Prediction of Remaining Life of Relay Protection Equipment Using Transformer-Holt Model
DOI:
https://doi.org/10.13052/dgaej2156-3306.4115Keywords:
Transformer-Holt model, relay protection equipment, remaining life prediction, time-frequency domain sequenceAbstract
Accurately predicting the remaining service life of relay protection equipment is crucial for maintaining the stability and safety of power systems. This study proposes a prediction method, based on the Transformer-Holt model, to improve the accuracy and generalization ability of predicting the remaining life of relay protection equipment. This method combines the deep learning ability of the Transformer model and the time-series smoothing processing function of the Holt model to develop a new type of prediction model. The experimental results showed that on the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) dataset, the prediction accuracy of this model reached 0.98, the prediction delay score was 0.90, and the generalization ability score was 0.95, all of which were significantly better than the comparison models. In the actual prediction scenarios, the evaluation parameters of mean square error, root mean square error, and mean absolute error of the model were 0.05, 0.21 and 0.15 respectively, demonstrating excellent performance. The proposed Transformer-Holt model provides a new technical approach to the predictive maintenance of power systems.
Downloads
References
Padmanaban S, Khalili M, Nasab M A, Zand M, Shamim A G, Khan B. Determination of power transformers health index using parameters affecting the transformer’s life. IETE Journal of Research, 2023, 69(11): 8467–8488.
Hussein R I H, Gökºenli N, Bektaº E. Enhanced Transformer Protection Using Fuzzy-Logic-Integrated Differential Relays: A Comparative Study with Rule-based Methods. Journal of Robotics and Control (JRC), 2024, 5(5): 1299–1310.
Subramaniam A, Sahoo A, Manohar S S, Raman S J, Panda S K. Switchgear condition assessment and lifecycle management: Standards, failure statistics, condition assessment, partial discharge analysis, maintenance approaches, and future trends. IEEE Electrical Insulation Magazine, 2021, 37(3): 27–41.
Chen X, Hu Y, Dong Z, Zheng P, Wei J. Transformer operating state monitoring system based on wireless sensor networks. IEEE Sensors Journal, 2021, 21(22): 25098–25105.
Madhushanka G W T I, Jayasinghe M T R, Rajapakse R A. Multiple-Day-Ahead Flood Prediction in the South Asian Tropical Zone Using Deep Learning. Journal of Hydrologic Engineering, 2025, 30(1):4024054.1–4024054.13.
Yuming H, Jiaohong L, Zhenguo M, Bing T, Keqi Z, Jianyong Z. On combined PSO-SVM models in fault prediction of relay protection equipment. Circuits, Systems, and Signal Processing, 2023, 42(2): 875–891.
Aminifar F, Abedini M, Amraee T, Jafarian P, Samimi M H, Shahidehpour M. A review of power system protection and asset management with machine learning techniques. Energy Systems, 2022, 13(4): 855–892.
Peng F, Gao H, Huang J, Guo Y, Liu Y, Zhang Y. Power differential protection for transformer based on fault component network. IEEE Transactions on Power Delivery, 2023, 38(4): 2464–2477.
Liu G, Miao J, Zhao X, Wang Z, Li X. Life prediction of residual current circuit breaker with overcurrent protection based on BP neural network optimized by genetic algorithm. Journal of Electrical Engineering & Technology, 2022, 17(3): 2003–2014.
Suo N, Zhou Z. Computer assistance analysis of power grid relay protection based on data mining. Computer-Aided Design and Applications, 2021, 18(S4): 61–71.
Arnautalić S, Mujèinagić E H, Petrović S. Influence of Current Transformer Saturation on Numerical Protection Relays–A Case Study of Circuit Breaker Failure Protection. B&H Electrical Engineering, 2021, 15(2): 78–85.
Sharma H C, Gupta Y K, Atri S K, Singhal P K, Bhanage R M, Dixit V K, Basu A. Approach & experience of iot based predictive maintenance technologies in power distribution network. Journal International Association on Electricity Generation, Transmission and Distribution, 2021, 34(1): 15–22.
Parvez J, Khan S, Khan I. Real-time monitoring system of power transformer using IoT and GSM. J. Mech. Continua Math. Sci., 2021, 16(9): 1–15.
Dapshima B A. A fault detection and protection scheme for a 150 MVA transformer using fuzzy. International Journal of Advances in Engineering and Management, 2022, 4(11): 503–512.
Jawady N, Ibrahim M A, Khalaf L A, Khalaf L A, Abed M N. An intelligent overcurrent relay to protect transmission lines based on artificial neural network. International Journal of Power Electronics and Drive Systems (IJPEDS), 2023, 14(2): 1290–1299.
Arora R K, Batra S K. Significance of Condition Monitoring of Electrical Equipment in Transmission & Distribution System. Water and Energy International, 2024, 67(2): 34–42.
Ghosh S, Dutta S. Ensemble machine learning methods for better dynamic assessment of transformer status. Journal of The Institution of Engineers (India): Series B, 2021, 102(5): 1113–1122.
Shaikh S, Soomar A M, Shah S H H. Coordination of protective relays in the substation. International Journal of Power Electronics and Drive Systems (IJPEDS), 2023, 14(3): 1471–1478.
Chen H, Meng L, Xi Y, Xin M, Yu S, Chen G, Chen Y. GRU based time series forecast of oil temperature in power transformer. Distributed Generation & Alternative Energy Journal, 2023, 38(2): 393–412.
Sheikh A H, Bakhsh F I. Optimal power flow through variable frequency transformer using different optimization techniques. Distributed Generation & Alternative Energy Journal, 2022, 37(4): 1129–1158.
Gheisari M, Hamidpour H, Liu Y, Saedi P, Raza A, Jalili A, Rokhsati H, Amin R. Data Mining Techniques for Web Mining: A Survey. Artificial Intelligence and Applications, 2023, 1(1): 3–10.
Qin Y, Chen D, Xiang S, Zhu C. Gated dual attention unit neural networks for remaining useful life prediction of rolling bearings. IEEE Transactions on Industrial Informatics, 2020, 17(9): 6438–6447.
Harinaik S, Sathyan S. Design and analysis of quasi-Y source high gain DC/DC resonant converter for renewable energy applications. Distributed Generation & Alternative Energy Journal, 2023, 38(2): 569–594.
