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Recent Advances in Electrical & Electronic Engineering

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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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Research Article

Assessment of Power Quality Enhancement in a Grid-tied PV Network via ANN-based UPQC

Author(s): Ch. Phani Kumar*, E.B. Elanchezhian, Pragaspathy Subramani and S. Subramanian

Volume 17, Issue 5, 2024

Published on: 19 September, 2023

Page: [475 - 485] Pages: 11

DOI: 10.2174/2352096516666230822113234

Price: $65

Abstract

Background: Microgrid is the recent decade terminology that surpasses the long-run issues associated with the public and utility grids. Among the renewable energy sources, solar PV units have gained greater importance owing to their huge potential availability and laidback operating characteristics on technological grounds. Conversely, it offers pollution-free electricity and perhaps the dependability is volatile in most situations. The literature study accumulates the foresaid setback and presents the fluctuation-less and controlled standard quality of power outputs.

Objective: The aim of this particular research is to propose an assessment of Power Quality enhancement in a Grid-tied photovoltaic (PV) network via ANN-based UPQC. The novel idea behind this proposed approach is the UPQC component which deliberately regulates and controls the power system to achieve higher levels of power quality, ultimately meeting the recent IEEE standards.

Methods: This particular research enhances the performances of UPQC employed in the microgrid unit by replacing the traditional PI controller with a multi-layered feed-forward-type ANN controller for the current regulation of the series active filter. Additionally, a training algorithm for the ANN controller is built, trained and simulated via MATLAB/Simulink platform. The ANN-based UPQC is proposed to alleviate the power quality challenges like sag and swell in voltage, harmonic distortion, the time required for voltage compensation, and power factor. Therefore, UPQC is equipped to enrich the standard of power transfer at the point of common coupling inside the power frameworks, respectively.

Results: Finally, the simulation results are presented to validate the operation of the grid-tied PV network via an ANN-based UPQC system. To show the enriched performance of the proposed topology, a comparative analysis is made with PI controller-based UPQC, and outcomes infer to be in agreement with the theoretical discussions. Also, the ANN-based proposed approach reduces the restoration time and THD as well under both sag and swell conditions, respectively.

Conclusion: In this articulated work, a PV power system network with a DC-DC converter and three-phase inverter is employed for grid integration. The peak power extraction is ensured via a DC-DC converter with an incremental conductance algorithm. Both UPQCs are analysed and experimented via MATLAB/Simulink platform with inconstant nonlinear loads to investigate the indices mentioned above and corroborate the same within the operating regions.

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