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Predictive Control for Microgrid Applications: A Review Study

Author

Listed:
  • Ariel Villalón

    (Engineering Systems Doctoral Program, Faculty of Engineering, University of Talca, Campus Curicó 3344158, Chile)

  • Marco Rivera

    (Department of Electrical Engineering, Faculty of Engineering, University of Talca, Campus Curicó 3344158, Chile)

  • Yamisleydi Salgueiro

    (Department of Computer Science, Faculty of Engineering, University of Talca, Campus Curicó 3344158, Chile)

  • Javier Muñoz

    (Department of Electrical Engineering, Faculty of Engineering, University of Talca, Campus Curicó 3344158, Chile)

  • Tomislav Dragičević

    (Centre for Electric Power and Energy, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

  • Frede Blaabjerg

    (Department of Energy Technology, Aalborg University, 9220 Aalborg East, Denmark)

Abstract

Microgrids need control and management at different levels to allow the inclusion of renewable energy sources. In this paper, a comprehensive literature review is presented to analyse the latest trends in research and development referring to the applications of predictive control in microgrids. As a result of this review, it was found that the application of predictive control techniques on microgrids is performed for the three control levels and with adaptations of the models in order to include uncertainties to improve their performance and dynamics response. In addition, to ensure system stability, but also, at higher control levels, coordinated operation among the microgrid’s components and synchronised and optimised operation with utility grids and electric power markets. Predictive control appears as a very promising control scheme with several advantages for microgrid applications of different control levels.

Suggested Citation

  • Ariel Villalón & Marco Rivera & Yamisleydi Salgueiro & Javier Muñoz & Tomislav Dragičević & Frede Blaabjerg, 2020. "Predictive Control for Microgrid Applications: A Review Study," Energies, MDPI, vol. 13(10), pages 1-32, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2454-:d:357624
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    References listed on IDEAS

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    1. Md Alamgir Hossain & Hemanshu Roy Pota & Walid Issa & Md Jahangir Hossain, 2017. "Overview of AC Microgrid Controls with Inverter-Interfaced Generations," Energies, MDPI, vol. 10(9), pages 1-27, August.
    2. Justo, Jackson John & Mwasilu, Francis & Lee, Ju & Jung, Jin-Woo, 2013. "AC-microgrids versus DC-microgrids with distributed energy resources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 387-405.
    3. Yael Parag & Benjamin K. Sovacool, 2016. "Electricity market design for the prosumer era," Nature Energy, Nature, vol. 1(4), pages 1-6, April.
    4. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    5. Planas, Estefanía & Gil-de-Muro, Asier & Andreu, Jon & Kortabarria, Iñigo & Martínez de Alegría, Iñigo, 2013. "General aspects, hierarchical controls and droop methods in microgrids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 147-159.
    6. Hui Yang & Rui Tu & Ke Wang & Jiaxing Lei & Wenjia Wang & Shuang Feng & Chaofan Wei, 2019. "A Hybrid Predictive Control for a Current Source Converter in an Aircraft DC Microgrid," Energies, MDPI, vol. 12(21), pages 1-14, October.
    7. Sultana, W. Razia & Sahoo, Sarat Kumar & Sukchai, Sukruedee & Yamuna, S. & Venkatesh, D., 2017. "A review on state of art development of model predictive control for renewable energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 391-406.
    8. Andishgar, Mohammad Hadi & Gholipour, Eskandar & Hooshmand, Rahmat-allah, 2017. "An overview of control approaches of inverter-based microgrids in islanding mode of operation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1043-1060.
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    Cited by:

