Abstract:
Efficient and reliable monitoring of a photovoltaic (PV) plant is essential to maintain the power generated at the desired specifications. In this thesis, we propose a method based on Virtual Instrumentation (VI) to realize a monitoring system for a 9.54 kWp PV system using both a Data Acquisition (DAQ) device and LabVIEW software. The implemented monitoring system is able to measure, display, analyze and record all the informative data of the Grid Connected PV System (GCPVS) via an intuitive and user-friendly interface in real-time. The measurements were well-calibrated with reference instruments. The second part of this thesis concerns the behavioral modeling of the PV generator and the inverter in order to estimate the electricity production and analyze the performance of the GCPVS. The results obtained from the empirical models were validated and calibrated by experimental data. A user interface for modeling and analyzing the performance of a PV system under LabVIEW has been designed.
The last part of this thesis is dedicated to the design of a simple and efficient diagnostic tool in order to detect and identify faults occurring in the PV system. The residuals were calculated with parametric and nonparametric models. While the analysis of the residual is performed using two fault detection techniques. The first technique is carried out by analyzing the Performance Loss Rates (PLR) of four electrical indicators, whereas the second technique is achieved using the Double Exponentially Weighted Moving Average (DEWMA) scheme. In order to evaluate the proposed techniques, different electrical faults and environmental anomalies occurring in the GCPVS were taken into account. The obtained results show that the detection and the identification of faults were successfully achieved
