This paper explores the use of piecewise linear regression for modeling and analyzing electric vehicle charging curves, with a focus on optimizing charging efficiency for Charging Point Operator (CPO) and energy providers. Through a case study, we show the effectiveness of this method in informing more efficient Vehicle-to-Infrastructure (V2I) strategies and contributing to predictive Vehicle-to-Grid (V2G) design. A method is proposed to group and characterize charging stages, improving the design of charging infrastructure for more sustainable electric vehicles integration.

Use of Piecewise Linear Regression to Model and Analyze EV Charging Curve

Martini D.;Saldarini A.;Brenna M.;Longo M.;
2023-01-01

Abstract

This paper explores the use of piecewise linear regression for modeling and analyzing electric vehicle charging curves, with a focus on optimizing charging efficiency for Charging Point Operator (CPO) and energy providers. Through a case study, we show the effectiveness of this method in informing more efficient Vehicle-to-Infrastructure (V2I) strategies and contributing to predictive Vehicle-to-Grid (V2G) design. A method is proposed to group and characterize charging stages, improving the design of charging infrastructure for more sustainable electric vehicles integration.
2023
Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023
979-8-3503-4743-2
charging curve
charging infrastructure
data-driven
electric vehicle (EV)
energy provider
piecewise linear regression
V2G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1249480
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