Optimal Strategy to Exploit the Flexibility of an Electric Vehicle Charging Station

Cesar Diaz-Londono, Luigi Colangelo, Fredy Ruiz, Diego Patino, Carlo Novara and Gianfranco Chicco
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Cesar Diaz-Londono: Departamento de Electrónica, Pontificia Universidad Javeriana, Bogotá 110231, Colombia
Luigi Colangelo: Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, 10129 Torino, Italy
Fredy Ruiz: Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, 10129 Torino, Italy
Diego Patino: Departamento de Electrónica, Pontificia Universidad Javeriana, Bogotá 110231, Colombia
Carlo Novara: Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, 10129 Torino, Italy
Gianfranco Chicco: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, 10129 Torino, Italy

Energies, 2019, vol. 12, issue 20, 1-29

Abstract: The increasing use of electric vehicles connected to the power grid gives rise to challenges in the vehicle charging coordination, cost management, and provision of potential services to the grid. Scheduling of the power in an electric vehicle charging station is a quite challenging task, considering time-variant prices, customers with different charging time preferences, and the impact on the grid operations. The latter aspect can be addressed by exploiting the vehicle charging flexibility. In this article, a specific definition of flexibility to be used for an electric vehicle charging station is provided. Two optimal charging strategies are then proposed and evaluated, with the purpose of determining which strategy can offer spinning reserve services to the electrical grid, reducing at the same time the operation costs of the charging station. These strategies are based on a novel formulation of an economic model predictive control algorithm, aimed at minimising the charging station operation cost, and on a novel formulation of the flexibility capacity maximisation, while reducing the operation costs. These formulations incorporate the uncertainty in the arrival time and state of charge of the electric vehicles at their arrival. Both strategies lead to a considerable reduction of the costs with respect to a simple minimum time charging strategy, taken as the benchmark. In particular, the strategy that also accounts for flexibility maximisation emerges as a new tool for maintaining the grid balance giving cost savings to the charging stations.

Keywords: electric vehicle; flexible demand; model predictive control; spinning reserve (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: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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