Reducing the losses of the distribution network in the case of charging and discharging plug-in hybrid vehicles in the presence of scattered production sources

Document Type : Original Article


Department of Mechanical Engineering, South Branch, Islamic Azad University, Tehran, Iran


Background and purpose: The addition of plug-in hybrid vehicles to the distribution networks imposes additional loads on the network and can create adverse effects on the distribution network. In this article, the effects of electric vehicles on the losses of distribution networks and its reduction through power management of electric vehicles in parking lots have been investigated.
Research method: Since the parameters in the modeling of these cars are random, in the research, the parameters of the number of cars in each class, battery capacity, daily distance traveled, SOC, and the time of arrival and departure of cars are considered as probabilistic parameters. Parking lots are places with a large number of electric cars, so the simultaneous charging or discharging of the cars there can have destructive effects on the distribution network. Therefore, in this article, a charge and discharge management method for electric vehicles in parking lots is proposed to reduce network losses. The proposed method is implemented using genetic optimization algorithm.
Findings: In order to review and analyze the above method, four scenarios were investigated. In the first scenario, it was assumed that the network does not have electric vehicles. The reason for assuming this scenario without cars is to understand more easily the effect of electric cars on the distribution network. In the second scenario, it was assumed that electric cars are charged and discharged in parking lots, albeit in an uncontrolled manner. Comparison of losses and voltage in these two scenarios shows that electric vehicles increase losses if they are charged in an uncontrolled manner. Then, in the third scenario, the charge and discharge management of cars was discussed using the proposed objective function without considering the effect of DGs.


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Volume 2, Issue 2 - Serial Number 4
September 2023
Pages 175-184
  • Receive Date: 02 June 2023
  • Revise Date: 06 June 2023
  • Accept Date: 15 June 2023