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Fulfilling the electricity demand of electric vehicles in the long term future: An evaluation of centralized and decentralized power supply systems

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  • Brouwer, Anne Sjoerd
  • Kuramochi, Takeshi
  • van den Broek, Machteld
  • Faaij, André

Abstract

Electric vehicles (EVs) are currently seen as an option for a more sustainable transportation sector, but it is not yet clear how to supply them with electricity whilst striving for low costs and low CO2 emissions. Renewable sources can supply electricity with low emissions, but their penetration rate is still insufficient to meet current demand, let alone the extra demand of EVs. A promising option is supply by Combined Heat and Power (CHP) plants with high combined efficiencies, but an in-depth evaluation of the benefits of combining of EVs and CHP plants is still missing. Therefore, this study evaluates the performance of four different types of CHP plants to power electric vehicles, as compared to use of electricity from the grid. The performance of CHP plants is simulated using detailed datasets of the composition of a future power system, the demand for household electricity and heat, and technical specifications of CHP plants and electric vehicles. We find that the lowest abatement costs of 60–190€/tCO2 are achieved with grid electricity based on a low-carbon electricity mix compared to a business-as-usual electricity mix with marginal emissions of 450–500gCO2/kWh. When electricity is supplied by CHP plants, emissions are −1000 to 400gCO2/kWh, and abatement costs are 165–940€/tCO2. We did not observe added benefits of joint implementation of CHP plants and EVs: the timing of CHP electricity supply and EV electricity demand did not match well, and abatement costs were not lowered.

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  • Brouwer, Anne Sjoerd & Kuramochi, Takeshi & van den Broek, Machteld & Faaij, André, 2013. "Fulfilling the electricity demand of electric vehicles in the long term future: An evaluation of centralized and decentralized power supply systems," Applied Energy, Elsevier, vol. 107(C), pages 33-51.
    • Handle: RePEc:eee:appene:v:107:y:2013:i:c:p:33-51
    DOI: 10.1016/j.apenergy.2013.02.005
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    10. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
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    13. Ye Tao & Yupu Chen & Miaohua Huang & Lan Yang, 2023. "Data-Based Orderly Charging Strategy Considering Users’ Charging Choices," Energies, MDPI, vol. 16(19), pages 1-16, October.
    14. Nakamura, Hiroki & Uchida, Akira & Managi, Shunsuke, 2019. "Relationship between community-sharing of new personal transportation and local residents’ daily life consciousness," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 104-110.
    15. Cai, Hua & Hu, Xiaojun & Xu, Ming, 2013. "Impact of emerging clean vehicle system on water stress," Applied Energy, Elsevier, vol. 111(C), pages 644-651.
    16. Thiel, Christian & Nijs, Wouter & Simoes, Sofia & Schmidt, Johannes & van Zyl, Arnold & Schmid, Erwin, 2016. "The impact of the EU car CO2 regulation on the energy system and the role of electro-mobility to achieve transport decarbonisation," Energy Policy, Elsevier, vol. 96(C), pages 153-166.
    17. Khemakhem, Siwar & Rekik, Mouna & Krichen, Lotfi, 2017. "A flexible control strategy of plug-in electric vehicles operating in seven modes for smoothing load power curves in smart grid," Energy, Elsevier, vol. 118(C), pages 197-208.
    18. Schram, Wouter L. & Lampropoulos, Ioannis & van Sark, Wilfried G.J.H.M., 2018. "Photovoltaic systems coupled with batteries that are optimally sized for household self-consumption: Assessment of peak shaving potential," Applied Energy, Elsevier, vol. 223(C), pages 69-81.
    19. Azadeh Ahkamiraad & Yong Wang, 2018. "An Agent-Based Model for Zip-Code Level Diffusion of Electric Vehicles and Electricity Consumption in New York City," Energies, MDPI, vol. 11(3), pages 1-17, March.
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