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A reliable methodology based on mine blast optimization algorithm for optimal sizing of hybrid PV-wind-FC system for remote area in Egypt

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  • Fathy, Ahmed

Abstract

In this paper, a reliable methodology incorporated mine blast algorithm (MBA) is applied to solve the optimal sizing of a hybrid system consisting of photovoltaic modules, wind turbines and fuel cells (PV/WT/FC) to meet a certain load of remote area in Egypt. The main objective of the optimal sizing process is to achieve the minimum annual cost of the system with load coverage. The sizing process is performed optimally based on real measured data for solar radiation, ambient temperature and wind velocity recorded by the solar radiation and meteorological station located at national research institute of astronomy and geophysics, Helwan city, Egypt. Three other meta-heuristic optimization techniques, particle swarm optimization, cuckoo search and artificial bee colony are applied to solve the problem and the results are compared with those obtained by the proposed methodology. A power management strategy that regulates the power flow between each system component is also presented. The obtained results show that; applying the proposed methodology will save about 24.8% in the annual total cost of the proposed system compared with PSO, 8.956% compared with CS and 11.5576% compared with ABC. The proposed algorithm based on MBA is candidate for solving the presented optimization problem of optimal sizing the hybrid PV/WT/FC system.

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  • Fathy, Ahmed, 2016. "A reliable methodology based on mine blast optimization algorithm for optimal sizing of hybrid PV-wind-FC system for remote area in Egypt," Renewable Energy, Elsevier, vol. 95(C), pages 367-380.
    • Handle: RePEc:eee:renene:v:95:y:2016:i:c:p:367-380
    DOI: 10.1016/j.renene.2016.04.030
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    8. Hosein Kalantari & Seyed Ali Ghoreishi-Madiseh & Agus P. Sasmito, 2020. "Hybrid Renewable Hydrogen Energy Solution for Application in Remote Mines," Energies, MDPI, vol. 13(23), pages 1-22, December.
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    16. Xiaohang Wang & Wentong Chong & Kokhoe Wong & Saihin Lai & Liphuat Saw & Xianbo Xiang & Chin-Tsan Wang, 2019. "Preliminary Techno–Environment–Economic Evaluation of an Innovative Hybrid Renewable Energy Harvester System for Residential Application," Energies, MDPI, vol. 12(8), pages 1-28, April.
    17. Alsagri, Ali Sulaiman & Alrobaian, Abdulrahman A. & Nejlaoui, Mohamed, 2021. "Techno-economic evaluation of an off-grid health clinic considering the current and future energy challenges: A rural case study," Renewable Energy, Elsevier, vol. 169(C), pages 34-52.
    18. Liu, Zhijian & Li, Ying & Fan, Guangyao & Wu, Di & Guo, Jiacheng & Jin, Guangya & Zhang, Shicong & Yang, Xinyan, 2022. "Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios," Energy, Elsevier, vol. 247(C).
    19. Toopshekan, Ashkan & Yousefi, Hossein & Astaraei, Fatemeh Razi, 2020. "Technical, economic, and performance analysis of a hybrid energy system using a novel dispatch strategy," Energy, Elsevier, vol. 213(C).
    20. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    21. Nadjemi, O. & Nacer, T. & Hamidat, A. & Salhi, H., 2017. "Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1352-1365.
    22. Sadeghi, Saber & Askari, Ighball Baniasad, 2019. "Prefeasibility techno-economic assessment of a hybrid power plant with photovoltaic, fuel cell and Compressed Air Energy Storage (CAES)," Energy, Elsevier, vol. 168(C), pages 409-424.
    23. Buonomano, Annamaria & Calise, Francesco & d'Accadia, Massimo Dentice & Vicidomini, Maria, 2018. "A hybrid renewable system based on wind and solar energy coupled with an electrical storage: Dynamic simulation and economic assessment," Energy, Elsevier, vol. 155(C), pages 174-189.
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