Preprint Article Version 1 This version is not peer-reviewed

Elastic Charging Service Fee Based Load Guiding Strategy for Fast Charging Station

Version 1 : Received: 20 April 2017 / Approved: 20 April 2017 / Online: 20 April 2017 (07:58:13 CEST)

A peer-reviewed article of this Preprint also exists.

Su, S.; Zhao, H.; Zhang, H.; Lin, X. An Elastic Charging Service Fee-Based Load Guiding Strategy for Fast Charging Stations. Energies 2017, 10, 672. Su, S.; Zhao, H.; Zhang, H.; Lin, X. An Elastic Charging Service Fee-Based Load Guiding Strategy for Fast Charging Stations. Energies 2017, 10, 672.

Journal reference: Energies 2017, 10, 672
DOI: 10.3390/en10050672

Abstract

Compared with the traditional slow charging loads, random integration of large scale fast charging loads will exert more serious impacts on the security of power network operation. Besides, to maximize social benefits, effective scheduling strategy guiding fast charging behaviors should be formulated rather than simply increasing infrastructure construction investments on the power grid. This paper has analyzed the charging users’ various responses to the elastic charging service fee, introduced the index of charging balance degree to a target region by considering the influence of fast charging loads on power grid. Then, a multi-objective optimization model of the fast charging service fee is constructed, whose service fee can be further optimized by employing fuzzy programming method. Therefore, both users’ satisfaction degree and the equilibrium of charging loads can be maintained simultaneously by guiding EVs to different fast charging stations reasonably. The simulation results demonstrate the effectiveness of proposed dynamic charging service pricing and the proposed fast charging load guidance strategy.

Subject Areas

EV; fast charging; real-time pricing; ordered charging; charging balance degree; Users’ satisfaction; behavior characteristics; navigation strategy

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