Evolution of Capacitor Switching Detection and Location Determination in Power Distribution Systems: from Traditional Methods to AI-Enhanced Approaches

Sofyan Sofyan; Ahmad Rizal Sultan; Sarma Thaha; Usman Usman; Syahrir; Norazliani Md Sapari

doi:10.31963/elekterika.v22i2.5593

Authors

Sofyan Sofyan Politeknik Negeri Ujung Pandang (PNUP) https://orcid.org/0000-0001-9076-7229
Ahmad Rizal Sultan Politeknik Negeri Ujung Pandang (PNUP)
Sarma Thaha Politeknik Negeri Ujung Pandang (PNUP)
Usman Politeknik Negeri Ujung Pandang (PNUP)
syahrir Politeknik Negeri Ujung Pandang (PNUP)
Norazliani Univeriti Teknologi Malaysia

DOI:

https://doi.org/10.31963/elekterika.v22i2.5593

Keywords:

Capacitor switching, detection algorithms, location determination, artificial intelligence, machine learning, power quality, distribution systems, performance analysis.

Abstract

This paper presents a comprehensive analysis of methodological evolution in capacitor switching detection and location determination for power distribution systems, spanning from traditional analytical approaches to contemporary artificial intelligence-enhanced methods. The analysis evaluates six major methodological paradigms: gradient-based detection, voltage-only approaches, machine learning integration, deep learning applications, uncertainty quantification, and real-time processing techniques. Through systematic performance comparisons across 45 recent studies (2020-2025), this research demonstrates that AI-enhanced methods achieve detection accuracy exceeding 97% with uncertainty bounds, compared to 85-92% for traditional approaches. The comparative analysis reveals computational trade-offs, implementation complexity, and economic considerations for each methodology class. Key findings indicate a 40% reduction in false positive rates and 60% improvement in computational efficiency when transitioning from traditional to AI-enhanced approaches. This research provides quantitative benchmarking and decision frameworks for utilities selecting optimal capacitors switching analysis methodologies, contributing to improved power quality management in modern distribution systems.

Author Biographies

Sofyan Sofyan, Politeknik Negeri Ujung Pandang (PNUP)

Sofyan Sofyan completed his S.T. and M.T. degrees in 2002 and 2010, respectively, from the Dept. of Electrical Engineering at UNHAS, Indonesia. Currently, he is pursuing a doctoral program in the Dept. of Electrical Engineering at UTM, Malaysia. Additionally, Sofyan serves as a lecturer in the Dept. of Electrical Engineering at the Polytechnic State of Ujung Pandang (PNUP), Indonesia. His research focuses on the operation and optimization of power systems, energy demand in smart grid systems, and technology related to renewable energy. Sofyan Sofyan menyelesaikan gelar S.T. dan M.T. masing-masing pada tahun 2002 dan 2010 dari Jurusan Teknik Elektro di UNHAS, Indonesia. Saat ini, ia sedang menempuh program doktoral di Jurusan Teknik Elektro di UTM, Malaysia. Selain itu, Sofyan menjabat sebagai dosen di Jurusan Teknik Elektro di Politeknik Negeri Ujung Pandang (PNUP), Indonesia. Penelitiannya berfokus pada pengoperasian dan optimalisasi sistem tenaga listrik, permintaan energi dalam sistem jaringan pintar, dan teknologi yang terkait dengan energi terbarukan.

Ahmad Rizal Sultan, Politeknik Negeri Ujung Pandang (PNUP)

Teknik Elektro, Politeknik Negeri Ujung Pandang, Makassar 90245, Indonesia

Sarma Thaha, Politeknik Negeri Ujung Pandang (PNUP)

Teknik Elektro, Politeknik Negeri Ujung Pandang, Makassar 90245, Indonesia

Usman, Politeknik Negeri Ujung Pandang (PNUP)

Teknik Elektro, Politeknik Negeri Ujung Pandang, Makassar 90245, Indonesia

syahrir, Politeknik Negeri Ujung Pandang (PNUP)

Jurusan Teknik Informatika dan Komputer, Program Studi Teknik Multimedia dan Jaringan, Politeknik Negeri Ujung Pandang, Makassar, Sulawesi Selatan, 90245

Norazliani , Univeriti Teknologi Malaysia

Faculty of Electrical Engineering Universiti Teknologi Malaysia, Johor Bahru, Johor 81310, Malaysia

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