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Prospective hydrogen-based microgrid systems for optimal leverage via metaheuristic approaches

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  • Abo-Elyousr, Farag K.
  • Guerrero, Josep M.
  • Ramadan, Haitham S.

Abstract

The paper proposes a hybrid microgrid (HMG) system with solar modules and wind turbines as primary energy sources and a diesel engine as backup. Meanwhile, the hydrogen energy storage system (HySS) is utilized as energy storage. Firstly, by reducing the levelized cost of energy (COE), this study presents the optimal size and configuration of various renewable and distributed energy resources in HMG systems. Secondly, two novel modified hybridized particle swarm optimization (PSO) and ant colony optimization (ACO) are developed, namely, ACO initialized PSO and ACO updated PSO. The optimal simulation results using PSO and ACO metaheuristic technique either individually or hybridized are compared in terms of primarily minimizing the levelized COE and achieving short execution time. Thirdly, to verify the geographical-independency of the integration of HySS for producing onsite green hydrogen locally, the estimation performance is examined for three different locations in Egypt, Mozambique and Denmark respectively using hourly meteorological and load data in 2019. Sensitivity and effectiveness analysis are carried out to highlight the major parameters that impact HySS incorporation. Finally, the system readiness level together with the different hydrogen, economy barriers constraints, limitations and risks are investigated based on the technology readiness level and the integration readiness level indices. The simulation results demonstrate the superiority of the ACO updated PSO optimization algorithm towards minimizing the levelized COE in the different regions. In the developing countries, the salvage market supports HySS integration. At system readiness levels range between 0.65 and 0.94, versatile HySS integration is verified.

Suggested Citation

  • Abo-Elyousr, Farag K. & Guerrero, Josep M. & Ramadan, Haitham S., 2021. "Prospective hydrogen-based microgrid systems for optimal leverage via metaheuristic approaches," Applied Energy, Elsevier, vol. 300(C).
  • Handle: RePEc:eee:appene:v:300:y:2021:i:c:s030626192100787x
    DOI: 10.1016/j.apenergy.2021.117384
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    References listed on IDEAS

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    2. Shen, Xiaojun & Li, Xingyi & Yuan, Jiahai & Jin, Yu, 2022. "A hydrogen-based zero-carbon microgrid demonstration in renewable-rich remote areas: System design and economic feasibility," Applied Energy, Elsevier, vol. 326(C).
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    4. Gordon, Joel A. & Balta-Ozkan, Nazmiye & Nabavi, Seyed Ali, 2023. "Socio-technical barriers to domestic hydrogen futures: Repurposing pipelines, policies, and public perceptions," Applied Energy, Elsevier, vol. 336(C).
    5. Yin, Linfei & Cao, Xinghui & Liu, Dongduan, 2023. "Weighted fully-connected regression networks for one-day-ahead hourly photovoltaic power forecasting," Applied Energy, Elsevier, vol. 332(C).
    6. Hongshan Zhao & Junyang Xu & Kunyu Xu & Jingjie Sun & Yufeng Wang, 2022. "Optimal Allocation Method of Source and Storage Capacity of PV-Hydrogen Zero Carbon Emission Microgrid Considering the Usage Cost of Energy Storage Equipment," Energies, MDPI, vol. 15(13), pages 1-18, July.
    7. Mohseni, Soheil & Khalid, Roomana & Brent, Alan C., 2023. "Stochastic, resilience-oriented optimal sizing of off-grid microgrids considering EV-charging demand response: An efficiency comparison of state-of-the-art metaheuristics," Applied Energy, Elsevier, vol. 341(C).

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