توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Modeling Global Solar Radiation over Iran based on Meteorological Data Using ANN Technique
اطلاعات انتشار: یازدهمین کنفرانس سراسری سیستم های هوشمند، سال
تعداد صفحات: ۸
Among the renewable sources, Iran has a high potential of solar energy. The main step of designing new solar plants is sites selection. Monthly mean daily global solar radiation data are essential to achieve this important goal. However, these data are not available as a function of geographical and meteorological parameters. In this case, an ANN algorithm was engaged to establish a forward\reverse correspondence between the latitude, longitude, altitude, month of the year, minimum atmospheric temperature, maximum atmospheric temperature, minimum earth temperature, maximum earth temperature, relative humidity, wind speed, participation, atmospheric pressure, sunshine duration and monthly mean solar irradiation. For this purpose, the meteorological data of 31 stations of Iran along the years 1983–2005 were used as training (27 stations) and testing (4 stations) data. The Stepwise Multi Non–Linear Regression (MNLR) method was applied to determine the most suitable input variables. In order to investigate the effect of each meteorological variable, ten ANN–models were developed by using different combinations of the most suitable variables as inputs. The results showed that the ANN10 has a very good architecture for the prediction of monthly mean daily global solar radiation in Iran with an average correlation coefficient of more than 99.5% that performs a more accurate prediction than the other ANN models. It is concluded that the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment<\div>

۲EXPERIMENTAL INVESTIGATION AND PERFORMANCE ANALYSIS OF A POINT–FOCUS PARABOLIC SOLAR STILL
اطلاعات انتشار: اولین کنفرانس و نمایشگاه بین المللی انرژی خورشیدی، سال
تعداد صفحات: ۱۰
This study presents a design and performance analysis of a point–focus parabolic solar still (PPSS) during seven sunny, relative cloudy and dusty days in October. The variations of hourly and daily production rates were investigated by studying the effect of environmental and operational parameters composed of beam solar insolation, wind speed, air temperature, absorber temperature, preheating and salt concentration of raw water. The results indicated that the most effective parameter is available solar insolation and absorber temperature, as the most average daily production rate of 5.12 kg 〖day〗^(–1)was obtained on the day with the average solar insolation of 626.8 W m^(–2) and the average absorber temperature of 150.7℃. Whereas no significant effect of the air temperature and salt concentration of raw water was obtained. This means that the acceptable performance rate would be achieved by the solar still with high levels of solar insolation even in in cold and windy days. Based on the performance evaluation, the daily productivity of freshwater was increased up to 13% by preheating of raw water. The average daily efficiency of the still was calculated as 34.69% with the maximum hourly productivity of 1.5kg h^(–1). The quality of distillate from the still was analyzed to verify the ability of the still to meet the standards required for drinking water.<\div>

۳MODELING PRODUCTION OF A POINT–FOCUS PARABOLIC SOLAR STILL USING LOCAL WEATHER DATA AND ARTIFICIAL NEURAL NETWORKS
اطلاعات انتشار: اولین کنفرانس و نمایشگاه بین المللی انرژی خورشیدی، سال
تعداد صفحات: ۱۳
A study has been performed to predict distillate production of a point–focus parabolic solar still (PPSS) was operated for seven sunny, relative cloudy and dusty days in October. The aim of this study is to determine the effectiveness of modeling solar still distillate production using artificial neural networks (ANNs) and local weather data. A mathematical model is also presented to predict the thermal losses, and hourly productivity of the PPSS based on energy balance and heat transfer equations. The study used the environmental and operational variables affecting solar still performance, which are the hourly beam solar insolation, hourly air temperature, hourly wind velocity and wind incidence angle. The objectives of the study are to assess the sensitivity of the ANN predictions to different combinations of input parameters as well as to determine the minimum amount of inputs necessary to accurately model the solar still performance. The results showed that the ANN–model gave the best estimation with the accuracy of more than 99%. By using the correlation coefficient (R), it was found that 93–97% of the variance was accounted for by the ANN model. Satisfactory results for the PPSS suggest that, with sufficient input data, the ANN method could be extended to predict the performance of other solar still designs in different climate regimes<\div>
نمایش نتایج ۱ تا ۳ از میان ۳ نتیجه