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Design and optimization of an entirely hybrid renewable energy system (WT/PV/BW/HS/TES/EVPL) to supply electrical and thermal loads with considering uncertainties in generation and consumption

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  • Azad, AmirHossein
  • Shateri, Hossein

Abstract

Renewable energy resources have gotten considerable attention in recent years owing to significant advancements in power electronics technologies, decreased cost of utilizing renewable resources, and increasing concerns about environmental pollutants, particularly in stand-alone applications. Utilizing entirely renewable resources to meet demand has numerous advantages, including lower energy prices, energy price stability, local accessibility, etc. The capability to apply a modified combination of the gray wolf optimization algorithm and the sine–cosine algorithm is evaluated to minimize the levelized cost of energy and the total annualized net present cost (comprising investment, replacement, decommissioning, and operation & maintenance costs) of the proposed system while complying with system constraints and demand requirements. The optimal power planning of a stand-alone hybrid entirely renewable system comprising wind turbines, PV systems, bio-waste units, and storage devices to supply electrical and thermal loads simultaneously was investigated in this paper. A parking lot for electric vehicles is also considered in non-smart and smart charging strategies. In addition, a redefined scenario-based stochastic optimization is utilized to consider uncertainties in electrical and thermal loads, EVs' parameters, and renewable energy resources. The proposed approach is implemented on a small system in Espoo, Finland. The results confirm its efficiency for economically and uninterrupted supplying electrical and thermal demands simultaneously in a stand-alone hybrid system with entirely renewable resources.

Suggested Citation

  • Azad, AmirHossein & Shateri, Hossein, 2023. "Design and optimization of an entirely hybrid renewable energy system (WT/PV/BW/HS/TES/EVPL) to supply electrical and thermal loads with considering uncertainties in generation and consumption," Applied Energy, Elsevier, vol. 336(C).
  • Handle: RePEc:eee:appene:v:336:y:2023:i:c:s0306261923001460
    DOI: 10.1016/j.apenergy.2023.120782
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    References listed on IDEAS

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    1. Das, Barun K. & Hasan, Mahmudul, 2021. "Optimal sizing of a stand-alone hybrid system for electric and thermal loads using excess energy and waste heat," Energy, Elsevier, vol. 214(C).
    2. Sadeghi, Delnia & Hesami Naghshbandy, Ali & Bahramara, Salah, 2020. "Optimal sizing of hybrid renewable energy systems in presence of electric vehicles using multi-objective particle swarm optimization," Energy, Elsevier, vol. 209(C).
    3. Askarzadeh, Alireza, 2017. "Distribution generation by photovoltaic and diesel generator systems: Energy management and size optimization by a new approach for a stand-alone application," Energy, Elsevier, vol. 122(C), pages 542-551.
    4. Voelklein, M.A. & Rusmanis, Davis & Murphy, J.D., 2019. "Biological methanation: Strategies for in-situ and ex-situ upgrading in anaerobic digestion," Applied Energy, Elsevier, vol. 235(C), pages 1061-1071.
    5. Kavousi-Fard, Abdollah & Khodaei, Amin, 2016. "Efficient integration of plug-in electric vehicles via reconfigurable microgrids," Energy, Elsevier, vol. 111(C), pages 653-663.
    6. Yang, Wenjun & Guo, Jia & Vartosh, Aris, 2022. "Optimal economic-emission planning of multi-energy systems integrated electric vehicles with modified group search optimization," Applied Energy, Elsevier, vol. 311(C).
    7. Cai, Wei & Li, Xing & Maleki, Akbar & Pourfayaz, Fathollah & Rosen, Marc A. & Alhuyi Nazari, Mohammad & Bui, Dieu Tien, 2020. "Optimal sizing and location based on economic parameters for an off-grid application of a hybrid system with photovoltaic, battery and diesel technology," Energy, Elsevier, vol. 201(C).
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