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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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Research Article

Effects of Optimization on User-based Charging/Discharging Control Strategy

Author(s): Zohaib Khan and Yang Wang*

Volume 15, Issue 2, 2022

Published on: 26 April, 2022

Page: [158 - 170] Pages: 13

DOI: 10.2174/2215083808666220324144603

Price: $65

Abstract

With the increase in the number of Electric Vehicles (EVs), more power will be needed from the grid. An increase in the load demand, losses, and grid operational costs will occur. Furthermore, with the increasing number of EVs, there comes a possibility of user dissatisfaction which can further lower the popularity of EVs.

Objective: This article focuses on EV battery charging and discharging control optimization, i.e., optimizing load demand to minimize power grid system losses and reduce charging costs. It also aids in the vehicle to grid (V2G) process while considering the "User Decision Variable" for each prospective EV.

Methods: As a load minimization problem, the optimal power flow model has been formulated first, then the problem has been formulated for each EV. The operational cost of the charging station is an objective function.

Results: Further investigation of the load minimization of the IEEE33-bus system has been carried out, and Particle Swarm Optimization (PSO) algorithm is proposed.

Conclusion: MATLAB results show that the proposed strategy to charge and discharge can decrease losses from the power grid, reduce the running operational cost while considering battery life and the user's sense of security.

Keywords: Charging station, electric vehicles, optimal power flow, particle swarm optimization, smart load, peak shaving.

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