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Reactive rescheduling method for electric vehicles charging in dedicated residential zone parking

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Abstract

Uncertainties are among the biggest challenges to the electric vehicles (EV) charging scheduling problem. In this paper, we propose a predictive-reactive scheduling method to deal with those disturbances. This study is limited to the charging management of the dedicated residential zone parking. Hence the set of charging tasks is finite (static) and the random distributions of the arrival times and the daily charging demands are known. We propose a reactive partial reschedule strategy to tackle the online scheduling problem. The experimentation is set up to measure the performance of the method in two aspects: the objective value minimisation and the stability. Data used to conduct tests are collected throughout our industrial project. The reactive rescheduling method is implementable in standalone schedulers. Also, it is proved to be very efficient to solve the proposed problem.
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hal-02502864 , version 1 (09-03-2020)

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Nhan Quy Nguyen, Farouk Yalaoui, Lionel Amodeo, Hicham Chehade, Pascal Toggenburger. Reactive rescheduling method for electric vehicles charging in dedicated residential zone parking. 2017 IEEE Symposium Series on Computational Intelligence (SSCI), Nov 2017, Honolulu, United States. pp.1-6, ⟨10.1109/SSCI.2017.8285245⟩. ⟨hal-02502864⟩

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