A bidirectional AC-DC interlinking converter, a power electronic device, efficiently transfers electrical power between direct current (DC) and alternating current (AC) in both directions. Previous standard articles on bidirectional AC-DC interlinking converters identified a variety of hurdles, such as control complexity, dynamic response restrictions, efficiency concerns, grid interaction issues, and scalability and modularity constraints. To solve these problems, this paper introduces a novel approach called the Coati-based radial basis controller (CbRBC). The CbRBC aims to enhance the performance of bidirectional AC-DC interlinking converters. Numerous evaluation metrics were used in the study, including power stability, switching loss, execution time, root mean square error (RMSE), mean absolute error (MAE), and decrease of total harmonic distortion (THD). In all those performance metrics, the proposed strategy has earned a better outcome than the traditional approaches. Hence, the proposed strategy has a lower THD of 0.702% with a 0.0008 s execution time, which is a quite optimized solution compared to the traditional models.

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Intelligent Bidirectional Controller Framework for AC-DC Interlinking Converter

  • Putchakayala Yanna Reddy,
  • Lalit Chandra Saikia

摘要

A bidirectional AC-DC interlinking converter, a power electronic device, efficiently transfers electrical power between direct current (DC) and alternating current (AC) in both directions. Previous standard articles on bidirectional AC-DC interlinking converters identified a variety of hurdles, such as control complexity, dynamic response restrictions, efficiency concerns, grid interaction issues, and scalability and modularity constraints. To solve these problems, this paper introduces a novel approach called the Coati-based radial basis controller (CbRBC). The CbRBC aims to enhance the performance of bidirectional AC-DC interlinking converters. Numerous evaluation metrics were used in the study, including power stability, switching loss, execution time, root mean square error (RMSE), mean absolute error (MAE), and decrease of total harmonic distortion (THD). In all those performance metrics, the proposed strategy has earned a better outcome than the traditional approaches. Hence, the proposed strategy has a lower THD of 0.702% with a 0.0008 s execution time, which is a quite optimized solution compared to the traditional models.