Pan, X, Zhang, L, Li, Y et al. (2 more authors) (2022) Modulated Model Predictive Control with Common Mode Voltage Injection for MMCC-STATCOM Based Unbalanced Load Compensation. IEEE Transactions on Power Electronics, 37 (8). pp. 8948-8962. ISSN 0885-8993
Abstract
This paper presents a novel modulated model- predictive control (MMPC) scheme for Modular Multilevel Cascaded Converter-based STATCOMs (MMCC-STATCOM) to compensate unbalanced load current and regulate reactive power flow. By adding a common mode voltage (CMV) to the phase-voltages of the star-connected MMCC current model, the method allows natural injection of a non-sinusoidal voltage to the neutral point of the converter, hence achieving inter-phase cluster voltage balance. Moreover the imposed CMV is shown to extend the operating ranges of MMCC STATCOMs when used for negative sequence current compensation. The proposed MMPC method incorporates a modified branch and bound (B&B) algorithm to optimize the per-phase switch duty ratios. It is shown to be computationally more efficient compared to model-predictive control schemes using optimal voltage level method combined with voltage sorting schemes. Experimental results with different weighting factors confirm the effectiveness of this control scheme, and compared favorably with the conventional scheme of injecting only a sinusoidal zero sequence voltage.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Modulated model predictive control (MMPC) , Branch and bound method (B&B) , Multilevel modular cascaded converter-based STATCOM (MMCC-STATCOM) |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Apr 2022 07:34 |
Last Modified: | 19 Jul 2022 01:26 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/tpel.2022.3152407 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185436 |