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The development of a techno-economic model for assessment of cost of energy storage for vehicle-to-grid applications in a cold climate

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  • Rahman, Md Mustafizur
  • Gemechu, Eskinder
  • Oni, Abayomi Olufemi
  • Kumar, Amit

Abstract

With the growing number of electric vehicles in the transportation sector aimed at reducing greenhouse gas emissions, vehicle-to-grid (V2G) technology can play an important role in stabilizing electricity grids. An electric vehicle could be used as an energy storage system (ESS) that provides electricity to the grid when required. Several studies have evaluated the economic performance of different stationary ESSs; however, research that focuses on the V2G technology economic feasibility is scarce for cold climates. In this study, an engineering principles-based techno-economic model was developed to estimate the levelized cost of storage (LCOS) of V2G technology for energy arbitrage and frequency regulation. A model was also developed to predict the available energy and cost for V2G applications at various temperatures. Sensitivity and uncertainty analyses were performed to identify the key parameters that drive economic performance. The base case values of the LCOS are $230.88 and $329.93/MWh for energy arbitrage and frequency regulation, respectively. The key parameters are ambient temperature, battery cycle life, distance traveled per day, battery depth of discharge, battery capital cost, and electricity price. Considering the variabilities in these parameters, the probable ranges of the LCOS are $158-$290/MWh and $244-$485/MWh for energy arbitrage and frequency regulation, respectively.

Suggested Citation

  • Rahman, Md Mustafizur & Gemechu, Eskinder & Oni, Abayomi Olufemi & Kumar, Amit, 2023. "The development of a techno-economic model for assessment of cost of energy storage for vehicle-to-grid applications in a cold climate," Energy, Elsevier, vol. 262(PA).
    • Handle: RePEc:eee:energy:v:262:y:2023:i:pa:s0360544222022800
    DOI: 10.1016/j.energy.2022.125398
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    3. Terkes, Musa & Arikan, Oktay & Gokalp, Erdin, 2024. "The effect of electric vehicle charging demand variability on optimal hybrid power systems with second-life lithium-ion or fresh Na–S batteries considering power quality," Energy, Elsevier, vol. 288(C).
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    6. Yang, Wenqiang & Zhu, Xinxin & Xiao, Qinge & Yang, Zhile, 2023. "Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles," Energy, Elsevier, vol. 282(C).

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