Fuzzy logic-based electric vehicle charging management considering charging urgency
Department of Mechanical Engineering-Engineering Mechanics
This paper presents a decentralized electric vehicle (EV) charging/discharging and rate control approach based on the fuzzy logic control (FLC). Three factors are considered in the FLC control scheme, which are EV users' charging urgency, the voltage deviation of grid node, and the pricing signals from utilities. The control decisions of charging, discharging, and rate are determined based on these three factors with the objectives to meet the EV owner's charging requirements, reduce the EV owners' charging cost, and maintain the distribution system nodal voltages within acceptable limits. The performance of the presented FLC-based EV charging management is evaluated in a modified radial IEEE-33 distribution network. The control performance of the FLC is compared to the immediate charge (IC), average charge rate (ACR) and randomly delayed charging (RDC) methods. In addition, the FLC control performance is evaluated with the time of use (TOU) tariff, TOU + critical peak price (CPP) tariff, and real-time pricing (RTP). The comparison results show that the FLC strategy outperforms IC, ACR and RDC. By integrating price signals, the FLC control performance is further improved. The integrated methods can eliminate voltage violations, prevent the overloading caused by the EV charging, meet EV users' charging needs, and ensure the reduction of charging cost.
2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)
Fuzzy logic-based electric vehicle charging management considering charging urgency.
2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), 3441-3446.
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