Abstract

ABSTRACT This paper presents a coordinated plug-in electric vehicle (PEV) charging scheme in the presence of conservation voltage reduction (CVR) with a possibility of network re-configuration in a half-hourly based tariff environment. The information of the arrived PEVs in time slot “t” are gathered in a centralized manner, including initial and desired state of charge (SOC), rating of PEV charger, and arrival and departure times. In addition, the load forecasted data of all the nodes are also collected. A linear programming (LP) based intelligent charging framework is developed whereby an optimal global solution for EV charging is obtained that tends to minimize the charging cost, and the schedule is dispatched to all the PEVs. At first, PEV charging cost is minimized using the existing time of use (TOU) based tariff structure. After that, the charging schedule is carried out under the same TOU tariff structure but on a re-configured network with and without CVR deployment. The proposed charging strategy through re-configuration of the distribution network under CVR is implemented on a modified IEEE-33 bus test system. The results obtained from the simulation show that the proposed PEV charging scheme through network re-configuration under a TOU-based tariff structure considerably reduces the charging cost by 55.8% compared to uncoordinated charging. However, a 50.2% cost reduction is achieved in the absence of network re-configuration. Therefore, the proposed PEV charging through network re-configuration under a TOU-based tariff is more effective in cost reduction. Further, investigations were carried out on EV charging through network re-configuration under TOU-based tariff and CVR deployment. It was observed that the PEV charging cost was reduced by 51.3% compared to uncoordinated charging, where higher cost benefits were obtained through the reduction in energy consumed by constant impedance loads. It has been further observed that the proposed scheme effectively flattens the load profile by clipping the peak and filling the valley load.

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