    1. Kaiye Gao & Tianshi Wang & Chenjing Han & Jinhao Xie & Ye Ma & Rui Peng, 2021. "A Review of Optimization of Microgrid Operation," Energies, MDPI, vol. 14(10), pages 1-39, May.
    2. Xuhong Yang & Hui Li & Wei Jia & Zhongxin Liu & Yu Pan & Fengwei Qian, 2022. "Adaptive Virtual Synchronous Generator Based on Model Predictive Control with Improved Frequency Stability," Energies, MDPI, vol. 15(22), pages 1-13, November.
    3. 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.
    4. Luís Caseiro & André Mendes, 2021. "Fault Analysis and Non-Redundant Fault Tolerance in 3-Level Double Conversion UPS Systems Using Finite-Control-Set Model Predictive Control," Energies, MDPI, vol. 14(8), pages 1-39, April.
    5. Ariel Villalón & Carlos Muñoz & Javier Muñoz & Marco Rivera, 2023. "Fixed-Switching-Frequency Modulated Model Predictive Control for Islanded AC Microgrid Applications," Mathematics, MDPI, vol. 11(3), pages 1-27, January.
    6. Smitha Joyce Pinto & Pierluigi Siano & Mimmo Parente, 2023. "Review of Cybersecurity Analysis in Smart Distribution Systems and Future Directions for Using Unsupervised Learning Methods for Cyber Detection," Energies, MDPI, vol. 16(4), pages 1-24, February.
    7. Patricio Gaisse & Javier Muñoz & Ariel Villalón & Rodrigo Aliaga, 2020. "Improved Predictive Control for an Asymmetric Multilevel Converter for Photovoltaic Energy," Sustainability, MDPI, vol. 12(15), pages 1-22, August.
    8. Marcel Nicola & Claudiu-Ionel Nicola & Dan Selișteanu, 2022. "Improvement of the Control of a Grid Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent," Energies, MDPI, vol. 15(7), pages 1-32, March.
    9. Sarah Ouédraogo & Ghjuvan Antone Faggianelli & Guillaume Pigelet & Jean Laurent Duchaud & Gilles Notton, 2020. "Application of Optimal Energy Management Strategies for a Building Powered by PV/Battery System in Corsica Island," Energies, MDPI, vol. 13(17), pages 1-20, September.
    10. Ramzi Saidi & Jean-Christophe Olivier & Mohamed Machmoum & Eric Chauveau, 2021. "Cascaded Centered Moving Average Filters for Energy Management in Multisource Power Systems with a Large Number of Devices," Energies, MDPI, vol. 14(12), pages 1-21, June.
    11. Nor Liza Tumeran & Siti Hajar Yusoff & Teddy Surya Gunawan & Mohd Shahrin Abu Hanifah & Suriza Ahmad Zabidi & Bernardi Pranggono & Muhammad Sharir Fathullah Mohd Yunus & Siti Nadiah Mohd Sapihie & Asm, 2023. "Model Predictive Control Based Energy Management System Literature Assessment for RES Integration," Energies, MDPI, vol. 16(8), pages 1-27, April.
    12. Bingyin Lei & Yue Ren & Huiyu Luan & Ruonan Dong & Xiuyuan Wang & Junli Liao & Shu Fang & Kaiye Gao, 2023. "A Review of Optimization for System Reliability of Microgrid," Mathematics, MDPI, vol. 11(4), pages 1-30, February.
    13. Saeedreza Jadidi & Hamed Badihi & Youmin Zhang, 2020. "Passive Fault-Tolerant Control Strategies for Power Converter in a Hybrid Microgrid," Energies, MDPI, vol. 13(21), pages 1-28, October.
    14. Marvin Lema & Wilson Pavon & Leony Ortiz & Ama Baduba Asiedu-Asante & Silvio Simani, 2022. "Controller Coordination Strategy for DC Microgrid Using Distributed Predictive Control Improving Voltage Stability," Energies, MDPI, vol. 15(15), pages 1-15, July.
    15. Qingle Pang & Lin Ye & Houlei Gao & Xinian Li & Yang Zheng & Chenbin He, 2021. "Penalty Electricity Price-Based Optimal Control for Distribution Networks," Energies, MDPI, vol. 14(7), pages 1-16, March.
    16. Felix Garcia-Torres & Ascension Zafra-Cabeza & Carlos Silva & Stephane Grieu & Tejaswinee Darure & Ana Estanqueiro, 2021. "Model Predictive Control for Microgrid Functionalities: Review and Future Challenges," Energies, MDPI, vol. 14(5), pages 1-26, February.
    17. Ammar Armghan & Muhammad Kashif Azeem & Hammad Armghan & Ming Yang & Fayadh Alenezi & Mudasser Hassan, 2021. "Dynamical Operation Based Robust Nonlinear Control of DC Microgrid Considering Renewable Energy Integration," Energies, MDPI, vol. 14(13), pages 1-23, July.
    18. Eros D. Escobar & Tatiana Manrique & Idi A. Isaac, 2022. "Campus Microgrid Data-Driven Model Identification and Secondary Voltage Control," Energies, MDPI, vol. 15(21), pages 1-19, October.
    19. Marcel Nicola & Claudiu-Ionel Nicola, 2021. "Fractional-Order Control of Grid-Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers," Energies, MDPI, vol. 14(2), pages 1-25, January.
    20. Juan Moreno-Castro & Victor Samuel Ocaña Guevara & Lesyani Teresa León Viltre & Yandi Gallego Landera & Oscar Cuaresma Zevallos & Miguel Aybar-Mejía, 2023. "Microgrid Management Strategies for Economic Dispatch of Electricity Using Model Predictive Control Techniques: A Review," Energies, MDPI, vol. 16(16), pages 1-24, August.
    21. Escobar, Eros D. & Betancur, Daniel & Manrique, Tatiana & Isaac, Idi A., 2023. "Model predictive real-time architecture for secondary voltage control of microgrids," Applied Energy, Elsevier, vol. 345(C).

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