Management: A Review," Energies, MDPI, vol. 16(7), pages 1-16, March.
    10. Pascual, Julio & Barricarte, Javier & Sanchis, Pablo & Marroyo, Luis, 2015. "Energy management strategy for a renewable-based residential microgrid with generation and demand forecasting," Applied Energy, Elsevier, vol. 158(C), pages 12-25.
    11. Md Shafiullah & Akib Mostabe Refat & Md Ershadul Haque & Dewan Mabrur Hasan Chowdhury & Md Sanower Hossain & Abdullah G. Alharbi & Md Shafiul Alam & Amjad Ali & Shorab Hossain, 2022. "Review of Recent Developments in Microgrid Energy Management Strategies," Sustainability, MDPI, vol. 14(22), pages 1-30, November.
    12. Abdellatif Elmouatamid & Radouane Ouladsine & Mohamed Bakhouya & Najib El Kamoun & Mohammed Khaidar & Khalid Zine-Dine, 2020. "Review of Control and Energy Management Approaches in Micro-Grid Systems," Energies, MDPI, vol. 14(1), pages 1-30, December.
    13. Zhang, Jingrui & Wu, Yihong & Guo, Yiran & Wang, Bo & Wang, Hengyue & Liu, Houde, 2016. "A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints," Applied Energy, Elsevier, vol. 183(C), pages 791-804.
    14. Thiaux, Yaël & Dang, Thu Thuy & Schmerber, Louis & Multon, Bernard & Ben Ahmed, Hamid & Bacha, Seddik & Tran, Quoc Tuan, 2019. "Demand-side management strategy in stand-alone hybrid photovoltaic systems with real-time simulation of stochastic electricity consumption behavior," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    15. Ji-Won Lee & Mun-Kyeom Kim & Hyung-Joon Kim, 2021. "A Multi-Agent Based Optimization Model for Microgrid Operation with Hybrid Method Using Game Theory Strategy," Energies, MDPI, vol. 14(3), pages 1-21, January.
    16. Clarke, Will Challis & Brear, Michael John & Manzie, Chris, 2020. "Control of an isolated microgrid using hierarchical economic model predictive control," Applied Energy, Elsevier, vol. 280(C).
    17. Elsied, Moataz & Oukaour, Amrane & Youssef, Tarek & Gualous, Hamid & Mohammed, Osama, 2016. "An advanced real time energy management system for microgrids," Energy, Elsevier, vol. 114(C), pages 742-752.
    18. 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.
    19. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2015. "A detailed model for the optimal management of a multigood microgrid," Applied Energy, Elsevier, vol. 154(C), pages 862-873.
    20. Brandon Cortés-Caicedo & Luis Fernando Grisales-Noreña & Oscar Danilo Montoya & Miguel Angel Rodriguez-Cabal & Javier Alveiro Rosero, 2022. "Energy Management System for the Optimal Operation of PV Generators in Distribution Systems Using the Antlion Optimizer: A Colombian Urban and Rural Case Study," Sustainability, MDPI, vol. 14(23), pages 1-35, December.

    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:14:y:2021:i:18:p:5976-:d:639572. 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.