Comparative Evaluation of Distance and Differential Protection Schemes for Power Transformers under Inrush and Fault Conditions
- 1 Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
- 2 Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Abstract
Power transformers constitute some of the very fundamental parts of power systems and they are important correlations in the delivery of electricity. As a result of their sensitivity and high price, highly reliable protection against abnormal conditions is crucial to system stability and service continuity. This paper involves a detailed study of the transformer protection performance when differential and distance protection schemes are combined to achieve great reliability, selectivity, and speed in different operating conditions. The response was simulated and modeled to provide the reaction of the system to normal operation, external faults, internal faults, magnetizing inrush, and load changes. Time domain current waveforms and frequency domain harmonic spectrums were assessed to differentiate between fault-induced and non-persistent conditions. The differential protection was found to be highly sensitive and fast-acting to internal faults and the distance protection offered effective backup as well as accurate fault localization. A harmonic restraint algorithm designed on the second harmonic ratio (H2/fundamental) was used to prevent maloperation when transformer energizing was going on, which was effective in differentiating between inrush and actual fault conditions. Comparative studies of the two protection schemes evidenced that coordinated operation improves reliability of the protection of transformers. The results of the simulation confirmed that the proposed system of integrated protection can be used in accordance with the necessary requirements of speed, selectivity, and reliability, which ensures the accurate detection of faults without false tripping during non-fault transients. The results demonstrate the necessity of using both conventional protection techniques and signal processing techniques, which will lead to the intelligent protection architectures of the future using wavelet transforms and machine learning-based fault classifiers. Also, a long-performance and sensitivity analysis was performed to determine the effects of second harmonic blocking threshold and high-impedance internal faults on the reliability of protection. The findings indicate that under ideal harmonic restraint settings are effective in minimizing the occurrence of false tripping, whereas the hybrid protection scheme proposed is efficient in enhancing the strength of fault detection in unfavorable operating environments.
- Hernández-Santafé, J.D. and Sorrentino, E. (2025) Problems and Solutions Concerning the Distance Protection of Transmission Lines Connected to Inverter-Based Resources. Energies , 18, 1375. https://doi.org/10.3390/en18061375
- Huang, C., Fang, C., Hsu, W., Yang, C. and Zhou, L. (2025) Improving the Protection of Step-Down Transformers by Utilizing Percentage Differential Protection and Scale-Dependent Intrinsic Entropy. Entropy , 27, Article 444. https://doi.org/10.3390/e27040444
- Arias Velásquez, R.M. (2025) Transient Analysis of Temporary Overvoltage and Cable Faults in Underground Medium Voltage Systems. Results in Engineering , 25, Article ID: 103875. https://doi.org/10.1016/j.rineng.2024.103875
- Atiyah, W.A., Karimi, S. and Moradi, M. (2024) Real-Time Revolutionizing Internal Defect Detection in Power Transformers by Leveraging Wavelet Transform and Deep Learning LSTM in Cascading Application. Journal of Electrical Engineering & Technology , 19, 5273-5292. https://doi.org/10.1007/s42835-024-02048-7
- Moravej, Z., Ebrahimi, A., Pazoki, M. and Barati, M. (2023) Time Domain Differential Protection Scheme Applied to Power Transformers. International Journal of Electrical Power & Energy Systems , 154, Article ID: 109465. https://doi.org/10.1016/j.ijepes.2023.109465
- Alhamd, Q., Saniei, M., Seifossadat, S.G. and Mashhour, E. (2024) Advanced Fault Detection in Power Transformers Using Improved Wavelet Analysis and LSTM Networks Considering Current Transformer Saturation and Uncertainties. Algorithms , 17, Article 397. https://doi.org/10.3390/a17090397
- Zhou, S., Huang, J., Zhang, Y. and Li, Y. (2025) A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm. Energies , 18, Article 3872. https://doi.org/10.3390/en18143872
- Youssef, M., Abdelaziz, E.S., Mohamed, H.S. and Attia, M. (2025) Condition Monitoring and Fault Diagnosis of Power Transformer Based on Non-Invasive Measurement. Scientific Reports , 15, Article No. 32123. https://doi.org/10.1038/s41598-025-14242-2
- Shah, A.M., Bhalja, B.R. and Patel, R.M. (2018) New Protection Scheme for Power Transformer Based on Superimposed Differential Current. IET Generation , Transmission & Distribution , 12, 3587-3595. https://doi.org/10.1049/iet-gtd.2018.0296
- Tarafdar-Hagh, M., Hasanlouei, N., Muttaqi, K., Taghizad-Tavana, K., Nojavan, S. and Abdi, M. (2024) Application of Saturated Core Transformer as Inrush Current Limiter. e - Prime — Advances in Electrical Engineering , Electronics and Energy , 9, Article ID: 100677. https://doi.org/10.1016/j.prime.2024.100677