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A novel maximum power point tracker for PV panels using switching frequency modulation

Tse, K.K., Ho, M.T., Chung, H.S.-H., Hui, S.Y.·2002·IEEE Transactions on Power Electronics

Abstract

A novel technique for efficiently extracting maximum power from photovoltaic (PV) panels is presented. The power conversion stage, which is connected between a PV panel and a load or bus, is a SEPIC or Cuk converter or their derived circuits operating in discontinuous inductor-current or capacitor-voltage mode. A method of locating the maximum power point (MPP) is based on injecting a small-signal sinusoidal perturbation into the switching frequency and comparing the AC component and the average value of the panel terminal voltage. Apart from not requiring any sophisticated digital computation of the panel power, the proposed technique does not approximate the panel characteristics and can globally locate the MPP under wide insolation conditions. The tracking capability has been verified experimentally with a 10 W solar panel under a controlled experimental setup. Performances under the steady state and in the large-signal change of the insolation level will are given.

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Metadata

Authors
Tse, K. K., Ho, M. T., Chung, H. S.-H., & Hui, S. Y.
Venue
IEEE Transactions on Power Electronics
Published
2002-11
Volume
17
Issue
6
Pages
980-989
ISSN
  • 0885-8993 (ISSN-L)
  • 1941-0107
OpenAlex
W2128919138
Cited by
172
References
0
FWCI
4.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A novel maximum power point tracker for PV panels using switching frequency modulation. https://app.cochat.ai/papers/10.1109/tpel.2002.805594
The paper
Tse, K. K., Ho, M. T., Chung, H. S.-H., & Hui, S. Y. (2002). A novel maximum power point tracker for PV panels using switching frequency modulation. IEEE Transactions on Power Electronics. https://doi.org/10.1109/tpel.2002.805594

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.