Presenting a new method for charging and discharging PHEVs for improving in electrical parameters of the network

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Problems with the cost and pollution of fossil fuels have increased the incentive to operate on electric vehicles. However, the use of these vehicles is a challenge due to the additional loads which imposed on the power grid. Accordingly, a method has been proposed to improve the electrical parameters of the network including losses and voltage profiles by optimally managing the charge and discharge of plug in hybrid electric vehicles (PHEVs). The optimal management of the present paper involves the simultaneous management of active and reactive power of PHEVs. In order to implement the optimal management, in this paper, the probabilistic behavior of consumers and PHEVs are modeled on the factors affecting them. Regarding the multiplicity of factors considered and the non-convergence of the problem by conventional methods of optimization, a two-stage optimization method is proposed which provides the ability to achieve the desired goals by managing active and reactive power of PHEVs. The advantages of the proposed method can be to reduce the computational volume with respect to problem solving in each step of the time independently and thus reduce the optimization problem solving time. The proposed method is implemented by performing Monte Carlo repetitions on six power management scenarios implemented by GAMS and DIgSILENT software on real network of 20 kV distribution of Sirjan in Kerman province. The results of various scenarios show that the management of charge and discharge of PHEVs has smooth the voltage profile and reduced network losses. Therefore, using the proposed method, the additional loads imposed by the electric vehicle on the grid will not only increase the energy losses, but, with the proper management of the PHEVs, the network losses will be reduced compared to the absence of them.
Language:
Persian
Published:
Iranian Electric Industry Journal of Quality and Productivity, Volume:8 Issue: 1, 2019
Pages:
41 to 52
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