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Optimum Size of Hybrid Renewable Energy System to Supply the Electrical Loads of the Northeastern Sector in the Kingdom of Saudi Arabia

Author

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  • Sulaiman Alshammari

    (Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

  • Ahmed Fathy

    (Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
    Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt)

Abstract

Due to the unpredictable nature of renewable sources such as sun and wind, the integration of such sources to a grid is complicated. However, a hybrid renewable energy system (HRES) can solve this problem. Constructing a reliable HRES in remote areas is essential. Therefore, this paper proposes a new methodology incorporating a crow search algorithm (CSA) for optimizing the scale of an HRES installed in a remote area. The constructed system comprises photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generators (DGs). The target is to achieve the most economical and efficient use of renewable energy sources (RESs). The CSA is used as it is simple in implementation, it only requires a few parameters, and it has a high flexibility. The designed system is constructed to serve an electrical load installed in the northeastern region of the Kingdom of Saudi Arabia. The load data are provided by the Saudi Electricity Company, including those of the Aljouf region (Sakaka, Alqurayyat, Tabarjal, Dumat Aljandal, and its villages) and the northern border region (Arar, Tarif, Rafha, and its affiliated villages). The temperature, irradiance, and wind speed of the Aljouf region (latitude 29.764° and longitude 40.01°) are collected from the National Aeronautics and Space Administration (NASA) from 1 January to 31 December 2020. Three design factors are considered: the PV number, the WT number, and the number of days of battery autonomy (AD). We compared our results to the reported approaches of an elephant herding optimizer (EHO), a grasshopper optimization algorithm (GOA), a Harris hawks optimizer (HHO), a seagull optimization algorithm (SOA), and a spotted hyena optimizer (SHO). Moreover, the loss of power supply probability (LPSP) is calculated to assess the constructed system’s reliability. The proposed COA succeeded in achieving the best fitness values of 0.03883 USD/kWh, 0.03863 USD/kWh, and 0.04585 USD/kWh for PV/WT/battery, PV/battery, and WT/battery systems, respectively. The obtained results confirmed the superiority of the proposed approach in providing the best configuration of an HRES compared to the others.

Suggested Citation

  • Sulaiman Alshammari & Ahmed Fathy, 2022. "Optimum Size of Hybrid Renewable Energy System to Supply the Electrical Loads of the Northeastern Sector in the Kingdom of Saudi Arabia," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13274-:d:943338
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    References listed on IDEAS

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    1. Kaabeche, A. & Belhamel, M. & Ibtiouen, R., 2011. "Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system," Energy, Elsevier, vol. 36(2), pages 1214-1222.
    2. González, Arnau & Riba, Jordi-Roger & Rius, Antoni & Puig, Rita, 2015. "Optimal sizing of a hybrid grid-connected photovoltaic and wind power system," Applied Energy, Elsevier, vol. 154(C), pages 752-762.
    3. El-Hefnawi, Said H., 1998. "Photovoltaic diesel-generator hybrid power system sizing," Renewable Energy, Elsevier, vol. 13(1), pages 33-40.
    4. 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.
    5. Shafiqur Rehman & Md. Mahbub Alam & Luai M. Alhems & M. Mujahid Rafique, 2018. "Horizontal Axis Wind Turbine Blade Design Methodologies for Efficiency Enhancement—A Review," Energies, MDPI, vol. 11(3), pages 1-34, February.
    6. Arnau González & Jordi-Roger Riba & Antoni Rius, 2015. "Optimal Sizing of a Hybrid Grid-Connected Photovoltaic–Wind–Biomass Power System," Sustainability, MDPI, vol. 7(9), pages 1-20, September.
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    4. 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).

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