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Modeling and allocation of the Electric vehicles Charging Stations (EVCS) within the distribution network, as per the growing use of Electric vehicles (EVs) is a challenging task. In this paper, to manage the EVCS, first, with the aim of peak shaving, valley filling, and flattening the load curve of the network, the optimal planning of EV&#x2019;s charging/discharging is devised. In this regard, after modeling involving random variables, a novel hybrid method, based on the Multi Objective Particle Swarm Optimization (MOPSO) optimization algorithm and sequential Monte Carlo simulation is presented. The purpose of the presented optimal charge/discharge schedule is to control the rate and time of charging/discharging of EVs. In the proposed model, various battery operation strategies, including Uncontrolled Charging Mode (UCM), Controlled Charging Mode (CCM), and Smart Charge/Discharge Mode (SCDM) are also considered. In the next step, in order to implement the charge/discharge schedule of the EVCS profitably, a new formulation is presented for the allocation of two EVCSs (administrative and residential EVCS). In the proposed formulation, various objective functions such as power loss reduction, reducing power purchases from the upstream network, reducing voltage deviation in buses, improving reliability is addressed. Moreover, to incentivize the owner to construct the EVCS with adopted charging/discharging schedule, the optimal profits sharing between Distribution System Operator (DSO) and EVCS owner is also performed. The proposed formulation is applied to a standard network (IEEE 69 buses) and encouraging results are achieved.

Optimal Allocation of Electric Vehicle Charging Stations With Adopted Smart Charging/Discharging Schedule