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A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions

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  • Hu, Jiefeng
  • Xu, Yinliang
  • Cheng, Ka Wai
  • Guerrero, Josep M.

Abstract

Renewable energy sources have been increasingly deployed as distributed generators in remote areas. Meanwhile, fluctuating power generation from renewable energy sources, together with variable power demand, poses challenges in stable and reliable power supply. In this paper, a microgrid with solar photovoltaic (PV) and battery energy storage (BES) is studied. A state of charge (SOC)-oriented charging scheme is developed to control the BES to smooth the PV output. Most importantly, a sophisticated control algorithm, consisting of a model predictive voltage control (MPVC) and a model predictive power control (MPPC), is proposed for the interlinking converter. It enables stable voltage in islanded mode. Also, in grid-connected mode, flexible reactive power can be injected into the main grid for grid support according to the voltage variation level. Finally, by considering the intermittent nature of the PV and the load profile, an energy management system (EMS) is designed to ensure power balance within the system. Case studies are provided to demonstrate the effectiveness of the proposed control strategy.

Suggested Citation

  • Hu, Jiefeng & Xu, Yinliang & Cheng, Ka Wai & Guerrero, Josep M., 2018. "A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions," Applied Energy, Elsevier, vol. 221(C), pages 195-203.
    • Handle: RePEc:eee:appene:v:221:y:2018:i:c:p:195-203
    DOI: 10.1016/j.apenergy.2018.03.085
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    7. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    8. Wang, Jing & Zhao, Changhong & Pratt, Annabelle & Baggu, Murali, 2018. "Design of an advanced energy management system for microgrid control using a state machine," Applied Energy, Elsevier, vol. 228(C), pages 2407-2421.
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    10. Kneiske, T.M. & Niedermeyer, F. & Boelling, C., 2019. "Testing a model predictive control algorithm for a PV-CHP hybrid system on a laboratory test-bench," Applied Energy, Elsevier, vol. 242(C), pages 121-137.
    11. Yuan, Minghan & Fu, Yang & Mi, Yang & Li, Zhenkun & Wang, Chengshan, 2019. "Hierarchical control of DC microgrid with dynamical load power sharing," Applied Energy, Elsevier, vol. 239(C), pages 1-11.
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    14. Andreu Cecilia & Javier Carroquino & Vicente Roda & Ramon Costa-Castelló & Félix Barreras, 2020. "Optimal Energy Management in a Standalone Microgrid, with Photovoltaic Generation, Short-Term Storage, and Hydrogen Production," Energies, MDPI, vol. 13(6), pages 1-24, March.
    15. Masaki, Mukalu Sandro & Zhang, Lijun & Xia, Xiaohua, 2019. "A hierarchical predictive control for supercapacitor-retrofitted grid-connected hybrid renewable systems," Applied Energy, Elsevier, vol. 242(C), pages 393-402.
    16. Shen, Xiaojun & Wei, Hongyang & Wei, Li, 2020. "Study of trackside photovoltaic power integration into the traction power system of suburban elevated urban rail transit line," Applied Energy, Elsevier, vol. 260(C).
    17. Horrillo-Quintero, Pablo & García-Triviño, Pablo & Sarrias-Mena, Raúl & García-Vázquez, Carlos A. & Fernández-Ramírez, Luis M., 2023. "Model predictive control of a microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV systems," Applied Energy, Elsevier, vol. 346(C).
    18. Mi, Yang & Chen, Xin & Ji, Hongpeng & Ji, Liang & Fu, Yang & Wang, Chengshan & Wang, Jianhui, 2019. "The coordinated control strategy for isolated DC microgrid based on adaptive storage adjustment without communication," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    19. Sánchez de la Nieta, Agustín A. & Paterakis, Nikolaos G. & Gibescu, Madeleine, 2020. "Participation of photovoltaic power producers in short-term electricity markets based on rescheduling and risk-hedging mapping," Applied Energy, Elsevier, vol. 266(C).
    20. Chapaloglou, Spyridon & Nesiadis, Athanasios & Iliadis, Petros & Atsonios, Konstantinos & Nikolopoulos, Nikos & Grammelis, Panagiotis & Yiakopoulos, Christos & Antoniadis, Ioannis & Kakaras, Emmanuel, 2019. "Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system," Applied Energy, Elsevier, vol. 238(C), pages 627-642.
    21. Mudhafar Al-Saadi & Maher Al-Greer & Michael Short, 2021. "Strategies for Controlling Microgrid Networks with Energy Storage Systems: A Review," Energies, MDPI, vol. 14(21), pages 1-45, November.
    22. Fan, Feilong & Huang, Wentao & Tai, Nengling & Zheng, Xiaodong & Hu, Yan & Ma, Zhoujun, 2018. "A conditional depreciation balancing strategy for the equitable operation of extended hybrid energy storage systems," Applied Energy, Elsevier, vol. 228(C), pages 1937-1952.
    23. Vo-Van Thanh & Wencong Su & Bin Wang, 2022. "Optimal DC Microgrid Operation with Model Predictive Control-Based Voltage-Dependent Demand Response and Optimal Battery Dispatch," Energies, MDPI, vol. 15(6), pages 1-19, March.

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