ADVANCEMENT IN CONTROL STRATEGIES OF CASCADED MULTILEVEL INVERTERS USING AI DRIVEN ALGORITHM
DOI:
https://doi.org/10.5281/zenodo.21412083Keywords:
Artificial Intelligence, Cascaded Multilevel Inverter, Machine Learning, Deep Learning, Total Harmonic Distortion, Power Quality, Control StrategiesAbstract
The growing demand for high-quality power conversion in renewable energy systems and industrial applications has driven advancements in control strategies for cascaded multilevel inverters (CMLIs). Conventional control methods often suffer from limitations such as high total harmonic distortion (THD), switching losses, and reduced adaptability under dynamic conditions. This paper presents an AI-driven approach for enhancing the control performance of CMLIs using techniques such as machine learning and deep learning. The proposed methods enable adaptive modulation, real-time optimization, and improved fault detection by leveraging system data including voltage levels, load variations, and switching states. Performance is evaluated using key metrics such as THD, efficiency, and response time, demonstrating superior results compared to traditional control techniques. The AI-based approach achieves reduced harmonic distortion, improved voltage quality, and enhanced system stability. Despite challenges related to computational complexity and data requirements, the findings highlight the potential of AI-driven algorithms in developing efficient, reliable, and intelligent inverter systems for modern power applications.
References
I. Lee, C., Tan, M., & Ho, J. (2022). Reinforcement learning for dynamic power inverter control. IEEE Transactions on Smart Grid, 13(1), 150-162.
II. Mishra, P., & Gupta, S. (2021). Artificial neural networks for real-time optimization of multilevel inverters. Energy Conversion & Management, 11(3), 112-126.
III. Patel, T., Sharma, K., & Das, P. (2022). IoT-integrated AI systems for predictive maintenance in power electronics. Renewable Energy & Smart Technologies, 15(2), 98-113.
IV. Sahoo, B., Reddy, K., & Das, A. (2020). Evolutionary algorithms for THD reduction in multilevel inverters. International Journal of Power Electronics, 25(4), 345-360.
V. Sharma, D., & Verma, R. (2021). Deep learning approaches for real-time control in renewable energy systems. Machine Learning Applications in Energy, 14(3), 189-203.
VI. Wang, Z., Chen, X., & Li, H. (2021). Fuzzy logic-based adaptive control of multilevel inverters. Journal of Renewable Power Systems, 19(1), 67-79.
VII. Richard Castillo, Bill Diong, Preston Bigger, “Single phase hybridcascaded H-bridge and multilevel inverter with capacitor voltagebalancing”, IET Power Electron,.2018, vol. 11 Iss. 4, pp. 700707.
VIII. Prabhat Ranjan Bana, Kaibalya Prasad Panda, “Recently Developed Reduced Switch Multilevel Inverter for RenewableEnergy Integration and Drives Application: Topologies, Comprehensive Analysis and Comparative Evaluation” IEEE access vol 7, may 2019.
IX. M. Chaulagain and B. Diong, “Forced Redundant States Of 5-LevelSingle Phase Diode Clamped Multilevel Inverters” 978-1-509022465/16/$31.00 ©2016 IEEE.
X. E. C. dos Santos and E.R.C. dasilva “Flying Capacitor Four Level H-Bridge Converter” IEEE access VOL 24, NO 1, Aug 2021.
XI. S.M, A. Parvathy “IMPROVED RELIABLE MULTILEVELINVERTER FOR RENEWABLE ENERGY SYSTEM” corpusID:84835837, 1ST JUNE 2019.
XII. Seong Cheol Kim, S. Narasimha “A New Multilevel Inverter with Reduced Switch Count for Renewable Power Application” International Journal of Power Electronics 2020.
XIII. T. Hussein “Multilevel Inverter Single Phase InverterImplementation for Reduced Harmonic Contents” International
XIV. Journal of Power Electronics and Drives 2021.
XV. Saqib Hayat, Shahzada Sufyan “63 Level Reduced SwitchAsymmetrical Cascaded H-Bridge Multilevel Inverter” 2020 IEEE23rd International multitopic conference.
XVI. Vinh-Quan Ngung-Tho “Reduction of Common Mode Voltage forCascaded Multilevel Inverter Using Phase Shift KeyingTechnique” Indonesian Journal of Electrical Engineering andComputer Sciences, February 2021.
XVII. R. Palanisamy, K Vijaykumar D “MSPM Based implementation of novel five level inverter with photovoltaic system”. International Journal of Power Electronics and drives system, vol8, No 4, pp 1494-1502, December 2019.
XVIII. N. Choi, j. G. cho “A General Circuit Topology of MultilevelInverter” IEEE Power Electronics specialized conference 2019.
XIX. I. H. Shanono, N. Abdullah “Five Level Single Source Voltage Converter Controller Using Selective Harmonic Elimination” Indonesian Journal of Electrical Engineering and ComputerSciences 2018.
XX. J. Dixon, L. Moran “High Level Multistep Inverter Optimizationusing a Minimum Number of Power Transistors” IEEE transaction on Power Electronics, vol,21, no 2, pp 330-337, march 2018.
XXI. Marif Daula Siddique, Saad Mekhilef. “A New Multilevel InverterTopology with Reduced Switch Count” IEEE Access VOL 7,2019.
XXII. S.M, A. Parvathy, “Improved reliable multilevel inverter forrenewable energy system” Indonesian Journal of Electrical Engineering and Computer Sciences, 1st June 2019.
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