A Comprehensive Review on the Role of Artificial Intelligence in Power System Stability, Control, and Protection: Insights and Future Directions

Author:

Alhamrouni Ibrahim1ORCID,Abdul Kahar Nor Hidayah1ORCID,Salem Mohaned23ORCID,Swadi Mahmood4ORCID,Zahroui Younes5ORCID,Kadhim Dheyaa Jasim4ORCID,Mohamed Faisal A.3,Alhuyi Nazari Mohammad678

Affiliation:

1. British Malaysian Institute, Universiti Kuala Lumpur, Bt. 8, Jalan Sungai Pusu, Gombak 53100, Selangor, Malaysia

2. School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Penang, Malaysia

3. Libyan Authority for Scientific Research, Tripoli P.O. Box 80045, Libya

4. Department of Electrical Engineering, College of Engineering, University of Baghdad, Baghdad 10001, Iraq

5. Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway

6. Faculty of New Sciences and Technologies, University of Tehran, Tehran 1417935840, Iran

7. School of Engineering & Technology, Duy Tan University, Da Nang 550000, Vietnam

8. Research and Development Cell, Lovely Professional University, Phagwara 144411, India

Abstract

This review comprehensively examines the burgeoning field of intelligent techniques to enhance power systems’ stability, control, and protection. As global energy demands increase and renewable energy sources become more integrated, maintaining the stability and reliability of both conventional power systems and smart grids is crucial. Traditional methods are increasingly insufficient for handling today’s power grids’ complex, dynamic nature. This paper discusses the adoption of advanced intelligence methods, including artificial intelligence (AI), deep learning (DL), machine learning (ML), metaheuristic optimization algorithms, and other AI techniques such as fuzzy logic, reinforcement learning, and model predictive control to address these challenges. It underscores the critical importance of power system stability and the new challenges of integrating diverse energy sources. The paper reviews various intelligent methods used in power system analysis, emphasizing their roles in predictive maintenance, fault detection, real-time control, and monitoring. It details extensive research on the capabilities of AI and ML algorithms to enhance the precision and efficiency of protection systems, showing their effectiveness in accurately identifying and resolving faults. Additionally, it explores the potential of fuzzy logic in decision-making under uncertainty, reinforcement learning for dynamic stability control, and the integration of IoT and big data analytics for real-time system monitoring and optimization. Case studies from the literature are presented, offering valuable insights into practical applications. The review concludes by identifying current limitations and suggesting areas for future research, highlighting the need for more robust, flexible, and scalable intelligent systems in the power sector. This paper is a valuable resource for researchers, engineers, and policymakers, providing a detailed understanding of the current and future potential of intelligent techniques in power system stability, control, and protection.

Funder

Universiti Kuala Lumpur

Publisher

MDPI AG

Reference168 articles.

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