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Novel standalone hybrid solar/wind/fuel cell/battery power generation system

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  • Fathabadi, Hassan

Abstract

A novel standalone hybrid solar/wind/fuel cell (FC)/battery power generation system is designed and constructed. It consists of a photovoltaic (PV) array, a wind energy conversion system (WECS), a FC system, a battery bank, three unidirectional DC/DC converters, a bidirectional DC/DC converter, a unified maximum power point tracking (MPPT) controller, a control unit, and a DC/AC inverter. The contribution of this work is that the standalone hybrid solar/wind/FC/battery system presented in this work is the only large-scale constructed hybrid system reported in the literature that combines two renewable resources (solar and wind) with a battery bank and a fuel cell system used as standby power sources, and moreover, it maximally converts solar and wind energies into electric energy because it uses a novel fast and highly accurate unified MPPT technique that concurrently tracks the maximum power points of both PV system and WECS. Other works usually combine solar energy with wind energy, and are mostly simulation based works, and moreover, there is not any new MPPT consideration in them. It is experimentally verified that the constructed system is a perfect standalone hybrid solar/wind/FC/battery power source that efficiently produces electric energy under different environmental conditions such as cloudy sky, and so can be widely used in remote areas.

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  • Fathabadi, Hassan, 2017. "Novel standalone hybrid solar/wind/fuel cell/battery power generation system," Energy, Elsevier, vol. 140(P1), pages 454-465.
    • Handle: RePEc:eee:energy:v:140:y:2017:i:p1:p:454-465
    DOI: 10.1016/j.energy.2017.08.098
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    Cited by:

    1. Hou, Hui & Xu, Tao & Wu, Xixiu & Wang, Huan & Tang, Aihong & Chen, Yangyang, 2020. "Optimal capacity configuration of the wind-photovoltaic-storage hybrid power system based on gravity energy storage system," Applied Energy, Elsevier, vol. 271(C).
    2. Han, Ying & Yang, Hanqing & Li, Qi & Chen, Weirong & Zare, Firuz & Guerrero, Josep M., 2020. "Mode-triggered droop method for the decentralized energy management of an islanded hybrid PV/hydrogen/battery DC microgrid," Energy, Elsevier, vol. 199(C).
    3. Aktaş, Ahmet & Kırçiçek, Yağmur, 2020. "A novel optimal energy management strategy for offshore wind/marine current/battery/ultracapacitor hybrid renewable energy system," Energy, Elsevier, vol. 199(C).
    4. Fathabadi, Hassan, 2019. "Two novel methods for converting the waste heat of PV modules caused by temperature rise into electric power," Renewable Energy, Elsevier, vol. 142(C), pages 543-551.
    5. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    6. Fathabadi, Hassan, 2019. "Recovering waste vibration energy of an automobile using shock absorbers included magnet moving-coil mechanism and adding to overall efficiency using wind turbine," Energy, Elsevier, vol. 189(C).
    7. Assaf, Jihane & Shabani, Bahman, 2018. "Experimental study of a novel hybrid solar-thermal/PV-hydrogen system: Towards 100% renewable heat and power supply to standalone applications," Energy, Elsevier, vol. 157(C), pages 862-876.
    8. Mohammad Junaid Khan & Divesh Kumar & Yogendra Narayan & Hasmat Malik & Fausto Pedro García Márquez & Carlos Quiterio Gómez Muñoz, 2022. "A Novel Artificial Intelligence Maximum Power Point Tracking Technique for Integrated PV-WT-FC Frameworks," Energies, MDPI, vol. 15(9), pages 1-35, May.
    9. Fathabadi, Hassan, 2019. "Combining a proton exchange membrane fuel cell (PEMFC) stack with a Li-ion battery to supply the power needs of a hybrid electric vehicle," Renewable Energy, Elsevier, vol. 130(C), pages 714-724.
    10. Song, Dongran & Liu, Junbo & Yang, Yinggang & Yang, Jian & Su, Mei & Wang, Yun & Gui, Ning & Yang, Xuebing & Huang, Lingxiang & Hoon Joo, Young, 2021. "Maximum wind energy extraction of large-scale wind turbines using nonlinear model predictive control via Yin-Yang grey wolf optimization algorithm," Energy, Elsevier, vol. 221(C).

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