Abstract
Due to the increasing battery capacity of electric vehicles, European standard electricity socket-outlets at households are not enough for a full charge cycle overnight. Hence, people tend to install (semi-) fast charging wall-boxes (up to 22 kW) which can cause critical peak loads and voltage issues whenever many electric vehicles charge simultaneously in the same area.This paper proposes a centralized charging capacity allocation mechanism based on queuing systems that takes care of grid limitations and charging requirements of electric vehicles, including legacy charging control protocol restrictions. The proposed allocation mechanism dynamically updates the weights of the charging services in discrete time steps, such that electric vehicles with shorter remaining charging time and higher energy requirement are preferred against others. Furthermore, a set of metrics that determine the service quality for charging as a service is introduced. Among others, these metrics cover the ratio of charged energy to the required energy, the charging power variation during the charging process, as well as whether the upcoming trip is feasible or not. The proposed algorithm outperforms simpler scheduling policies in terms of achieved mean quality of service metric and fairness index in a co-simulation of the IEEE European low voltage grid configured with charging service requirements extracted from a mobility survey.
Highlights
Electric Vehicles (EVs) are seen as one of the key means to reduce the global greenhouse gas emission and air pollution in the transportation sector, especially with the growing use of renewable energy
We assume that most people will not change their driving behavior drastically when switching from combustion engine vehicles to electric vehicles in the future
Conclusion and future work This paper presented a set of Quality of Service (QoS) and Quality of Experience (QoE) metrics that can be used to evaluate EV charging services
Summary
Electric Vehicles (EVs) are seen as one of the key means to reduce the global greenhouse gas emission and air pollution in the transportation sector, especially with the growing use of renewable energy. Charging control algorithms need to achieve a high Quality of Service (QoS) and Quality of Experience (QoE) in times of grid congestion while ensuring fairness between parallel charging services to retain customers confidence. In this context, electricity (in the form of available grid capacity) can be seen as a limited resource that has to be shared by several end consumers in the power grid. The received charging current is dynamically adjusted to the grid state and is balanced among charging services to ensure QoS, QoE and fairness
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