Research Article
BibTex RIS Cite

Dağıtım Şebekelerinde Kısmi Deşarj Analizi için Entegre Akustik ve Elektriksel Yöntemler

Year 2025, Volume: 20 Issue: 2, 401 - 417, 30.09.2025
https://doi.org/10.55525/tjst.1625982

Abstract

Kısmi deşarjlar (KD), iletkenler arasındaki yalıtımı tamamen köprülemeyen ancak zamanla yalıtımın ciddi şekilde bozulmasına neden olabilen lokalize elektriksel boşalmalardır. Bu çalışma, elektrik dağıtım şebekelerinde KD etkinliğini analiz etmek amacıyla akustik ve elektriksel ölçüm tekniklerinin bir arada kullanıldığı entegre bir yöntem sunmaktadır. Saha ölçümleri, farklı çevresel ve işletme koşullarını temsil eden iki ayrı lokasyonda gerçekleştirilmiştir. Elektriksel sinyaller, COMTRADE formatında kayıt yapabilen yüksek hızlı bir güç kalitesi kaydedicisiyle; ultrasonik emisyonlar ise yüksek hassasiyetli akustik sensörler aracılığıyla elde edilmiştir. Toplanan veriler, MATLAB ortamında dalga biçimi analizi, zaman düzleminde değerlendirme, Hızlı Fourier Dönüşümü (FFT) ile frekans analizi ve Faz Çözünürlüklü Kısmi Deşarj (PRPD) desen tanımlaması gibi çok aşamalı bir süreçle incelenmiştir. Tepe genlikleri, tekrar oranları ve baskın frekans bileşenleri gibi temel KD göstergeleri çıkarılarak, boşalma türleri sınıflandırılmış ve yalıtım durumu değerlendirilmiştir. Elde edilen bulgular, akustik ve elektriksel verilerin birlikte analiz edilmesinin KD davranışını daha bütüncül biçimde anlamaya olanak tanıdığını ve bu sayede arızaların erken tespitini ve bakım stratejilerinin etkinliğini artırdığını ortaya koymuştur. Söz konusu yaklaşım, elektrik dağıtım altyapısının güvenilirliğini ve sürdürülebilirliğini artırmaya yönelik önemli katkılar sunmaktadır.

