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Sizing and Design of a PV-Wind-Fuel Cell Storage System Integrated into a Grid Considering the Uncertainty of Load Demand Using the Marine Predators Algorithm

Author

Listed:
  • Fayza S. Mahmoud

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61111, Egypt)

  • Ashraf M. Abdelhamid

    (Communications and Electronics Engineering Department, College of Engineering, Umm Al-Qura University, Al-Lith Branch, Makkah 24382, Saudi Arabia)

  • Ameena Al Sumaiti

    (Advanced Power and Energy Center, Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi 127788, United Arab Emirates)

  • Abou-Hashema M. El-Sayed

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61111, Egypt)

  • Ahmed A. Zaki Diab

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61111, Egypt)

Abstract

In this paper, the utility grid is integrated with hybrid photovoltaic (PV)/wind/fuel cells to overcome the unavailability of the grid and the single implementation of renewable energy. The main purpose of this study is smart management of hydrogen storage tanks and power exchange between the hybrid renewable energy and the grid to minimize the total cost of the hybrid system and load uncertainties. PV and wind act as the main renewable energy sources, whereas fuel cells act as auxiliary sources designed to compensate for power variations and to ensure continuous power flow to the load. The grid is considered a backup system that works when hybrid renewable energy and fuel cells are unavailable. In this study, the optimal size of the components of the hybrid energy system is introduced using two methods: the marine predators’ algorithm (MPA) and the seagull optimization algorithm (SOA). The optimal sizing problem is also run accounting for the uncertainty in load demand. The results obtained from the proposed optimization are given with and without uncertainty in load demand. The simulation results of the hybrid system without uncertainty demonstrate the superiority of the MPA compared with SOA. However, in the case of load uncertainty, the simulation results (the uncertainty) are given using the MPA optimization technique with +5%, +10%, and +15% uncertainty in load, which showed that the net present cost and purchase energy are increased with uncertainty.

Suggested Citation

  • Fayza S. Mahmoud & Ashraf M. Abdelhamid & Ameena Al Sumaiti & Abou-Hashema M. El-Sayed & Ahmed A. Zaki Diab, 2022. "Sizing and Design of a PV-Wind-Fuel Cell Storage System Integrated into a Grid Considering the Uncertainty of Load Demand Using the Marine Predators Algorithm," Mathematics, MDPI, vol. 10(19), pages 1-26, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3708-:d:938078
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    References listed on IDEAS

    as
    1. Rajanna, S. & Saini, R.P., 2016. "Modeling of integrated renewable energy system for electrification of a remote area in India," Renewable Energy, Elsevier, vol. 90(C), pages 175-187.
    2. Mohammad Junaid Khan & Lini Mathew & Majed A. Alotaibi & Hasmat Malik & Mohammed E. Nassar, 2022. "Fuzzy-Logic-Based Comparative Analysis of Different Maximum Power Point Tracking Controllers for Hybrid Renewal Energy Systems," Mathematics, MDPI, vol. 10(3), pages 1-28, February.
    3. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Yusta-Loyo, José M. & Domínguez-Navarro, José A. & Ramírez-Rosado, Ignacio J. & Lujano, Juan & Aso, Ismael, 2011. "Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV–wind–diesel systems with batteries storage," Applied Energy, Elsevier, vol. 88(11), pages 4033-4041.
    4. Ahmed A. Zaki Diab & Ali M. El-Rifaie & Magdy M. Zaky & Mohamed A. Tolba, 2022. "Optimal Sizing of Stand-Alone Microgrids Based on Recent Metaheuristic Algorithms," Mathematics, MDPI, vol. 10(1), pages 1-25, January.
    5. Chandra Mouli, G.R. & Bauer, P. & Zeman, M., 2016. "System design for a solar powered electric vehicle charging station for workplaces," Applied Energy, Elsevier, vol. 168(C), pages 434-443.
    6. Ahn, Hyeunguk & Rim, Donghyun & Pavlak, Gregory S. & Freihaut, James D., 2019. "Uncertainty analysis of energy and economic performances of hybrid solar photovoltaic and combined cooling, heating, and power (CCHP + PV) systems using a Monte-Carlo method," Applied Energy, Elsevier, vol. 255(C).
    7. Malheiro, André & Castro, Pedro M. & Lima, Ricardo M. & Estanqueiro, Ana, 2015. "Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems," Renewable Energy, Elsevier, vol. 83(C), pages 646-657.
    8. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    9. Yan, Jie & Zhang, Hao & Liu, Yongqian & Han, Shuang & Li, Li, 2019. "Uncertainty estimation for wind energy conversion by probabilistic wind turbine power curve modelling," Applied Energy, Elsevier, vol. 239(C), pages 1356-1370.
    10. Yang, Hongxing & Wei, Zhou & Chengzhi, Lou, 2009. "Optimal design and techno-economic analysis of a hybrid solar-wind power generation system," Applied Energy, Elsevier, vol. 86(2), pages 163-169, February.
    11. Kaiwen Li & Yuanming Song & Rui Wang, 2022. "Multi-Objective Optimal Sizing of HRES under Multiple Scenarios with Undetermined Probability," Mathematics, MDPI, vol. 10(9), pages 1-19, May.
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