Power Quality Enhancement of Three Phase Four Wire UPQC in Distribution System using Neural Network
J Shravani1, G. Deva Dasu2
1J Shravani, PG Scholar, Department of EEE, CMR College of Engineering & Technology, Kandlakoya, Hyderabad (Telangana), India.
2G. Deva Dasu, Head, Department, EEE, CMR College of Engineering & Technology, Kandlakoya, Hyderabad (Telangana), India.
Manuscript received on 19 August 2019 | Revised Manuscript received on 10 September 2019 | Manuscript Published on 17 September 2019 | PP: 1124-1132 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B10240882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1024.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The essential focus of this endeavor is examination of three phase four wire UPQC available for use structures by neural framework. The bound together power-quality conditioner (UPQC) is used to calm the current and voltage-related power-quality (PQ) issues in the meantime in three-arrange four-wire course structures. Among most of the PQ issues, voltage hang is a significant issue in three-arrange four-wire scattering systems. In this paper, another procedure is proposed playing out the plan parallel electrical cable trim. As such, despite when only a three-organize three-wire control structure is available at a plant site, the UPQC can do control line pay for presented loads that require a fair-minded channel to work. Not exactly equivalent to the control philosophies used in most of UPQC applications in which the controlled sums are nonsinusoidal, this UPQC uses a twofold pay technique, with the ultimate objective that the controlled sums are continually sinusoidal. Neural System controller have been used to make the proposed methodology online for least real power implantation with UPQC by using the PSObased data for different voltage rundown conditions. In the proposed system PI controller substituted by NN controller for better precision.
Keywords: Active Filter, Dual Control Strategy, UPQC, Neural Networks.
Scope of the Article: Low-power design