Adaptive Hybrid NFS-MSOGIQ Control Technique for Improving Power Quality in Solar PV Distributed Generation System

Abstract

A two-stage circuit configuration with 3-phase utility grid assisted solar power generation system is designed. In order to track the solar PV arrays maximum peak power (MPP), a DC boost converter with Composite Incremental Conductance (InC) MPP technique is employed in first stage. In Second stage, a grid-tied four-leg DC-AC converter, is employed to provide the solar power that was extracted into the utility grid and to enhancing power quality. An adaptive hybrid Multi-Second Order Generalized Integrator-Quadrature (MSOGI-Q) control algorithm, in conjunction with Neuro Fuzzy system (NFS) is proposed for controlling this DC-AC converter. MSOGI-Q reference current generation strategy is designed to mitigate current harmonics by retrieving the fundamental constituents from non-linear load. The Neuro Fuzzy system along with PID controller, by adjusting the voltage from dc link keeps consistent power in between AC and DC sides for varying isolation condition. To get the peak power out of a PV panel even in different environmental conditions, the composite incremental conductance algorithm is used. To upgrade the dynamic performance of voltage variation at Point of Common Coupling (PCC) a feedforward descriptor for Photovoltaic contributions has been implemented. In addition, a comparison between the proposed NFS-MSOGIQ control technique and the existing adaptive control technique is done to assess the effectiveness of the proposed adaptive control technique. The proposed adaptive control technique for the distributed generation system is designed and stimulated in MATLAB/SIMULINK and the simulation outcomes verify the effectiveness of the proposed control technique under various transition circumstances. A laboratory prototype model of the proposed system is developed for theoretical analysis and its results are found to be compliant with IEEE standards. Furthermore, THD values of voltage and current are found to be within standard limits.

Keywords:

• multi-second order generalized integrator-quadrature
• neuro fuzzy system
• maximum power point tracking
• point of common coupling
• power quality
• distributed generation

Disclosure statement

The authors have no conflicts of interest to declare. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report. We certify that the submission is original work and is not under review at any other publication.

Additional information

Notes on contributors

J. Sarawana Adchaya

J. Sarawana Adchaya received BE degree in Electrical and Electronics Engineering from Jeppiaar SRR Engineering College affiliated to Anna University, Chennai, Tamilnadu and ME degree in Power Electronics and Drives from Government College of Engineering, Tirunelveli, Tamilnadu. Currently she is pursuing her PhD degree at Faculty of Electrical Engineering at Anna University, Chennai, Tamil Nadu. Her research interest is in power converters, distributed generation and power system. Corresponding Author Email ID: [email protected].

C. Agees Kumar

C. Agees Kumar received the BE degree in Electronics and Instrumentation Engineering from National Engineering College, Kovilpatti affiliated to MS University, Tamil Nadu, India and ME degree from Annamalai University, Chidambaram, Tamil Nadu, India. He obtained his PhD degree from Anna University, Chennai, Tamil Nadu. Also, he is working as professor in the department of Electrical and Electronics Engineering at Arunachala College of Engineering for Women, Vellichandai, Tamil Nadu. His current research interest includes power electronics, electrical drives, soft computing, big data analytics and image processing. Email ID: [email protected].