Optimal charge control of electric vehicles in parking stations for cost minimization in V2G concept

Abstract

In this paper, we consider the coordinated charging control of electrical vehicle (EV) in the charging stations. The goals are to minimize the total charging cost of all the vehicles at the charging station, respecting subscription type to electricity for charging station. The algorithm is based on a given future electricity prices and uses linear programming.This cost reduction of charging being achieved through bidirectional power flow between vehicles and grid. Thus functionalities of electrical vehicle can be divided into two aspects: on one hand, battery of the EV can be considered as a variable load. With optimal charging or smart charging for the battery, vehicle owners could maximize their profits by purchasing energy, G2V (Grid to Vehicle), at the lowest possible electricity price and in on the other hand, battery of the EV canal so be considered as energy storage capacity which has possibility to provide energy V2G (Vehicle to Grid).After the simulations performed by applying this strategy to coordinate EV charging, we achieved a cost reduction with 20% from the initial cost. Index Terms -Electric Vehicle, Smart Charging, LinearProgramming, Vehicle to Grid (V2G), Grid to Vehicle (G2V).

A centralized vehicle‐to‐grid scheme with distributed computing capacity engaging internet of smart charging points: Case study

“…24 From the technological perspective, the models with the target of minimizing load variance, [25][26][27] minimizing power loss, [28][29][30] and minimizing load peak 31,32 are presented to improve the power quality of the grid and satisfy the energy requirements of PEV users. From the economic perspective, either the total charging cost of PEV users [33][34][35] or the total operating profit of EC 36,37 is considered for improving the financial benefit of each stakeholder. From the environmental perspective, minimizing carbon emissions is investigated and optimized, in which emissions resulting from PEVs charging varying with time and region are taken into account.…”

On The Strategies for the Diffusion of EVs: Comparison between Norway and Italy

“…On the other hand, the aim to decarbonize the transport sector through electrification has to consider the energy efficiency of both the electricity production and the energy use. One of the main potentially of the Italy is due to high diffusion of solar energy, which can produce electric energy in the same charging stations [21,[25][26][27][28][29][30]. In such a way the emissions reduction, primary aim of the employment of EVs, can be linked to the transport efficiency, expressed as the ratio of energy used per vehicle-km, that can be remodeled in low emission transport efficiency: a reduced number of EVs will employ decarbonized energy.…”

Cooperative Control of Charging Stations for an EV Park with Stochastic Dynamic Programming

“…Because SOFW has an internal repository where EV's connection to the charger data is stored, the probability mass function is updated with a defined frequency inside the platform becoming application specific. Furthermore, a number of optimization approaches deal with financial aspects for charging EVs, as for example the reduction of energy cost [7], [14]. Other works focus on grid stability avoiding the increase in peak consumption or reducing voltage instabilities [10].…”

“…It allows the system to be deployed at the car park immediacies of the DSO company in the future. Finally, vehicle to grid (V2G) has been recently analyzed in a number of publications [5], [12], [14]. At the moment this work does not consider V2G.…”