Estimation Model of Total Energy Consumptions of Electrical Vehicles under Different Driving Conditions

Seyed Mahdi Miraftabzadeh, Michela Longo and Federica Foiadelli
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Seyed Mahdi Miraftabzadeh: Department of Energy, Politecnico di Milano, Via La Masa, 34, 20156 Milan, Italy
Michela Longo: Department of Energy, Politecnico di Milano, Via La Masa, 34, 20156 Milan, Italy
Federica Foiadelli: Department of Energy, Politecnico di Milano, Via La Masa, 34, 20156 Milan, Italy

Energies, 2021, vol. 14, issue 4, 1-15

Abstract: The ubiquitous influence of E-mobility, especially electrical vehicles (EVs), in recent years has been considered in the electrical power system in which CO 2 reduction is the primary concern. Having an accurate and timely estimation of the total energy demand of EVs defines the interaction between customers and the electrical power grid, considering the traffic flow, power demand, and available charging infrastructures around a city. The existing EV energy prediction methods mainly focus on a single electric vehicle energy demand; to the best of our knowledge, none of them address the total energy that all EVs consume in a city. This situation motivated us to develop a novel estimation model in the big data regime to calculate EVs’ total energy consumption for any desired time interval. The main contribution of this article is to learn the generic demand patterns in order to adjust the schedules of power generation and prevent any electrical disturbances. The proposed model successfully handled 100 million records of real-world taxi routes and weather condition datasets, demonstrating that energy consumptions are highly correlated to the weekdays’ traffic flow. Moreover, the pattern identifies Thursdays and Fridays as the days of peak energy usage, while weekend days and holidays present the lowest range.

Keywords: electric vehicles (EVs); big data; smart grid; energy demands; estimation model; energy consumption (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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