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Electrical vehicles (EVs) are among the fastest-growing electrical loads that change both temporally and spatially on distribution networks. The large-scale integration of EVs equipped with power electronic-based chargers into distribution networks, to meet new electrical load demands, can cause instability and power quality issues. Moreover, the absence of control strategies for the smart charging and discharging of EVs at their plug-in intervals poses serious challenges to them. Accordingly, the implementation of controlled charging/discharging scheduling of EV batteries along with the use of charger capabilities, such as reactive power support, is a must. Against this background, this paper introduces an integrated model to solve the problem of simultaneous active and reactive power management in distribution networks subject to network operation constraints imposed by EV batteries and chargers. To this end, this problem is modeled as an optimization problem. In this respect, minimization of the costs associated with power generation and losses and improvement of the total harmonic distortion of voltage (THDv) on network buses are two terms of the objective function. The problem is solved by a hybrid technique named the “ PSO-GA algorithm” that takes advantage of both the genetic algorithm (GA) and the particle swarm optimization (PSO) method. Accordingly, the effectiveness of the proposed model is examined in a standard IEEE 33-bus distribution network populated with EVs and nonlinear devices (NLDs). The results obtained show that the maximum possible penetration rate of EVs into the network is facilitated, while technical and financial goals of the network and parking lots are ensured.