Effinformer: A Deep-Learning-Based Data-Driven Modeling of DC-DC Bidirectional Converters

This article presents a data-driven modeling method founded on deep learning (DL) to precisely model and identify a dc-dc bidirectional converter that is widely used in renewable energy systems (RESs). In contrast to the circuit-theory-based methods that require dealing with a high number of circuit...

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Bibliographic Details
Published in:	IEEE transactions on instrumentation and measurement Vol. 72; pp. 1 - 13
Main Authors:	Shang, Qianyi, Xiao, Fei, Fan, Yaxiang, Kang, Wei, Qin, Haochen, Wang, Ruitian
Format:	Journal Article
Language:	English
Published:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Analytical models Circuits Complexity Computational modeling Data-driven modeling dc-dc bidirectional converter Deep learning deep learning (DL) Distillation informer Model accuracy Outliers (statistics) Predictive models self-attention Time series analysis Visualization
ISSN:	0018-9456, 1557-9662
Online Access:	Get full text
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