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A Novel DROGI-Based Detection Scheme for Power Quality Improvement Using Four-Leg Converter Under Unbalanced Loads.
- Source :
-
IEEE Transactions on Industry Applications . Jan/Feb2020, Vol. 56 Issue 1, p815-825. 11p. - Publication Year :
- 2020
-
Abstract
- In three-phase four-wire systems, the four-leg converter has been an attractive solution for mitigating power quality problems, such as reactive power compensation, load balancing, neutral current reduction, etc. However, its conventional control algorithms based on instantaneous reactive power theory (IRPT) and synchronous reference frame theory (SRFT) have relatively slow dynamic response and unstable operation during transient conditions. Thus, a novel control algorithm using double reduced-order generalized integrators for a four-leg shunt converter is presented in this article. The first integrator is adopted to extract required reference compensation currents for power quality improvement, and the second one is to decouple compensation currents and rectification currents of the converter side. The reference rectification currents are generated using an outer-loop dc-link voltage controller and are synchronized to the three-phase voltages. Since the compensation mode (dc–ac) and rectification mode (ac–dc) of converter are decoupled and regulated separately, the four-leg converter operation with fast dynamic response, robust performance, and flexible controllability is achieved. The effectiveness of the proposed algorithm is validated using both simulation and experimental results for a 1.1-kW rated system. Experimental results for the proposed scheme are presented and compared with that of existing IRPT and SRFT detection methods in the literature. [ABSTRACT FROM AUTHOR]
- Subjects :
- *REACTIVE power
*PHASE-locked loops
*LEG
Subjects
Details
- Language :
- English
- ISSN :
- 00939994
- Volume :
- 56
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Industry Applications
- Publication Type :
- Academic Journal
- Accession number :
- 141381321
- Full Text :
- https://doi.org/10.1109/TIA.2019.2942798