References

  • Shahzad S, Abbasi MA, Ali H, Iqbal M, Munir R, Kilic H. Possibilities, Challenges, and Future Opportunities of Microgrids: A Review. Sustainability. 2023; 15(8):6366.
  • Kılıç H, Yılmaz M. Sensor and Actuator Fault Tolerant Control of Grid-Tied Microgrid. Balkan J Electr Comput Eng. 2023;11(2):190–197.
  • Khaki B, Kılıç H, Yılmaz M, Shafie-Khah M, Lotfi M, Catalão JPS. Active Fault Tolerant Control of Grid-Connected DER: Diagnosis and Reconfiguration. In: 45th Annu Conf IEEE Ind Electron Soc (IECON); 2019; Lisbon, Portugal. p. 4127–4132.
  • Gümüş B, Kılıç H, Haydaroğlu C, Butakın UY. Fault type and fault location detection in transmission lines with 6-convolutional layered CNN. Bull Pol Acad Sci Tech Sci. 2024;72(5):e151047.
  • Kilic H. Distributed cooperative fault tolerant optimal active power control in AC microgrid. ISA Trans. 2023;142:98-111.
  • Shahzad S, Alsenani TR, Alrumayh AN, Almutairi A, Kilic H. Fault ride-through capability improvement in hydrogen energy-based distributed generators using STATCOM and deep-Q learning. Int J Hydrogen Energy. 2024.
  • London Fire Brigade. Fire at electrical substation in Hayes. London Fire; March 2025. [Erişim adresi: https://www.london-fire.gov.uk/incidents/2025/march/fire-at-electrical-substation-hayes/].
  • Department for Energy Security & Net Zero, NESO. Review into the North Hyde substation outage – Terms of Reference. Gov.uk; April 2025. [Erişim adresi: https://www.gov.uk/government/publications/review-into-the-north-hyde-substation-outage-terms-of-reference/].
  • Strachan SM, Rudd S, McArthur SDJ, Judd MD, Meijer S, Gulski E. Knowledge-based diagnosis of partial discharges in power transformers. IEEE Trans Dielectr Electr Insul. 2008;15(1):259-268.
  • IEEE Power Engineering Society. IEEE Guide for Partial Discharge Testing of Shielded Power Cable Systems in a Field Environment. IEEE Std 400.3™-2006; 2007.
  • Vita V, Fotis G, Chobanov V, Pavlatos C, Mladenov V. Predictive Maintenance for Distribution System Operators in Increasing Transformers’ Reliability. Electronics. 2023;12(6):1356.
  • Yan X, Bai Y, Zhang W, Cheng C, Liu J. Partial Discharge Pattern-Recognition Method Based on Embedded Artificial Intelligence. Appl Sci. 2023;13(18):10370.
  • Faizol Z, Zubir F, Saman NM, Ahmad MH, Rahim MKA, Ayop O, Jusoh M, Majid HA, Yusoff Z. Detection Method of Partial Discharge on Transformer and Gas-Insulated Switchgear: A Review. Appl Sci. 2023;13(17):9605.
  • Yuwei F, et al. Partial Discharge Pattern Recognition Method Based on Transfer Learning and DenseNet Model. IEEE Trans Dielectr Electr Insul. 2023;30(3):1240–1246.
  • Chan JQ, Raymond WJK, Illias HA, Othman M. Partial Discharge Localization Techniques: A Review of Recent Progress. Energies. 2023;16(6):2863.
  • Haes Alhelou H, Hamedani-Golshan ME, Njenda TC, Siano P. A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges. Energies. 2019;12:682.
  • IEEE. IEEE Recommended Practice for Techniques for High-Voltage Testing. IEEE Standard 1434-2010; 2010.
  • Romphuchaiyapruek K, Wattanawongpitak S. Frequency-Based Density Estimation and Identification of Partial Discharges Signal in High-Voltage Generators via Gaussian Mixture Models. Eng. 2025;6(4):64.
  • Mwinisin P, Mingotti A, Peretto L, Tinarelli R, Tefferi M. Electrical Diagnosis Techniques for Power Transformers: A Comprehensive Review of Methods, Instrumentation, and Research Challenges. Sensors. 2025;25(7):1968.
  • Wang J, Zhang Y, Gu X. A Partial Discharge Detection Approach in Distribution Cabinets Using a Mach–Zehnder Interferometer. Sensors. 2025;25(7):2265.
  • Cai S, Fang C, Guo Y, Liu J, Zhou G. Partial Discharge Type Identification of 10 kV T-Type Terminal Based on Empirical Mode Decomposition and Deep Convolution Neural Network. Appl Sci. 2025;15(7):3962.
