Improved control of photovoltaic interfaces

• Main Author: Xiao, Weidong
• Format: Others
• Language: English
• Published: University of British Columbia 2008
• Subjects: Photovoltaic; Solar; Interfaces; Power tracking
• Online Access: http://hdl.handle.net/2429/2393

Photovoltaic (solar electric) technology has shown significant potential as a source of practical and sustainable energy; this study focuses on increasing the performance of photovoltaic systems through the use of improved control and power interfaces. The main objective is to find an effective control algorithm and topology that are optimally suited to extracting the maximum power possible from photovoltaic modules. The thesis consists of the following primary subjects: photovoltaic modelling, the topological study of photovoltaic interfaces, the regulation of photovoltaic voltage, and maximum power tracking. In photovoltaic power systems both photovoltaic modules and switching mode converters present non-linear and time-variant characteristics, resulting in a difficult control problem. This study applies in-depth modelling and analysis to quantify these inherent characteristics,s pecifically using successive linearization to create a simplified linear problem. Additionally, Youla Parameterisation is employed to design a stable control system for regulating the photovoltaic voltage. Finally, the thesis focuses on two critical aspects to improve the performance of maximum power point tracking. One improvement is to accurately locate the position of the maximum power point by using centred differentiation. The second is to reduce the oscillation around the steady-state maximum power point by controlling active perturbations. Adopting the method of steepest descent for maximum power point tracking, which delivers faster dynamic response and a smoother steady-state than the hill climbing method, enables these improvements. Comprehensive experimental evaluations have successfully illustrated the effectiveness of the proposed algorithms. Experimental evaluations show that the proposed control algorithm harvests about 1% more energy than the traditional method under the same evaluation platform and weather conditions without increasing the complexity of the hardware. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate