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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM28132

Electrical Load Frequency Control Using AI Techniques for EV Connected Power Systems

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM28132

Volume:

8 |

1 |

Jan 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM28132

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

RP

Rahul Parmar

DSG

Dr. Saurabh Gupta

DDS

Dr. Devendra Sharma

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Abstract

There are several challenges associated with electric vehicles. This work discusses the effect of electric vehicles on the load frequency deviation.. However, Load cannot be the same throughout, load deviates from time to time. To get rid of these disadvantages related to conventional controllers, a lot many schemes have been put forth in literature. This work presents a new design of various types of load frequency controllers based on different types of Artificial Intelligent (AI) optimization techniques such as Fuzzy logic, ANN tuner for a single area power system. The performance of the controller under study shows an enhancement in the frequency deviation signal as well as the peak overshoot and settling time for the frequency output signal. The performance of the proposed scheme is validated using MATLAB/ SIMULINK tools.

KEYWORDS

Multi- Area Power System. Electric Vehicles Load Frequency Control Artificial Neural Networks (ANN) Adaptive Neuro Fuzzy Inference Systems (ANFIS).

Cite This Article

Rahul Parmar, Dr. Saurabh Gupta, Dr. Devendra Sharma, "Electrical Load Frequency Control Using AI Techniques for EV Connected Power Systems," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 1, Jan 2024. https://doi.org/10.55041/IJSREM28132

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Publication Date

12/31/45304

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Double-Blind Peer Review

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