Browsing by Author "Devi, V.S.K."

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Comparative analysis of different machine learning techniques for condition monitoring of capacitors in a SEPIC converter
(Institute of Electrical and Electronics Engineers Inc., 2022) RAJENDRAN, S.; Jena, D.; Diaz-D, M.; Devi, V.S.K.
An efficient condition monitoring technique is essential for power converters to avoid unscheduled maintenance. In this work, the condition monitoring of capacitors in a single-ended primary inductance converter (SEPIC) is proposed based on the following machine learning classifiers: K nearest neighbor, support vector machine, back propagation neural network, Naive Bayes, and deep neural network. The feature of the machine learning algorithms is extracted by three node voltages such as voltage across $C$ 1,C2, and load. These features are utilized for training the algorithms. Moreover, the effectiveness of the different classifies are evaluated by considering the accuracy and area under the curve. Further, each algorithm is trained with a different percentage of a dataset. Finally, a comparative study has been made between the algorithms, and the results exhibit that the deep neural network performs better classification than other algorithms. Â© 2022 IEEE.
Comparative analysis of PID, I-PD and fractional order PI-PD for a DC-DC converter
(Institute of Electrical and Electronics Engineers Inc., 2022) Shanthini, C.; Devi, V.S.K.; RAJENDRAN, S.; Jena, D.
This article presents the design of fractional order PI-PD (FOPI-PD) controller for maintaining the output voltage of a buck converter. Initially, some conventional controllers were adapted, and these controllers introduced the overshoot and large settling time. Therefore, a FOPI-PD has been adapted to overcome the above limitations. The advantage of the FOPI-PD controller is that the error passes through the proportional and integral rather than all the controller gains, which reduces the overall control action. Further, the efficacy of the controllers is investigated in different simulation studies. The results show that the fractional order PI-PD controller significantly enhances the settling time in the presence of different load levels and controller disturbances. Â© 2022 IEEE.
Condition Monitoring of Submodule Capacitors in Modular Multilevel Converters—A Review
(Elsevier Ltd, 2025) Saravanakumar, R.; Sivakumar, N.; Devi, V.S.K.; Shanthini, C.; Jena, D.; Ibaceta, E.; Diaz-D, M.; Rodríguez, J.
Modular Multilevel Converters are highly promising power converter technologies used in high-voltage and high-power applications. The applications of modular multilevel converters are being increased in various industrial and renewable energy sectors due to their superior performance and efficiency. The modular multilevel converters contain multiple submodule capacitors, and these capacitors are the fragile components. The operating conditions and performance of these capacitors directly influence the system's reliability and operation. Hence, condition monitoring schemes are essential for submodule capacitors to ensure and enhance the modular multilevel converters operation which consequently reduces unscheduled maintenance. This article provides a detailed review and comprehensive analysis of condition monitoring schemes for submodule capacitors in modular multilevel converters. The review classifies the existing condition monitoring schemes into four major groups and thirteen subgroups and analyzes their methodologies using advantages and limitations of each scheme. Further, a critical analysis is presented with five significant parameters used to evaluate the condition monitoring schemes. The review highlighted the challenges related to condition monitoring accuracy, cost-effectiveness and system architecture that are to be studied in future. © 2025 Elsevier Ltd
Machine learning based condition monitoring of a DC-link capacitor in a Back-to-Back converter
(Institute of Electrical and Electronics Engineers Inc., 2022) RAJENDRAN, S.; Jena, D.; Diaz-D, M.; Devi, V.S.K.
The utilization of power electronic converters has increased, and the significance of continuous operation is essential in various applications. Therefore, proper condition monitoring (CM) is vital for power converters to eradicate unpredictable maintenance. However, the existing CM techniques may require additional sensors or injection of controlled voltage to the converters. The following machine learning algorithms, such as a K-nearest neighbors (KNN), Support Vector Machine (SVM), and Naive Bayes (NB), have been proposed to monitor the condition of the dc-link capacitor in a Back-to-Back (BTB) converter. The dc-link voltage is measured, and a wavelet decomposition is employed for the feature extraction. Moreover, the performance index evaluates the efficacy of the different classifiers. Further, different datasets have been considered for the evaluation of the classifiers. From this analysis, it is found that the SVM classifier performs better than others. Â© 2022 IEEE.
Wind Turbine Emulators—A Review
(Multidisciplinary Digital Publishing Institute (MDPI), 2023) RAJENDRAN, S.; Diaz-D, M.; Devi, V.S.K.; Jena, D.; Travieso-Torres, J.C.; Rodríguez, J.
Renewable energy sources have become a significant alternative energy source due to the continuing depletion of conventional energy sources and fluctuation in fuel costs. Currently, wind energy is the foremost among all other renewable energy sources. However, modeling and analyzing industrial wind turbines is complex as the wind turbine power ratio and size have steadily increased. Undoubtedly, industrial wind turbines are huge and challenging to keep in research labs; simultaneously, exploring the controller/power converter performance is practically impossible. Therefore, to overcome the above drawbacks, wind turbine emulators have been developed to achieve the static and dynamic characteristics of wind energy conversion systems. This paper aims to present a comprehensive review of the different wind turbine emulators available in the literature. In addition, the implementation of real-time emulators is classified according to the structure and approaches. Furthermore, an extensive analysis of the emulators was presented based on the significant parameters utilized for the real-time wind turbine emulators. Finally, this review analyzes the different emulator topologies according to cost, accuracy, complexity, and hardware implementation. © 2023 by the authors.