A Novel Intelligent Neural Network Techniques of UPQC with Integrated Solar PV System for Power Quality Enhancement

5Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

A Novel Intelligent control of a Unified Power Quality Conditioner (UPQC) coupled with Photovoltaic (PV) system is proposed in this work. The utilization of a Re-lift Luo converter in conjunction with a Cascaded Artificial Neural Network (ANN) Maximum Power Point Tracking (MPPT) method facilitates the optimization of power extraction from PV sources. UPQC is made up of a series and shunt Active Power Filter (APF), where the former compensates source side voltage quality issues and the latter compensates the load side current quality issues. The PV along with a series and shunt APFs of the UPQC are linked to a common dc-bus and for regulating a dc-bus voltage a fuzzy tuned Adaptive PI controller is employed. Moreover, a harmonics free reference current is generated with the aid of CNN assisted dq theory in case of the shunt APF. The results obtained from MATLAB simulation.

Cite

CITATION STYLE

APA

Rudraram, R., Chinnathambi, S., & Mani, M. (2023). A Novel Intelligent Neural Network Techniques of UPQC with Integrated Solar PV System for Power Quality Enhancement. International Journal of Electronics and Telecommunications, 69(3), 605–613. https://doi.org/10.24425/ijet.2023.146514

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free