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Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm

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  • Al Dawsari, Saleh
  • Anayi, Fatih
  • Packianather, Michael

Abstract

The global energy crisis, particularly in isolated and remote regions, has increased interest in renewable energy sources (RESs) to meet growing energy demands. Integrating RESs with energy storage systems offers a promising solution to mitigate fluctuations and intermittency, but concerns about cost and reliability remain. This study explores the optimal design of various microgrid configurations, combining photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS), and diesel generator (DG) systems for Najran city, Saudi Arabia, via real-world meteorological and load demand data. The Dwarf Mongoose Optimization Algorithm (DMOA), alongside the salp swarm algorithm (SSA) and whale optimization algorithm (WOA), was applied to minimize the levelized cost of energy (LCOE) while improving system reliability. The results demonstrate that the PV/BESS configuration, although cost-effective with an LCOE of 0.038 USD/kWh, fail to meet reliability constraints with a loss of power supply probability (LPSP) of 0.679. In contrast, the PV, WT, BESS, and DG configurations achieved an LPSP of 1.9 × 10^--8% with an LCOE of 0.199 USD/kWh, offering a robust and reliable solution for the region's energy needs. This paper presents a novel application of the DMOA for optimizing hybrid renewable energy systems, demonstrating its effectiveness in achieving a balance between cost and reliability. This strategy provides a viable approach for sustainable energy planning in similar regions facing energy challenges.

Suggested Citation

  • Al Dawsari, Saleh & Anayi, Fatih & Packianather, Michael, 2024. "Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224034315
    DOI: 10.1016/j.energy.2024.133653
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    References listed on IDEAS

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    1. Mengjun Ming & Rui Wang & Yabing Zha & Tao Zhang, 2017. "Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm," Energies, MDPI, vol. 10(5), pages 1-15, May.
    2. Toopshekan, Ashkan & Ahmadi, Esmaeil & Abedian, Ali & Vaziri Rad, Mohammad Amin, 2024. "Techno-economic analysis, optimization, and dispatch strategy development for renewable energy systems equipped with Internet of Things technology," Energy, Elsevier, vol. 296(C).
    3. Jabeen, Gul & Ahmad, Munir & Zhang, Qingyu, 2021. "Perceived critical factors affecting consumers’ intention to purchase renewable generation technologies: Rural-urban heterogeneity," Energy, Elsevier, vol. 218(C).
    4. Singh, Poonam & Pandit, Manjaree & Srivastava, Laxmi, 2023. "Multi-objective optimal sizing of hybrid micro-grid system using an integrated intelligent technique," Energy, Elsevier, vol. 269(C).
    5. Güven, Aykut Fatih & Yörükeren, Nuran & Samy, Mohamed Mahmoud, 2022. "Design optimization of a stand-alone green energy system of university campus based on Jaya-Harmony Search and Ant Colony Optimization algorithms approaches," Energy, Elsevier, vol. 253(C).
    6. Al Busaidi, Ahmed Said & Kazem, Hussein A & Al-Badi, Abdullah H & Farooq Khan, Mohammad, 2016. "A review of optimum sizing of hybrid PV–Wind renewable energy systems in oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 185-193.
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    1. Mohammed Alenezi & Fatih Anayi & Michael Packianather & Mokhtar Shouran, 2025. "A Hybrid Machine Learning Framework for Early Fault Detection in Power Transformers Using PSO and DMO Algorithms," Energies, MDPI, vol. 18(8), pages 1-23, April.

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