PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

This study explores the application of an artificial bee colony (ABC) to locate partial discharge (PD) in a test tank based on acoustic emission (AE) approach. Data from a previous AE PD experimental study, which includes the coordinates of 3 AE sensors and the time difference of arrival (TDOA), were used to construct the nonlinear localization equations. It is known that localization algorithms are among the factors that can affect PD localization accuracy, and the ongoing research in this area underscores the need for further advancements in this topic. Therefore, the ABC was proposed to estimate the PD location through a colony of 120 bees, evenly divided into 60 employed and 60 onlooker bees. The employed bees explored the bounded search space, and onlooker bees refined PD locations found by the employed bees through local search. Scout bees were set out whenever a bee exceeded the limit of abandonment to discover possible PD locations in new areas of the search space. After 500 iterations, the optimal solution was the estimated PD location produced by ABC. Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. The study concludes that the ABC is more suitable for the multi-variable PD localization task than the GA, PSO, and BA due to its effective balance between local search by onlooker bees and global exploration by scout bees.

• Al-Masri, W. M. F., Abdel-Hafez, M. F., & El-Hag, A. H. (2016). Toward high-accuracy estimation of partial discharge location. IEEE Transactions on Instrumentation and Measurement, 65(9), 2145–2153. https://doi.org/10.1109/TIM.2016.2573098
  
  Antony, D., & Punekar, G. S. (2018). Noniterative method for combined acoustic-electrical partial discharge source localization. IEEE Transactions on Power Delivery, 33(4), 1679–1688. https://doi.org/10.1109/TPWRD.2017.2769159
  
  Cai, J., Zhou, L., Hu, J., Zhang, C., Liao, W., & Guo, L. (2020). High‐accuracy localisation method for PD in transformers. IET Science, Measurement & Technology, 14(1), 104–110. https://doi.org/10.1049/iet-smt.2019.0051
  
  Chakravarthi, M. K., Giridhar, A. V., & Sarma, D. V. S. S. S. (2017, December 21-23). Localization of partial discharge source in power transformer using bat algorithm. [Paper presentation]. 7th International Conference on Power Systems (ICPS), Pune, India. https://doi.org/10.1109/ICPES.2017.8387324
  
  Dudani, K., & Chudasama, A. R. (2016). Partial discharge detection in transformer using adaptive grey wolf optimizer based acoustic emission technique. Cogent Engineering, 3(1), Article 1256083. https://doi.org/10.1080/23311916.2016.1256083
  
  Faizol, Z., Zubir, F., Saman, N. M., Ahmad, M. H., Rahim, M. K. A., Ayop, O., Jusoh, M., Majid, H. A., & Yusoff, Z. (2023). Detection method of partial discharge on transformer and gas-insulated switchgear: A review. Applied Sciences, 13(17), Article 9605. https://doi.org/10.3390/app13179605
  
  Hashim, A. H. M., Azis, N., Jasni, J., Radzi, M. A. M., Kozako, M., Jamil, M. K. M., & Yaakub, Z. (2023a). Application of ANFIS and ANN for partial discharge localization in oil through acoustic emission. IEEE Transactions on Dielectrics and Electrical Insulation, 30(3), 1247–1254. https://doi.org/10.1109/TDEI.2023.3264958
  
  Hashim, A. H. M., Azis, N., Jasni, J., Radzi, M. A. M., Kozako, M., Jamil, M. K. M., & Yaakub, Z. (2023b). Examination on the denoising methods for electrical and acoustic emission partial discharge signals in oil. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 11(3), 791–804. https://doi.org/10.52549/ijeei.v11i3.4463
  
  Hashim, A. H. M., Azis, N., Jasni, J., Radzi, M. A. M., Kozako, M., Jamil, M. K. M., & Yaakub, Z. (2022). Partial discharge localization in oil through acoustic emission technique utilizing fuzzy logic. IEEE Transactions on Dielectrics and Electrical Insulation, 29(2), 623-630. https://doi.org/10.1109/TDEI.2022.3157911
  
  Heris, M. (2015). Binary and real-coded genetic algorithms. MATLAB Central File Exchange.
  
  Heris, M. (2015). Particle swarm optimization (PSO). MATLAB Central File Exchange.
  
  Howells, E. T. N. E., & Norton, E. T. (1981). Location of partial discharge sites in on-line transformers. IEEE Transactions on Power Apparatus and Systems, 100(1), 158-162. https://doi.org/10.1109/TPAS.1981.316872
  
  Hussain, M. R., Refaat, S. S., & Abu-Rub, H. (2021). Overview and partial discharge analysis of power transformers: A literature review. IEEE Access, 9, 64587–64605. https://doi.org/10.1109/ACCESS.2021.3075288
  
  IEEE. (2019). C57.127-2018 - IEEE Guide for the Detection, Location and Interpretation of Sources of Acoustic Emissions from Electrical Discharges in Power Transformers and Power Reactors. IEEE. https://doi.org/10.1109/IEEESTD.2019.8664690
  
  Ilkhechi, H. D., & Samimi, M. H. (2021). Applications of the acoustic method in partial discharge measurement: A review. IEEE Transactions on Dielectrics and Electrical Insulation, 28(1), 42–51. https://doi.org/10.1109/TDEI.2020.008985
  
  Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization (Technical Report - TR06). Erciyes University. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://abc.erciyes.edu.tr/pub/tr06_2005.pdf
  
  Karaboga, D., & Akay, B. (2009). A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214(1), 108–132. https://doi.org/10.1016/j.amc.2009.03.090
  
  Kulkarni, V. R., & Desai, V. (2016, December 15-17). ABC and PSO: A comparative analysis. [Paper presentation]. IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Chennai, India. https://doi.org/10.1109/ICCIC.2016.7919625
  
  Kundu, P., Kishore, N. K., & Sinha, A. K. (2009). A non-iterative partial discharge source location method for transformers employing acoustic emission techniques. Applied Acoustics, 70(11–12), 1378–1383. https://doi.org/10.1016/j.apacoust.2009.07.001
  
  Liu, H. L. (2016). Acoustic partial discharge localization methodology in power transformers employing the quantum genetic algorithm. Applied Acoustics, 102, 71–78. https://doi.org/10.1016/j.apacoust.2015.08.011
  
  Liu, H. L., & Liu, H. D. (2014). Partial discharge localization in power transformers based on the sequential quadratic programming-genetic algorithm adopting acoustic emission techniques. EPJ Applied Physics, 68(1), Article 10801. https://doi.org/10.1051/epjap/2014140318
  
  Punekar, G. S., Jadhav, P., Bhavani, S. T., & Nagamani, H. N. (2012, July 24-28). Some aspects of location identification of PD source using AE signals by an iterative method. [Paper presentation]. IEEE 10th International Conference on the Properties and Applications of Dielectric Materials, Bangalore, India. https://doi.org/10.1109/ICPADM.2012.6318957
  
  Rathod, V. B., Kumbhar, G. B., & Bhalja, B. R. (2022). Partial discharge detection and localization in power transformers based on acoustic emission: Theory, methods, and recent trends. IETE Technical Review, 39(3), 540-552. https://doi.org/10.1080/02564602.2021.1871672
  
  Ri-cheng, L., Kai, B., Chun, D., Shao-yu, L., & Guo-zheng, X. (2008, November 9-12). Study on partial discharge localization by ultrasonic measuring in power transformer based on particle swarm optimization. [Paper presentation]. International Conference on High Voltage Engineering and Application, Chongqing, China. https://doi.org/10.1109/ICHVE.2008.4774007
  
  Sinaga, H. H., Phung, B. T., & Blackburn, T. R. (2012). Partial discharge localization in transformers using UHF detection method. IEEE Transactions on Dielectrics and Electrical Insulation, 19(6), 1891-1900. https://doi.org/10.1109/TDEI.2012.6396945
  
  Tang, L., Luo, R., Deng, M., & Su, J. (2008). Study of partial discharge localization using ultrasonics in power transformer based on particle swarm optimization. IEEE Transactions on Dielectrics and Electrical Insulation, 15(2), 492–495. https://doi.org/10.1109/TDEI.2008.4483469
  
  Veloso, G. C., Silva, L. E. B. D., Lambert-Torres, G., & Pinto, J. O. P. (2006). Localization of partial discharges in transformers by the analysis of the acoustic emission. In IEEE International Symposium on Industrial Electronics (pp. 537–541). IEEE Publishing. https://doi.org/10.1109/ISIE.2006.295515
  
  Veloso, G. F. C., Silva, L. E. B. D., & Lambert-Torres, G. (2007). A strategy to locate partial discharges in power transformers using acoustic emission. Renewable Energy and Power Quality Journal, 1(5), 596–600. https://doi.org/10.24084/repqj05.344
  
  Veloso, G. F. C., Silva, L. E. B. D., Noronha, I., & Lambert-Torres, G. (2008, June 30 – July 2). Identification of wavefronts in Partial Discharge acoustic signals using discrete wavelet transform. [Paper presentation]. IEEE International Symposium on Industrial Electronics, Cambridge, United Kingdom. https://doi.org/10.1109/ISIE.2008.4677219
  
  Wang, Y. B., Chang, D. G., Fan, Y. H., Zhang, G. J., Zhan, J. Y., Shao, X. J., & He, W. L. (2017). Acoustic localization of partial discharge sources in power transformers using a particle-swarm-optimization-route-searching algorithm. IEEE Transactions on Dielectrics and Electrical Insulation, 24(6), 3647–3656. https://doi.org/10.1109/TDEI.2017.006857
  
  Yang, X. S. (2010). A new metaheuristic bat-inspired algorithm. In J. R. Gonzalex, D. A. Pelta, C. Cruz, G. Terrazas & N. Krasnogpr (Eds.) Nature inspired cooperative strategies for optimization (pp. 65–74). Springer. https://doi.org/10.1007/978-3-642-12538-6_6