  • Thango BA. Interpretation of Partial-Discharge-Activated Frequency Response Analysis for Transformer Diagnostics. Machines. 2025;13(4):300.
  • Chen B, Hu Y, Wu L. Deep Learning-Based Multi-Source Partial Discharge Pattern Recognition Integrated with Auxiliary Prior Localization Information. IEEE Trans Dielectr Electr Insul. 2025.
  • Ruan J, Zhong Y, Peng P, Liu Y, Zhong L. Diagnosis and Analysis of Partial Discharge Fault of 500 kV Transformer. In: Int Conf Electr Autom Artif Intell (ICEAAI); 2025; Guangzhou, China. p. 1036–1039.
  • Wang H, et al. Surface Partial Discharge Characteristics of GIS Under AC and Superimposed Switching Impulse Voltage. IEEE Trans Dielectr Electr Insul. 2025.
  • Lu G, et al. Interpretable Fault Diagnosis for Overhead Lines with Covered Conductors: A Physics-Informed Deep Learning Approach. Prot Control Mod Power Syst. 2025;10(2):25–39.
  • Tang Z, et al. Research on Electromagnetic Interference Signal Characteristics and Suppression Methods for High Frequency Partial Discharge Monitoring in Renewable Energy Stations. IEEE Trans Power Deliv. 2025.
  • Wang Y, et al. A Class Alignment Multi-Source Domain Adaptation for Partial Discharge Condition Assessment With Unknown Faults in GIS. IEEE Internet Things J. 2025.
  • Choudhary M, Shafiq M, Bhattarai A, Kiitam I, Taklaja P, Palu I. A comprehensive study of partial discharge based extrinsic aging in nomex insulation films: Modeling, simulation and measurement. Electr Power Syst Res. 2025;245:111663.
  • Freitas-Gutierres LF, Maresch K, Quatrin ADN, Morais AM, Romano MAA, Nunes MVA, Correa CH, Martins EF, Fontoura HC, Borin AS, Cardoso G Jr, Oliveira AL. Advancing substation inspection: The Hilbert–Huang transform approach for partial discharge recognition and assessment. Measurement. 2025;247:116846.
  • Peng S, Wang Y, Tang A, Jiang Y, Kan J, Pecht M. State of health estimation joint improved grey wolf optimization algorithm and LSTM using partial discharging health features for lithium-ion batteries. Energy. 2025;315:134293.
  • Yang C, Chen J, Ni W, Liu W, Tian Y, Shum PP. Passive ultrasonic-image localization of partial discharge precursors in power transmission. Appl Acoust. 2025;231:110508.
  • Zheng S, Liu J, Zeng J. A partial discharge pattern recognition method based on multi-scale adaptive denoising network and Stacking Ensemble Learning. Electr Power Syst Res. 2025;241:111392.
  • Chen Y, Yan J, Wang Y, Wu Y, Liu Z. A novel localization method for partial discharge in GIS based on electromagnetic time reversal technique. Measurement. 2025;253(Pt B):117599.
  • Govindarajan S, Morales A, Ardila-Rey JA, Purushothaman N. A review on partial discharge diagnosis in cables: Theory, techniques, and trends. Measurement. 2023;216:112882.
  • Hussain GA, Hassan W, Mahmood F, Shafiq M, Rehman H, Kay JA. Review on partial discharge diagnostic techniques for high voltage equipment in power systems. IEEE Access. 2023;11:51382–51394.
  • Sahoo R, Karmakar S. Investigation of electrical tree growth characteristics and partial discharge pattern analysis using deep neural network. Electr Power Syst Res. 2023;220:109287.
  • Kaziz S, Said MH, Imburgia A, Maamer B, Flandre D, Romano P, Tounsi F. Radiometric partial discharge detection: A review. Energies. 2023;16(4):1978.
  • Long, J., Xie, L., Wang, X., Zhang, J., Lu, B., Wei, C., ... & Tian, M. (2024). A comprehensive review of signal processing and machine learning technologies for UHF PD detection and diagnosis (II): Pattern recognition approaches. IEEE Access, 12, 29850-29890.
  • Ilkhechi HD, Samimi MH. Applications of the acoustic method in partial discharge measurement: A review. IEEE Trans Dielectr Electr Insul. 2021;28(1):42-51.

Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks

Year 2025, Volume: 20 Issue: 2, 401 - 417, 30.09.2025
https://doi.org/10.55525/tjst.1625982

Abstract

Partial discharges (PD) are localized electrical discharges that do not fully bridge the insulation between conductors but can significantly degrade insulation over time. This study introduces an integrated methodology that combines acoustic and electrical measurement techniques to analyze PD activity in electricity distribution networks. Field measurements were carried out at two distinct locations under varying environmental and operational conditions. Electrical signals were acquired using a high-speed power quality recorder in COMTRADE format, while ultrasonic emissions were captured via precision acoustic sensors. The collected data were analyzed in MATLAB through a multi-step process involving waveform analysis, time-domain evaluation, frequency-domain analysis using Fast Fourier Transform (FFT), and Phase-Resolved Partial Discharge (PRPD) pattern recognition. Key PD indicators—including peak amplitudes, repetition rates, and dominant frequency components—were extracted to classify discharge types and assess insulation condition. The findings reveal that integrating acoustic and electrical data enables a more holistic understanding of PD behavior, facilitating early fault detection and the development of proactive maintenance strategies. This integrated approach contributes to improving the reliability and sustainability of power distribution infrastructure.

References

  • Shahzad S, Abbasi MA, Ali H, Iqbal M, Munir R, Kilic H. Possibilities, Challenges, and Future Opportunities of Microgrids: A Review. Sustainability. 2023; 15(8):6366.
  • Kılıç H, Yılmaz M. Sensor and Actuator Fault Tolerant Control of Grid-Tied Microgrid. Balkan J Electr Comput Eng. 2023;11(2):190–197.
  • Khaki B, Kılıç H, Yılmaz M, Shafie-Khah M, Lotfi M, Catalão JPS. Active Fault Tolerant Control of Grid-Connected DER: Diagnosis and Reconfiguration. In: 45th Annu Conf IEEE Ind Electron Soc (IECON); 2019; Lisbon, Portugal. p. 4127–4132.
  • Gümüş B, Kılıç H, Haydaroğlu C, Butakın UY. Fault type and fault location detection in transmission lines with 6-convolutional layered CNN. Bull Pol Acad Sci Tech Sci. 2024;72(5):e151047.
  • Kilic H. Distributed cooperative fault tolerant optimal active power control in AC microgrid. ISA Trans. 2023;142:98-111.
  • Shahzad S, Alsenani TR, Alrumayh AN, Almutairi A, Kilic H. Fault ride-through capability improvement in hydrogen energy-based distributed generators using STATCOM and deep-Q learning. Int J Hydrogen Energy. 2024.
  • London Fire Brigade. Fire at electrical substation in Hayes. London Fire; March 2025. [Erişim adresi: https://www.london-fire.gov.uk/incidents/2025/march/fire-at-electrical-substation-hayes/].
  • Department for Energy Security & Net Zero, NESO. Review into the North Hyde substation outage – Terms of Reference. Gov.uk; April 2025. [Erişim adresi: https://www.gov.uk/government/publications/review-into-the-north-hyde-substation-outage-terms-of-reference/].
  • Strachan SM, Rudd S, McArthur SDJ, Judd MD, Meijer S, Gulski E. Knowledge-based diagnosis of partial discharges in power transformers. IEEE Trans Dielectr Electr Insul. 2008;15(1):259-268.
  • IEEE Power Engineering Society. IEEE Guide for Partial Discharge Testing of Shielded Power Cable Systems in a Field Environment. IEEE Std 400.3™-2006; 2007.
  • Vita V, Fotis G, Chobanov V, Pavlatos C, Mladenov V. Predictive Maintenance for Distribution System Operators in Increasing Transformers’ Reliability. Electronics. 2023;12(6):1356.
  • Yan X, Bai Y, Zhang W, Cheng C, Liu J. Partial Discharge Pattern-Recognition Method Based on Embedded Artificial Intelligence. Appl Sci. 2023;13(18):10370.
  • Faizol Z, Zubir F, Saman NM, Ahmad MH, Rahim MKA, Ayop O, Jusoh M, Majid HA, Yusoff Z. Detection Method of Partial Discharge on Transformer and Gas-Insulated Switchgear: A Review. Appl Sci. 2023;13(17):9605.
  • Yuwei F, et al. Partial Discharge Pattern Recognition Method Based on Transfer Learning and DenseNet Model. IEEE Trans Dielectr Electr Insul. 2023;30(3):1240–1246.
  • Chan JQ, Raymond WJK, Illias HA, Othman M. Partial Discharge Localization Techniques: A Review of Recent Progress. Energies. 2023;16(6):2863.
  • Haes Alhelou H, Hamedani-Golshan ME, Njenda TC, Siano P. A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges. Energies. 2019;12:682.
  • IEEE. IEEE Recommended Practice for Techniques for High-Voltage Testing. IEEE Standard 1434-2010; 2010.
