New method for analytical photovoltaic parameters identification: meeting manufacturer’s datasheet for different ambient conditions

At present, photovoltaic energy is one of the most important renewable energy sources. The demand for solar panels has been continuously growing, both in the industrial electric sector and in the private sector. In both cases the analysis of the solar panel efficiency is extremely important in order to maximize the energy production. In order to have a more efficient photovoltaic system, the most accurate understanding of this system is required. However, in most of the cases the only information available in this matter is reduced, the experimental testing of the photovoltaic device being out of consideration, normally for budget reasons. Several methods, normally based on an equivalent circuit model, have been developed to extract the I-V curve of a photovoltaic device from the small amount of data provided by the manufacturer. The aim of this paper is to present a fast, easy, and accurate analytical method, developed to calculate the equivalent circuit parameters of a solar panel from the only data that manufacturers usually provide. The calculated circuit accurately reproduces the solar panel behavior, that is, the I-V curve. This fact being extremely important for practical reasons such as selecting the best solar panel in the market for a particular purpose, or maximize the energy extraction with MPPT (Maximum Peak Power Tracking) methods

Modelling Techniques for the Quantification of Some Electron Beam Induced Phenomena

This paper presents simulation models for quantifying the voltage contrast, cathodoluminescence and indirect specimen charging phenomena in the scanning electron microscope (SEM). The voltage contrast model comprises an electric field computation program using the finite-element approach, and a secondary electron trajectory tracking algorithm employing a linear electric field assumption. This trajectory tracking algorithm is more accurate than the conventional electron trajectory tracking algorithms which make use of a constant electric field assumption within each computation step. Using this model, results of qualitative voltage contrast effects on secondary electron trajectories in the specimen chamber of the SEM are shown. This model can also be used for quantitative voltage studies for designing low error voltage energy analysers. The cathodoluminescence (CL) model consists of programs for simulating the electron beam-specimen interaction via Monte Carlo analysis, excess carrier generation and distribution, and optical losses of the CL emission. This model has been used to simulate the CL intensity as a function of surface recombination velocity, diffusion length, and absorption coefficient. A model has also been developed to simulate indirect charging of specimens in the SEM. This model uses the finite-element method to solve for the self-consistent electric field due to the imposed boundary conditions, trapped and moving charges. Secondary electrons are tracked using the trajectory tracking scheme developed

Effect of shot noise and secondary emission noise in scanning electron microscope images

The effect of shot noise and emission noise due to materials that have different emission properties was simulated. Local variations in emission properties affect the overall signal-to-noise ratio (SNR) value of the scanning electron microscope image. In the case in which emission noise is assumed to be absent, the image SNRs for silicon and gold on a black background are identical. This is because only shot noise in the primary beam affects the SNRs, irrespective of the assumed noiseless secondary electron emission or backscattered electron emission processes. The addition of secondary emission noise degrades the SNR. Materials with higher secondary electron yield and backscattering electron yield give rise to higher SNR. For images formed from two types of material, the contrast of the image is lower. The reduction in image signal reduces the overall image SNR. As expected, large differences in delta or eta give rise to higher SNR images