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Mixed Step Size Normalized Least Mean Fourth Algorithm of DSTATCOM Integrated Electric Vehicle Charging Station

Publication Type : Conference Paper

Publisher : Institute of Electrical and Electronics Engineers (IEEE)

Source : IEEE Transactions on Industrial Informatics

Url : https://doi.org/10.1109/tii.2022.3211958

Campus : Coimbatore

School : School of Artificial Intelligence

Year : 2023

Abstract : The growth of electric vehicle loads increases the harmonics in the distribution grid. This article proposes a mixed step size normalized least mean fourth control algorithm (MSSNLMF) of distribution static compensator to alleviate the harmonics in the electric vehicles connected distribution grid. The overall system comprises bidirectional ac–dc, dc–dc converters, and distribution static compensator. The bidirectional converters are employed to achieve the vehicle to grid and grid to vehicle operations. A lithium-ion battery is utilized as an electric vehicle energy storage device. An adaptive MSSNLMF control algorithm is proposed to extract active and reactive power signals from the distorted load current to obtain the reference source currents. This algorithm combines the least mean fourth and normalized least mean fourth algorithms with mixed step size. The performance of the control algorithm is evaluated in the MATLAB/Simulink environment. It is experimentally verified through the real time simulation using the dSPACE (DS1202) real-time processor. The proposed MSSNLMF algorithm performs well in the DSTATCOM dc-link voltage regulation and reduction of total harmonic distortion. The source current total harmonic distortion is maintained below the allowable limit of IEEE 519-2014 standard.

Cite this Research Publication : Chelladurai Balasundar, Chinnayan Karuppaiyah Sundarabalan, Srinath Nangavaram Santhanam, Jayant Sharma, Josep M. Guerrero, Mixed Step Size Normalized Least Mean Fourth Algorithm of DSTATCOM Integrated Electric Vehicle Charging Station, IEEE Transactions on Industrial Informatics, Institute of Electrical and Electronics Engineers (IEEE), 2023, https://doi.org/10.1109/tii.2022.3211958

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