  • Romphuchaiyapruek K, Wattanawongpitak S. Frequency-Based Density Estimation and Identification of Partial Discharges Signal in High-Voltage Generators via Gaussian Mixture Models. Eng. 2025;6(4):64.
  • Mwinisin P, Mingotti A, Peretto L, Tinarelli R, Tefferi M. Electrical Diagnosis Techniques for Power Transformers: A Comprehensive Review of Methods, Instrumentation, and Research Challenges. Sensors. 2025;25(7):1968.
  • Wang J, Zhang Y, Gu X. A Partial Discharge Detection Approach in Distribution Cabinets Using a Mach–Zehnder Interferometer. Sensors. 2025;25(7):2265.
  • Cai S, Fang C, Guo Y, Liu J, Zhou G. Partial Discharge Type Identification of 10 kV T-Type Terminal Based on Empirical Mode Decomposition and Deep Convolution Neural Network. Appl Sci. 2025;15(7):3962.
  • Thango BA. Interpretation of Partial-Discharge-Activated Frequency Response Analysis for Transformer Diagnostics. Machines. 2025;13(4):300.
  • Chen B, Hu Y, Wu L. Deep Learning-Based Multi-Source Partial Discharge Pattern Recognition Integrated with Auxiliary Prior Localization Information. IEEE Trans Dielectr Electr Insul. 2025.
  • Ruan J, Zhong Y, Peng P, Liu Y, Zhong L. Diagnosis and Analysis of Partial Discharge Fault of 500 kV Transformer. In: Int Conf Electr Autom Artif Intell (ICEAAI); 2025; Guangzhou, China. p. 1036–1039.
  • Wang H, et al. Surface Partial Discharge Characteristics of GIS Under AC and Superimposed Switching Impulse Voltage. IEEE Trans Dielectr Electr Insul. 2025.
  • Lu G, et al. Interpretable Fault Diagnosis for Overhead Lines with Covered Conductors: A Physics-Informed Deep Learning Approach. Prot Control Mod Power Syst. 2025;10(2):25–39.
  • Tang Z, et al. Research on Electromagnetic Interference Signal Characteristics and Suppression Methods for High Frequency Partial Discharge Monitoring in Renewable Energy Stations. IEEE Trans Power Deliv. 2025.
  • Wang Y, et al. A Class Alignment Multi-Source Domain Adaptation for Partial Discharge Condition Assessment With Unknown Faults in GIS. IEEE Internet Things J. 2025.
  • Choudhary M, Shafiq M, Bhattarai A, Kiitam I, Taklaja P, Palu I. A comprehensive study of partial discharge based extrinsic aging in nomex insulation films: Modeling, simulation and measurement. Electr Power Syst Res. 2025;245:111663.
  • Freitas-Gutierres LF, Maresch K, Quatrin ADN, Morais AM, Romano MAA, Nunes MVA, Correa CH, Martins EF, Fontoura HC, Borin AS, Cardoso G Jr, Oliveira AL. Advancing substation inspection: The Hilbert–Huang transform approach for partial discharge recognition and assessment. Measurement. 2025;247:116846.
  • Peng S, Wang Y, Tang A, Jiang Y, Kan J, Pecht M. State of health estimation joint improved grey wolf optimization algorithm and LSTM using partial discharging health features for lithium-ion batteries. Energy. 2025;315:134293.
  • Yang C, Chen J, Ni W, Liu W, Tian Y, Shum PP. Passive ultrasonic-image localization of partial discharge precursors in power transmission. Appl Acoust. 2025;231:110508.
  • Zheng S, Liu J, Zeng J. A partial discharge pattern recognition method based on multi-scale adaptive denoising network and Stacking Ensemble Learning. Electr Power Syst Res. 2025;241:111392.
  • Chen Y, Yan J, Wang Y, Wu Y, Liu Z. A novel localization method for partial discharge in GIS based on electromagnetic time reversal technique. Measurement. 2025;253(Pt B):117599.
  • Govindarajan S, Morales A, Ardila-Rey JA, Purushothaman N. A review on partial discharge diagnosis in cables: Theory, techniques, and trends. Measurement. 2023;216:112882.
  • Hussain GA, Hassan W, Mahmood F, Shafiq M, Rehman H, Kay JA. Review on partial discharge diagnostic techniques for high voltage equipment in power systems. IEEE Access. 2023;11:51382–51394.
  • Sahoo R, Karmakar S. Investigation of electrical tree growth characteristics and partial discharge pattern analysis using deep neural network. Electr Power Syst Res. 2023;220:109287.
  • Kaziz S, Said MH, Imburgia A, Maamer B, Flandre D, Romano P, Tounsi F. Radiometric partial discharge detection: A review. Energies. 2023;16(4):1978.
  • Long, J., Xie, L., Wang, X., Zhang, J., Lu, B., Wei, C., ... & Tian, M. (2024). A comprehensive review of signal processing and machine learning technologies for UHF PD detection and diagnosis (II): Pattern recognition approaches. IEEE Access, 12, 29850-29890.
  • Ilkhechi HD, Samimi MH. Applications of the acoustic method in partial discharge measurement: A review. IEEE Trans Dielectr Electr Insul. 2021;28(1):42-51.
There are 40 citations in total.

