Locating Fast Charging Stations for Plug-In Hybrid Electric Vehicles in Distribution Networks with Considering Load Uncertainties Using a New Multi-Agent Harmony Search Algorithm

Subject Areas : Communication

Razieh  Heidari ¹ (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)
Alimorad  Khajehzadeh ² (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)
Mahdiyeh  Eslami ³ (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)

Received: 2021-02-01 Accepted : 2021-04-11 Published : 2021-09-01

Keywords: Plug-in hybrid electric vehicles, New multi-agent harmony search algorithm, Charging stations, Poison and Normal Distributions,

Abstract :

The use of Plug-in Hybrid Electric Vehicles (PHEV) can be known as an efficient factor for reducing the pollution caused by fossil fuels. It is obvious that with increasing the number of these vehicles, charging stations are needed to be established on the network. Therefore, in this paper, the problem of locating fast charging stations for Plug-in Hybrid Electric Vehicles using a new Multi-agent Harmony Search Algorithm is completely studied. According to the fact that the load uncertainties caused by charging hybrid electric vehicles are an effective and important factor to determine the number and also suitable locations of charging stations, the Poison and normal distributions are here used for considering uncertainties about the number of hybrid electric vehicles per hour and the charging demand for each hybrid electric vehicle, respectively. To study the problem in this paper, first, 10,000 different scenarios are made per hour and then, using Latin Hypercube, the number of the scenarios of each hour is dropped to 10. Finally, a new Multi-Agent Harmony Search Algorithm is applied to reduce network losses in different scenarios. The obtained results show that determining the number and the suitable locations for vehicle charging stations can greatly reduce the risk of overloading in the network caused by charging hybrid electric vehicles