Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Faculty of Computing, Health and Science

School

School of Engineering / Centre for Communications Engineering Research

RAS ID

12908

Comments

This is an Author's Accepted Manuscript of: Al-Saedi, W. , Lachowicz, S. W., & Habibi, D. (2011). An optimal current control strategy for a three-phase grid-connected photovoltaic system using particle swarm optimization. Paper presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM). Wuhan, China. Available here

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Abstract

A robust current control strategy for PV (photovoltaic) grid-connected systems is required for reliable use of solar energy as an abundant and clean renewable energy. This paper presents real time optimization parameters of the current control strategy for a 3-phase photovoltaic grid-connected Voltage Source Inverter (VSI) system. The proposed controller scheme is implemented based on a synchronous reference frame; the Phase-Locked Loop (PLL) is used as grid phase detector. Particle Swarm Optimization (PSO) algorithm is an intelligent searching algorithm that is used to implement the real time self-tuning method for the current control parameters. Two conventional PI controllers are used and feed-forward compensation is applied with the inner inverter current control loop to achieve fast dynamic response. The main aim of this work is to achieve high dynamic response for the inverter output current with acceptable harmonics level in steady-state condition all of which is required for power quality improvement. The results show that the proposed strategy provides an excellent dynamic response within real time optimization.

DOI

10.1109/PEAM.2011.6134857

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free_to_read

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Link to publisher version (DOI)

10.1109/PEAM.2011.6134857