EE Seminar: Modeling Aspects in Photovoltaic Devices and Their Environmental Factors
~~Speaker: Assaf Peled,
M.Sc. student under the supervision of Prof. Joseph Appelbaum
Wednesday, March 4, 2015 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering
Modeling Aspects in Photovoltaic Devices and Their Environmental Factors
Abstract
The thesis study is organized in three sections which encompass topics from the fields of solar energy and photovoltaics. Thematically, the study first discusses how environmental factors affect PV systems, and then works its way down into the solar-cell level.
The first part concerns the energy production's intermittency of outdoor PV facilities due to stochastic movement of clouds. In this part, an analysis was conducted on global solar irradiance time-series under clear and overcast weather conditions. One effective method for isolating and identifying the underlying patterns of solar fluctuations is the use of wavelets and wavelet transform. A cross-correlation between a wavelet's waveform and a solar irradiance time signal produces a value which quantifies how similar those two functions are. Through a careful analysis, it is shown that although an outdoor PV system is frequently subjected to environmental changes, its power yield can be effectively predicted.
A novel solar spectral irradiance model based on artificial neural networks (ANN), is established in the second part of the thesis. The ANN typically starts with a learning phase, in which it learns to recognize persisting input-output relations. The model's output is gradually refined so as to minimize the error between the real-measured output data and the modeled outcome. Separate neural-networks are designated to simulate the spectral solar irradiance at a specific wavelength. The complete solar irradiance spectrum is assembled from all individual fractional spectra. The spectral model is further tested against an empirical measured spectral data, showing a remarkable performance under all-sky conditions.
In the third part of the thesis, methods to extract the electrical parameters of solar cells are presented based on the single-diode model and on the cell's I-V curve. Three different optimization methods are employed. The study aims to emphasize the discrepancies between the extraction's methodologies in terms of accuracy and time efficiency. All methods are tested against real measured parameter values of GaAs and a Multi-Junction cells.
