Enhanced Approaches to Modeling and Controlling of Photovoltaic Power Systems

Abstract

Reliable and accurate photovoltaic (PV) models are essential for simulating and designing solar power systems. A lack of such PV models in literature is one of the serious challenges facing PV power system designers and researchers. Latest PV models in literature suffer from low accuracy, parameterization complexity, low computational speed and singularity problems. This thesis proposes two newly developed PV models addressing the problematic aspects found in available PV models. In addition to that, it develops an innovative control structure for grid tied PV inverters which reduces control complexity and inverter cost. This work firstly proposes a very simple and easy-to-model PV modeling approach for implementation in simulations of PV power systems. It takes advantage of the simplicity of ideal models and enhances the accuracy by deriving a mathematical representation, capable of extracting accurate estimates of the model parameters, directly related to manufacturer datasheets. Experimental measurements proved the effectiveness of the proposed approach. A second approach is also proposed to further improve modeling performance. It ensures the best error minimization between the curvature of modeled curve and actual measured curve without a need for any additional measured points. The modeling approach is thoroughly evaluated by comparing the simulation results with experimental data of solar modules made of mono-crystalline, multi-crystalline, and thin film. Furthermore, this theses presents modeling, control, simulation and testing of a grid connected PV inverter. Finally, it develops an innovative current sensor-less control structure, for PV inverters, which reduces the high cost and complexity of available PV inverters.

Date of Award	Dec 2012
Original language	American English
Supervisor	Michael Weidong Xiao (Supervisor)