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Techno-economic modelling for energy cost minimisation of a university campus to support electric vehicle charging with photovoltaic capacity optimisation

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  • Wu, Yan
  • Aziz, Syed Mahfuzul
  • Haque, Mohammed H.

Abstract

Workplace charging of Electric Vehicles (EV) is a promising approach for transport decarbonization while addressing issues emerging from renewable energy growth. For workplaces, the decision to invest in EV charging infrastructure depends on the overall cost of providing this service. This study proposes a novel modelling approach to minimize the net annual energy cost of a university campus providing EV charging service using optimum capacity solar photovoltaic (PV) systems. The research includes an innovative approach to determine the campus EV charging demand and a novel net annual energy cost minimisation method combining PV size optimisation and EV charging control. A comprehensive analysis is presented to illustrate the influence of EV penetration, charging strategy, charging fees, charger cost and PV generation cost on the campus net annual energy cost. The influence of these parameters are also analysed on the optimal PV capacity, power and energy demand, and PV self-utilisation. Results show that, by using the proposed method, for 25 % EV penetration, the campus's peak demand is reduced by around 12 % and net annual energy cost is reduced by up to 9.2 % while providing free EV charging. The net annual energy cost reduction increases to over 20 % for 100 % EV penetration.

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  • Wu, Yan & Aziz, Syed Mahfuzul & Haque, Mohammed H., 2023. "Techno-economic modelling for energy cost minimisation of a university campus to support electric vehicle charging with photovoltaic capacity optimisation," Renewable Energy, Elsevier, vol. 219(P1).
    • Handle: RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123013423
    DOI: 10.1016/j.renene.2023.119427
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    References listed on IDEAS

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    1. Husein, Munir & Chung, Il-Yop, 2018. "Optimal design and financial feasibility of a university campus microgrid considering renewable energy incentives," Applied Energy, Elsevier, vol. 225(C), pages 273-289.
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    Cited by:

    1. Lazaroiu, Alexandra Catalina & Panait, Cornel & Serițan, George & Popescu, Claudia Laurenta & Roscia, Mariacristina, 2024. "Maximizing renewable energy and storage integration in university campuses," Renewable Energy, Elsevier, vol. 230(C).
    2. Wu, Yan & Aziz, Syed Mahfuzul & Haque, Mohammed H., 2024. "Vehicle-to-home operation and multi-location charging of electric vehicles for energy cost optimisation of households with photovoltaic system and battery energy storage," Renewable Energy, Elsevier, vol. 221(C).
    3. Zhang, Chengyu & Rezgui, Yacine & Luo, Zhiwen & Jiang, Ben & Zhao, Tianyi, 2024. "Simultaneous community energy supply-demand optimization by microgrid operation scheduling optimization and occupant-oriented flexible energy-use regulation," Applied Energy, Elsevier, vol. 373(C).

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