الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
”In this thesis, the influences of EV technologies on various energy systems, control scheme strategies, benefits, and motivational challenges are investigated. An overview of the impacts of uncontrolled EV loading on the electric power system and how controlled charging becomes useful is presented. Moreover, a review of the controlled charge and discharge benefits of EVs and the electrical serving involved in the reduction of frequency deviation, voltage stability, and power quality improvement is introduced.
In order to improve the power quality of the system based on the electric vehicle control system as well as facilitate the integration of the EV into the weak grid, this thesis introduces two improved control methods:
• A proposed control/operation strategy to improve the frequency stability of a weak grid connected to EVs.
• A control and operation strategy aimed at enhancing the stability of frequency and voltage in a weak grid using connected electric vehicles (EVs).
The proposed strategy involves leveraging the EVs to regulate both active and reactive injected power, thereby reducing frequency deviation and providing voltage support in the event of voltage fluctuations at the point of common coupling during various transient scenarios. Furthermore, a smart plug-off strategy is proposed to disconnect the EV from the weak grid without frequency interruption.
The proposed method is simulated in a MATLAB environment and a comparison between the system with and without the proposed EVs’ control schemes under different operating conditions is presented. Results prove the effectiveness of the proposed control/operation strategy.
Moreover, an algorithm is suggested to determine the optimum planning of CSs/EVs locations to conserve voltage, improve power loss, and reduce the effect of CSs/EVs in electrical distribution systems. The multi-objective genetic algorithm method (MOGA) is utilized to solve the optimization problem and reduce the impact of the random location of CSs/EVs. The simulations are performed on IEEE 33-bus and IEEE 69-bus radial distribution systems (RDS). The optimal EV allocation is carried out with two fixed levels of loading from 100% to 150% of the candidate EV load. A comparison between the proposed MOGA technique and other optimization techniques is carried out. The results demonstrated the capability of the proposed technique for optimal placement of CSs/EVs in RDS which reduces the total power loss, improves the voltage profile, and enhances the voltage stability.