Enhancing Power System Stability with AI-Based Relaying Algorithms – A Review

0*, D. Sam Harison**
* Department of Electrical and Electronics Engineering, C. S. I. Institute of Technology, Thovalai, Tamil Nadu, India.
** Department of Electrical and Electronics Engineering, Rohini College of Engineering and Technology, Kanyakumari, Tamil Nadu, India.
Periodicity:January - March'2023
DOI : https://doi.org/10.26634/jps.10.4.19373

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies that are increasingly being used to improve various aspects of power systems. In particular, AI-based relaying algorithms have the potential to revolutionize the way power systems are protected from faults and failures. Relaying algorithms play a critical role in ensuring the stability and reliability of power systems. However, traditional relay protection algorithms face several challenges, including difficulty handling complex and dynamic systems, limited fault detection accuracy, and slow response times to changing conditions. AI-based relaying algorithms can address these challenges by leveraging the power of Artificial Intelligence and Machine Learning. This paper presents an overview of AI-based relaying algorithms and their potential applications in power systems. It explores the use of AI techniques such as Artificial Neural Networks (ANN), Decision Trees (DT), and expert systems for improving the accuracy and reliability of relay protection. It also discuss the steps involved in AI-based relaying algorithms, including feature extraction, classification, and result output. This paper highlights the importance of further research and development in this field to fully realize the benefits of AI-based relaying algorithms.

Keywords

Power System, Relaying Algorithm, Artificial Intelligence, Machine Learning, ANN, DT, Expert System.

How to Cite this Article?

Rajesh, C. R., and Harison, D. S. (2023). Enhancing Power System Stability with AI-Based Relaying Algorithms – A Review. i-manager’s Journal on Power Systems Engineering, 10(4), 53-59. https://doi.org/10.26634/jps.10.4.19373

References

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