APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN POWER ELECTRONICS AND DRIVES SYSTEMS: A COMPREHENSIVE REVIEW
Keywords:
Artificial Intelligence, Applications, Power Electronics, Drives SystemsAbstract
Power electronics and drives systems are critical components in many industrial and consumer applications, including electric vehicles, renewable energy systems, and home appliances. The application of artificial intelligence (AI) has emerged as a potential strategy to improve the control, fault detection, energy management, and design optimisation of power electronics and drives systems in response to the growing demand for improved performance and efficiency. This article provides a comprehensive review of the applications of AI in power electronics and drives systems. It starts with an introduction to power electronics and drives systems and the importance of AI in enhancing their performance. Then, the fundamentals of AI techniques, including machine learning, fuzzy logic, and metaheuristic methods, are presented. The article covers various applications of AI in power electronics and drives, including control and optimization, fault diagnosis and prognosis, energy management, and design optimization.
References
Robert E. Uhrig, "Introduction to Artificial Neural Networks", Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics and Instrumentation, 6-10th Nov. 1995.
Zhao, S., Blaabjerg, F., & Wang, H. (2021). An overview of artificial intelligence applications for power electronics. IEEE Transactions on Power Electronics, 36(4), 4633-4658. [9200511]. https://doi.org/10.1109/TPEL.2020.3024914
Franki, V.; Majnarić, D.; Višković, A. A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector. Energies 2023, 16, 1077. https://doi.org/10.3390/en16031077
Duan, Y.; Edwards, J.S.; Dwivedi, Y.K. Artificial intelligence for decision making in the era of Big Data—Evolution, challenges and research agenda. Int. J. Inf. Manag. 2019, 48, 63–71.
Aziz, A.F.A.; Khalid, S.N.; Mustafa, M.W.; Shareef, H.; Aliyu, G. Artificial Intelligent Meter development based on Advanced Metering Infrastructure technology. Renew. Sustain. Energy Rev. 2013, 27, 191–197.
M. Muthuvinayagam, P. C. Sivakumar, M. C. John Wiselin and M. Sakthikumaran, Comprehensive Analysis on Power Electronic Systems in Relation with Machine Learning, International Journal of Computer Engineering and Technology 11(1), 2020, pp. 57-62. doi: https://doi.org/10.17605/OSF.IO/K4VDP
Bose, B. K. (1994). Expert system, fuzzy logic, and neural network applications in power electronics and motion control. Proceedings of the IEEE, 82(8), 1303-1323.
S. Balasubramanian, Literature Review on Developing Explainable AI for Trustworthy Decision-Making, International Journal of Design and Manufacturing Technology (IJDMT), 14(1), 2023, pp. 1-6. doi: https://doi.org/10.17605/OSF.IO/7PBY8
C.Wei, Z. Zhang,W. Qiao, and L. Qu, “Reinforcement-learning-based intelligent maximum power point tracking control for wind energy conversion systems,” IEEE Trans. Ind. Electron., vol. 62, no. 10, pp. 6360–6370,
M. R. G. Meireles, P. E. M. Almeida, and M. G. Simoes, “A comprehensive review for industrial applicability of artificial neural networks,” IEEE Trans. Ind. Electron., vol. 50, no. 3, pp. 585–601, Jun. 2003.
S. Zhao, F. Blaabjerg and H. Wang, "An Overview of Artificial Intelligence Applications for Power Electronics," in IEEE Transactions on Power Electronics, vol. 36, no. 4, pp. 4633-4658, April 2021, doi: 10.1109/TPEL.2020.3024914.
M. Seyedmahmoudian et al., “State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems—A review,” Renewable Sustain. Energy Rev., vol. 64, pp. 435–455, Oct. 2016
Pinto and Ozpineci, “Tutorial: Artificial intelligence applications to power electronics,” in Proc. IEEE Energy Convers. Congr. Expo., 2019, pp. 1–139.
W. Wang et al., “Training neural-network-based controller on distributed machine learning platform for power electronics systems,” in Proc. IEEE Energy Convers. Congr. Expo., 2017, pp. 3083–3089
M. G. Simoes, B. K. Bose, and R. J. Spiegel, “Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system,” IEEE Trans. Ind. Appl., vol. 33, no. 4, pp. 956–965, Jul./Aug. 1997
Matlab, “Manual of neural network toolbox,” 2005. [Online]. Available: http://matlab.izmiran.ru/help/toolbox/nnet/
H. Soliman, I. Abdelsalam, H. Wang, and F. Blaabjerg, “Artificial neural network based DC-link capacitance estimation in a diode-bridge frontend inverter system,” in Proc. IEEE 3rd Int. Future Energy Electron. Conf. ECCE Asia, 2017, pp. 196–201.
Everson Mattos, Lucas Cielo Borin, Caio Ruviaro Dantas Osório, Gustavo G. Koch, Ricardo C. L. F. Oliveira, Vinícius Foletto Montagner, "Robust Optimized Current Controller Based on a Two-Step Procedure for Grid-Connected Converters", IEEE Transactions on Industry Applications, vol.59, no.1, pp.1024-1034, 2023.
Kurokawa, F., Tanaka, M., Furukawa, Y., & Matsui, N. (2021). Recent Research Trends of Artificial Intelligence Applications in Power Electronics. International Journal of Renewable Energy Research, 11(3)
Jagdale, S. (2023, January 16). AI and the Evolution of Power Electronics. E-Power Journal. Retrieved from https://www.epowerjournal.com/2023/01/16/ai-and-the-evolution-of-power-electronics/
Paret, P., Finegan, D., and Narumanchi, S. (December 9, 2022). "Artificial Intelligence for Power Electronics in Electric Vehicles: Challenges and Opportunities." ASME. J. Electron. Packag. September 2023; 145(3): 034501. https://doi.org/10.1115/1.4056306
Sivadasan, B. (2018). Application of Artificial Intelligence in Electrical Engineering. GRD Journal for Engineering, 3(3), 105-111
Hore, D. (2018). Application of Artificial Intelligence and Machine Learning in the Field of Electrical Engineering: An Overview. International Journal of Advances in Science Engineering and Technology, 6(4), 10-15
Tripathi, K., & Shrivastava, S. (2022). Contemporary Implementation of Artificial Intelligence in Power Electronics: A Review. Specialusis Ugdymas / Special Education, 1(43), 1354-1364.
Rastgoufard, Samin, "Applications of Artificial Intelligence in Power Systems" (2018). University of New Orleans Theses and Dissertations. 2487.
P. Qashqai, H. Vahedi, and K. Al-Haddad, “Applications of artifical intelligence in power electronics,” IEEE Int. Symp. Ind. Electron., vol. 2019-June, pp. 764–769, 2019, doi: 10.1109/ISIE.2019.8781216.
E. Hossain, I. Khan, F. Un-Noor, S. S. Sikander, and M. S. H. Sunny, “Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review,” IEEE Access, vol. 7, pp. 13960–13988, 2019, doi: 10.1109/ACCESS.2019.2894819.
M. Jafari, Z. Malekjamshidi, J. Zhu, and M. H. Khooban, “A Novel Predictive Fuzzy Logic-Based Energy Management System for Grid-Connected and Off-Grid Operation of Residential Smart Microgrids,” IEEE J. Emerg. Sel. Top. Power Electron., vol. 8, no. 2, pp. 1391–1404, 2020, doi: 10.1109/JESTPE.2018.2882509.
B. Omrane, N. Mariun, I. Bin Aris, S. M. Bashi, and S. Taib, “Expert system-based approach to automate the design process of power electronics converters,” Proc. IEEE Power Eng. Soc. Transm. Distrib. Conf., vol. 3, no. ASIA PACIFIC, pp. 1943–1946, 2002, doi: 10.1109/tdc.2002.1177756.
Syed Ammar Shah , I. O. Habiballah, 2022, Applications of Artificial Intelligence Models in Power System Analysis, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 11, Issue 12 (December 2022),
Aalborg Universitet. (n.d.). AI-Power Artificial Intelligence for Next-Generation Power Electronics. Energy Technology. Retrieved from https://energiforskning.dk/en/node/16581
Shcherbatov, I.; Lisin, E.; Rogalev, A.; Tsurikov, G.; Dvořák, M.; Strielkowski, W. Power Equipment Defects Prediction Based on the Joint Solution of Classification and Regression Problems Using Machine Learning Methods. Electronics 2021, 10, 3145. https://doi.org/10.3390/electronics10243145
A. N. Babadi, M. T. Bina and R. Amjadifard, "A New Index for Reliability Assessment of Power Semiconductor Devices: IGBTs," 2022 13th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC), Tehran, Iran, Islamic Republic of, 2022, pp. 300-304, doi: 10.1109/PEDSTC53976.2022.9767227.
Simoes, M. G. (2022). A Review on Application of Artificial Intelligence Techniques in Microgrids. IEEE Journal of Emerging and Selected Topics in Industrial Electronics. https://doi.org/10.1109/JESTIE.2022.3198504
Simoes, M. G. (2021). Artificial Intelligence for Smarter Power Systems: Fuzzy logic and neural networks. ISBN-13: 978-1-83953-000-5.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 K. Vasudevan (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
