Microgrid Frequency Regulation by Using of Electric Vehicles Controlled by Fuzzy Controller with Optimized Rules and Membership Functions

Articles in Press

Document Type : Original Article

Authors

1 Electrical and Computer Engineering Department, University of Kashan. Kashan.

2 Faculty of Electrical and Computer Engineering, Department of Electrical Engineering - Power, University of Kashan, Kashan, Iran

Abstract

The growing use of electric power on one hand and environmental pollutions due to using of fossil fuels on another hand, have made it necessary to find new sources of energy to produce electric power. Renewable energies such as wind and solar resources can be employed to produce electric power but they suffer from uncertainties in their output powers due to stochastic environmental situations. These changes lead to frequency deviations in power grid and may make it unstable. This problem can be more challenging in standalone microgrids due to their low inertia. To overcome this problem, energy storage systems (ESSs) can be used. However using of ESSs needs to investments and may be not economical. Electric vehicles (EVs) can help power systems to balance generation and consumption and compensate the changes of renewable energy outputs. This can be done by EVs batteries so that they can be charged when grid frequency is high and discharged when frequency is low. This concept is introduced by Vehicle to Grid (V2G) phrase. In this paper a new method for control of EVs in a microgrid is proposed in order to decrease frequency deviations. For this purpose, fuzzy controller with optimized membership functions and rules has been introduced. Moreover in proposed method, state of charge (SOC) of EV battery can be control along with frequency regulation. Simulations have been carried out in MATLAB environment and results of simulations illustrate appropriate performance of proposed method.

Keywords

Soft Computing Journal

Articles in Press, Accepted Manuscript
Available Online from 31 July 2022

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History

  • Receive Date: 09 April 2022
  • Revise Date: 12 May 2022
  • Accept Date: 31 July 2022

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