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Charging station Stochastic Programming for Hydrogen/Battery Electric Buses using Multi-Criteria Crow Search Algorithm

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  • Panah, Payam Ghaebi
  • Bornapour, Mosayeb
  • Hemmati, Reza
  • Guerrero, Josep M.

Abstract

Today, the zero-emission transport system is a public will in megacities. A promising alternative among the countermeasures is to employ Battery Electric Buses (BEB) and Fuel-Cell Buses (FCB) at reasonable prices. This paper addresses Multi-product Charging Stations (MCS) in the selected bus terminals for refilling hydrogen and electricity. The core of MCS is constituted of a pair of Electrolyzer/Fuel Cell working back to back by Proton Exchange Membrane (PEM) technology. The innate flexibility in the operation of such a configuration enables for providing regulating services when the market price is soaring. The multi-criteria programming for the hourly schedule in different weather conditions is investigated using the Crow Search Algorithm. The objective is to enhance the daily profit of charging stations through the optimized multi-products/services selection. Uncertainty in wind speed, market price, and electric vehicles is considered in scenarios. The weightings are decided through the Analytic Hierarchy Process (AHP) and Criteria Importance through Inter-criteria Correlation (CRITIC) methods. The superiority of MC-CSA Stochastic Programming is showcased by simulations on a modified 33-bus IEEE distribution system using DK2 (east Denmark) data under subsidized and liberal markets. Regarding the daily profit outcomes, CRITIC was advantageous on windy days when the market prices vary with wind speed whilst AHP was preferred in low wind hours. The most lucrative operations are achievable when the products are fully accepted by regulating markets, BEBs, and FCBs on windy days. The results indicate that the additional remuneration on green hydrogen leaves a deeper impact rather than subsidies on electricity prices for EVs.

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  • Panah, Payam Ghaebi & Bornapour, Mosayeb & Hemmati, Reza & Guerrero, Josep M., 2021. "Charging station Stochastic Programming for Hydrogen/Battery Electric Buses using Multi-Criteria Crow Search Algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    • Handle: RePEc:eee:rensus:v:144:y:2021:i:c:s1364032121003361
    DOI: 10.1016/j.rser.2021.111046
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    Cited by:

    1. Zhang, Hui & Wang, Jiye & Zhao, Xiongwen & Yang, Jingqi & Bu sinnah, Zainab Ali, 2023. "Modeling a hydrogen-based sustainable multi-carrier energy system using a multi-objective optimization considering embedded joint chance constraints," Energy, Elsevier, vol. 278(C).
    2. Ghaffari, Abolfazl & Askarzadeh, Alireza & Fadaeinedjad, Roohollah, 2022. "Optimal allocation of energy storage systems, wind turbines and photovoltaic systems in distribution network considering flicker mitigation," Applied Energy, Elsevier, vol. 319(C).
    3. Fang, Xiaolun & Wang, Yubin & Dong, Wei & Yang, Qiang & Sun, Siyang, 2023. "Optimal energy management of multiple electricity-hydrogen integrated charging stations," Energy, Elsevier, vol. 262(PB).
    4. Witold Torbacki, 2021. "Achieving Sustainable Mobility in the Szczecin Metropolitan Area in the Post-COVID-19 Era: The DEMATEL and PROMETHEE II Approach," Sustainability, MDPI, vol. 13(22), pages 1-25, November.

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