Trainee Project
Title:
Fault detection and diagnosis algorithms for photovoltaic systems
Dates:
2019/04/01 - 2019/07/31
Supervisor(s): 
Description:
Photovoltaic systems (PVS) have grown rapidly in recent years due to their importance as sources of renewable energy in smart grids, buildings, etc. One of the main objectives of research on photovoltaic systems, for example those integrated into buildings, is to improve the efficiency, reliability and availability of the system. Although much work has been done on technology design to improve the efficiency of photovoltaic modules, little research has been conducted so far on the detection and diagnosis of failures for SPVs. These failures of a PV system, if not detected, can not only reduce power generation, but also compromise the availability and dependability of the entire system. The objective of this research internship is to first develop a basic simulation model of a photovoltaic system with possibly the maximum power point (MPPT) tracking using the MATLAB software. On the basis of the simulation model, an SPV model of various types of faults will be developed by modifying the conditions or inputs of the MATLAB model as well as the temporal parameters. Finally, on the basis of the retained faults, different detection and fault diagnosis techniques will be proposed.

Prerequisites: Good knowledge of the MATLAB / SIMULINK environment, some background on systems monitoring and fault diagnosis
Department(s): 
Control Identification Diagnosis