Short-term forecast of electric vehicle charging station occupancy using big data streaming analysis

Publications - Paper

Short-term forecast of electric vehicle charging station occupancy using big data streaming analysis

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#Electricity Network #Energy Efficiency #Infrastructure #Smart Grids #Sustainable Mobility #Technologies and Components #Transportation, Electric Mobility

Publications - Paper

Short-term forecast of electric vehicle charging station occupancy using big data streaming analysis

This work presents an architecture capable of managing data flows coming from a charging infrastructure, with the final goal of forecasting the availability of electric charging stations a given number of minutes from the current time.

The spread of electric mobility requires THE simultaneous development of charging infrastructure. Collecting and processing information on electric vehicle charging can transform every EV charging station into a valuable source of streaming data. This article presents an architecture capable of managing data flows from a charging infrastructure, with the ultimate goal of forecasting the availability of electric charging stations a given number of minutes from the current time. Both historical data from past charges and real-time data streams are used to train a streaming logistic regression model that takes into account recurring past situations and unexpected real-world events. The findings highlight the importance of constantly updating predictive model parameters to adapt to changing conditions and always provide accurate forecasts.

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Publications - Paper

Short-term forecast of electric vehicle charging station occupancy using big data streaming analysis

Publications - Paper

Short-term forecast of electric vehicle charging station occupancy using big data streaming analysis

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