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Solar parking lot management: An IoT platform for smart charging EV fleets, using real-time data and production forecasts

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  • Varone, Alberto
  • Heilmann, Zeno
  • Porruvecchio, Guido
  • Romanino, Alessandro

Abstract

The fast transition to the electrification of the energy system, combined with an exponential growth of the market share of electric vehicles, is leading to a tight interrelation between electric energy production and transportation, two prominent sectors in fossil fuels consumption and greenhouse gas emissions. Accelerating this process, the management of electric fluxes, aiming at optimizing production and demand coupling, plays a crucial role in reaching the net-zero emission target. The proposed software platform is designed to optimally manage the energy fluxes for a solar powered parking lot, serving a fleet of electric vehicles; the real-time knowledge of energy production and demand, in conjunction with forecasted power generation, allows the maximization of renewable energy self-consumption, thus reducing the exchange with the external grid. The software platform can work either in design mode, allowing the dimensioning of the various parking lot components, or in real-time mode managing instantaneously the energy balance. As a case study, it is tested on the 2019 parking lot mobility data of a research center, assuming a complete transformation of the then existing fleet of employees' cars to electric vehicles. A comparison of the resulting energy flows with those projected by an established commercial tool is performed, as well as a preliminary economic evaluation. Both consistency of the simulation results and favorable economics validate the presented smart charging algorithm and Internet of Things platform for the real-time energy management of a solar parking lot.

Suggested Citation

  • Varone, Alberto & Heilmann, Zeno & Porruvecchio, Guido & Romanino, Alessandro, 2024. "Solar parking lot management: An IoT platform for smart charging EV fleets, using real-time data and production forecasts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    • Handle: RePEc:eee:rensus:v:189:y:2024:i:pa:s1364032123007037
    DOI: 10.1016/j.rser.2023.113845
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    References listed on IDEAS

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