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A comparison of high-power converter topologies for the implementation of FACTS controllers

Soto, D., Green, T.C.·2002·IEEE Transactions on Industrial Electronics

Abstract

This paper compares four power converter topologies for the implementation of flexible AC transmission system (FACTS) controllers: three multilevel topologies (multipoint clamped (MPC), chain, and nested cell) and the well-established multipulse topology. In keeping with the need to implement very-high-power inverters, switching frequency is restricted to line frequency. The study addresses device count, DC filter ratings, restrictions on voltage control, active power transfer through the DC link, and balancing of DC-link voltages. Emphasis is placed on capacitor sizing because of its impact on the cost and size of the FACTS controller. A method for the dimensioning the DC capacitor filter is presented. It is found that the chain converter is attractive for the implementation of a static compensator or a static synchronous series compensator. The MPC converter is attractive for the implementation of a unified power flow controller or an interline power flow controller, but a special arrangement is required to overcome the limitations on voltage control.

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Metadata

Authors
Soto, D., & Green, T. C.
Venue
IEEE Transactions on Industrial Electronics
Published
2002-10
Volume
49
Issue
5
Pages
1072-1080
ISSN
0278-0046 (ISSN-L)
OpenAlex
W2169593248
Cited by
288
References
0
FWCI
5.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A comparison of high-power converter topologies for the implementation of FACTS controllers. https://app.cochat.ai/papers/10.1109/tie.2002.803217
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Soto, D., & Green, T. C. (2002). A comparison of high-power converter topologies for the implementation of FACTS controllers. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2002.803217

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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.