Details

Primary Language English
Subjects Electrical Energy Transmission, Networks and Systems
Journal Section TJST
Authors

Hüsnügül Tekin 0000-0002-9817-9373

Heybet Kılıç 0000-0002-6119-0886

Publication Date September 30, 2025
Submission Date January 23, 2025
Acceptance Date May 21, 2025
Published in Issue Year 2025 Volume: 20 Issue: 2

Cite

APA Tekin, H., & Kılıç, H. (2025). Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks. Turkish Journal of Science and Technology, 20(2), 401-417. https://doi.org/10.55525/tjst.1625982
AMA Tekin H, Kılıç H. Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks. TJST. September 2025;20(2):401-417. doi:10.55525/tjst.1625982
Chicago Tekin, Hüsnügül, and Heybet Kılıç. “Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks”. Turkish Journal of Science and Technology 20, no. 2 (September 2025): 401-17. https://doi.org/10.55525/tjst.1625982.
EndNote Tekin H, Kılıç H (September 1, 2025) Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks. Turkish Journal of Science and Technology 20 2 401–417.
IEEE H. Tekin and H. Kılıç, “Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks”, TJST, vol. 20, no. 2, pp. 401–417, 2025, doi: 10.55525/tjst.1625982.
ISNAD Tekin, Hüsnügül - Kılıç, Heybet. “Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks”. Turkish Journal of Science and Technology 20/2 (September2025), 401-417. https://doi.org/10.55525/tjst.1625982.
JAMA Tekin H, Kılıç H. Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks. TJST. 2025;20:401–417.
MLA Tekin, Hüsnügül and Heybet Kılıç. “Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks”. Turkish Journal of Science and Technology, vol. 20, no. 2, 2025, pp. 401-17, doi:10.55525/tjst.1625982.
Vancouver Tekin H, Kılıç H. Integrated Acoustic and Electrical Methods for Partial Discharge Analysis in Distribution Networks. TJST. 2025;20(2):401-17.