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Erschienen in: Soft Computing 20/2020

08.04.2020 | Methodologies and Application

A strategy of PI + repetitive control for LCL-type photovoltaic inverters

verfasst von: Shengqing Li, Wen Chen, Baling Fang, Donghui Zhang

Erschienen in: Soft Computing | Ausgabe 20/2020

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Abstract

Due to the traditional grid-connected current control method of single Proportional Integral (PI) and Repetitive Control (RC) strategies, the photovoltaic inverter output current will have a distortion problem, which can not only maintain the stability of the whole photovoltaic system, but also the current quality of the photovoltaic inverter grid-connected system is reduced in the case of high-order LCL photovoltaic inverter control system operation. So, a strategy of PI + repetitive control in two-phase stationary frame is proposed. The introduction of the weighting coefficient m of the PI controller branch can enhance the adjustment ability of the PI link and accelerate the responding speed to meet the dynamic characteristics of the entire operating system, while the other weighting coefficient n on the repetitive controller branch can increase the correction capability and eliminate the steady-state error to meet system steady-state requirements. The scheme not only simplifies the coordinate transformation and decoupling calculation process, but also improves the harmonics suppression ability of the photovoltaic inverter and reduces the total harmonic distortion rate of the grid-connected current. At the same time, with the load operation mode change, the system can also retain better stability and keep a fast dynamic response capability, and the grid current can be able to return to a stable state in one cycle. Finally, the effectiveness of theoretical analysis and the strategy is verified by simulation.

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Metadaten
Titel
A strategy of PI + repetitive control for LCL-type photovoltaic inverters
verfasst von
Shengqing Li
Wen Chen
Baling Fang
Donghui Zhang
Publikationsdatum
08.04.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 20/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-020-04898-5

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