Actual Optical and Thermal Performance of Photovoltaic Modules

Field testing is costly, time-consuming and depends heavily on prevailing weather conditions. Adequate security and weather protection must also be provided at the test site. Delays can be caused due to bad weather and system failures. To overcome these problems, a photovoltaic array simulation may be used. In any simulation scheme involving photovoltaic systems, one important choice is the selection of a mathematical model.In the literature several approaches to the problem have been made. Most procedures designed for this purpose are based on analytical descriptions of the physical mechanisms inside the solar cell that can be represented by a circuit diagram with discrete components, like a two-exponential model. Such simulators have some merits. However, their limited flexibility in readily simulating the influence of solar radiation, temperature and various array parameters is a serious drawback that has been noted. To get more accurate results in predicting the actual performance of photovoltaic modules, the parameters influencing incoming (optical parameters) and outgoing power flow (electrical and thermal parameters) were investigated by simulation and by some verifying experiments, to get a closer insight into the response behavior of this element, and to estimate the overall performance as well as optimization of the parameters

Comparison Between Atmospheric Turbidity Coefficients of Desert and Temperate Climates

Knowledge of the solar radiation available on the earth’s surface is essential for the development of solar energy devices and for estimating of their performance efficiencies. For this purpose it is helpful to study the attenuation of direct normal irradiance by the atmosphere, in terms of fundamental quantities, including optical thickness, relative optical air mass, water vapor content, and aerosol amount. In the present article, we will not deal with cloudy atmospheres because of their great variability in space and time, but will focus our attention on atmospheres characterized by the complete absence of condensed water. The objectives of this article are to report data on aerosol optical depth and atmospheric turbidity coefficients for a desert climate, and to compare them with those of a temperate climate. Aerosol optical depth, the Linke turbidity factor, TL, and ngström turbidity coefficients, _, are calculated from measurements of broadband filters at Helwan, Egypt, which has a desert climate. A linear regression model is to be determined between the Linke factor and the ngström turbidity coefficient. This relation is compared with similar relations reported for a temperate climate [Prague, Czech Republic]. This comparison is made to determine whether a universal relation exists between these two important coefficients, or whether the relation is location dependent

Ground-based measurements of UV Index (UVI) at Helwan

AbstractOn October 2010 UV Index (UVI) ground-based measurements were carried out by weather station at solar laboratory in NRIAG. The daily variation has maximum values in spring and summer days, while minimum values in autumn and winter days. The low level of UVI between 2.55 and 2.825 was found in December, January and February. The moderate level of UVI between 3.075 and 5.6 was found in March, October and November. The high level of UVI between 6.7 and 7.65 was found in April, May and September. The very high level of UVI between 8 and 8.6 was found in June, July and August. High level of radiation over 6months per year including 3months with a very high level UVI. According to the equation {UVI=a[SZA]b} the UVI increases with decreasing SZA by 82% on a daily scale and 88% on a monthly scale. Helwan exposure to a high level of radiation over 6months per year including 3months with a very high level UVI, so it is advisable not to direct exposure to the sun from 11am to 2:00pm

Temperature Distribution in Solar Cells Calculated in Three Dimensional Approach

Field-testing is costly, time consuming and depends heavily on prevailing weather conditions. Adequate security and weather protection must also provide at the test site. Delays can also be caused due to bad weather and system failures. To overcome these problems, a Photovoltaic (PV) array simulation may be used. For system design purpose, the model must reflect the details of the physical process occurring in the cell, to get a closer insight into device operation as well as optimization of particular device parameters. PV cell temperature ratings have a great effect on the main cell performance. Hence, the need for an exact technique to calculate accurately and efficiently the temperature distribution of a PV cell arises, from which we can adjust safe and proper operation at maximum ratings. The Scope of this work is to describe the development of 3D-thermal models, which are used to update the operation temperature, to get a closer insight into the response behavior and to estimate the overall performance

SignsWorld Atlas; a benchmark Arabic Sign Language database

Research has increased notably in vision-based automatic sign language recognition (ASLR). However, there has been little attention given to building a uniform platform for these purposes. Sign language (SL) includes not only static hand gestures, finger spelling, hand motions (which are called manual signs “MS”) but also facial expressions, lip reading, and body language (which are called non-manual signs “NMS”). Building up a database (DB) that includes both MS and NMS is the main first step for any SL recognition task. In addition to this, the Arabic Sign Language (ArSL) has no standard database. For this purpose, this paper presents a DB developed for the ArSL MS and NM signs which we call SignsWorld Atlas. The postures, gestures, and motions included in this DB are collected in lighting and background laboratory conditions. Individual facial expression recognition and static hand gestures recognition tasks were tested by the authors using the SignsWorld Atlas, achieving a recognition rate of 97% and 95.28%, respectively