Journal
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING
Volume 43, Issue 4, Pages 1053-1073Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s40998-019-00215-5
Keywords
Artificial neural network PI (ANN-PI)-based controller; Wind energy conversion system (WECS); Reduced switch cascaded multilevel inverter (RSCMLI); Solid-state transformer (SST); Fuzzy logic controller (FLC); Doubly fed induction generator (DFIG)
Categories
Ask authors/readers for more resources
In this manuscript, artificial neural network PI (ANN-PI)-based controller is presented for a reduced switch cascaded multilevel inverter (RSCMLI) applied to wind energy conversion system (WECS) integrated with a solid-state transformer (SST). To improve the power quality by harmonic reduction, a seven-level RSCMLI is proposed. The utility-side parameters and the dc-link voltage of the inverter are regulated by fuzzy logic and ANN-PI-based controller, respectively. For better operational benefits, SST is applied in the distribution system instead of grid-side converter. The two objectives such as real power control and the reactive power support are provided by the machine interface converter and grid interface converter components of SST, respectively, particularly under insufficient wind energy generation condition. The proposed approach performs seamless fault ride through operation, by following the standard grid code requirements of WECS even under symmetrical and unsymmetrical fault condition. The efficacy of the proposed approach is validated by comparing the results with the PI-controlled conventional inverter under normal, symmetrical and unsymmetrical fault mode of operation.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available