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Abstract: The receiving ends of the solar energy conversion systems that generate heat or electricity from radiation is usually tilted at an optimum angle to increase the solar incident on the surface. Solar irradiation data measured on horizontal surfaces is readily available for many locations where such solar energy conversion systems are installed. Various equations have been developed to convert solar irradiation data measured on horizontal surface to that on tilted one. These equations constitute the conventional approach. In this article, an alternative approach, generalized regression type of neural network, is used to predict the solar irradiation on tilted surfaces, using the minimum number of variables involved in the physical process, namely the global solar irradiation on horizontal surface, declination and hour angles. Artificial neural networks have been successfully used in recent years for optimization, prediction and modeling in energy systems as alternative to conventional modeling approaches. To show the merit of the presently developed neural network, the solar irradiation data predicted from the novel model was compared to that from the conventional approach (isotropic and anisotropic models), with strict reference to the irradiation data measured in the same location. The present neural network model was found to provide closer solar irradiation values to the measured than the conventional approach, with a mean absolute error value of 14.9Wh/m2. The other statistical values of coefficient of determination and relative mean absolute error also indicate the advantage of the neural network approach over the conventional one. In terms of the coefficient of determination, the neural network model results in a value of 0.987 whereas the isotropic and anisotropic approaches result in values of 0.959 and 0.966, respectively. On the other hand, the isotropic and anisotropic approaches give relative mean absolute error values of 11.4% and 11.5%, respectively, while that of the neural network model is 9.1%. [Copyright &y& Elsevier]

This article presents modeling and experimental verification of conversion of solar irradiation from horizontal to sloped surfaces and photovoltaic cell temperature and an analysis of photovoltaic conversion efficiency. Modeling and validation of the models are carried out on the basis of measurements conducted using the experimental system set in a city in southern Turkey. In addition to current, voltage, and cell temperature of the photovoltaic module, environmental variables such as ambient temperature and solar irradiance were measured and used for validation purposes. Correlation of conversion of solar irradiation from horizontal to sloped surfaces indicated that the presently used model is highly successful because of the fitting parameters: the coefficient of determination , and the mean bias error . Similarly, the cell temperature model used in the present article is validated by the following correlation parameters: , , and root-mean-square error . [ABSTRACT FROM AUTHOR]

Abstract: This article analyses the energy statistics of 15 European Union countries (EU-15), giving special emphasis to the installed solar photovoltaic and thermal collector capacity. The installed capacities per capita are analysed in relation to the solar radiation income of respective countries with the view to explore the relationship between the solar income and its utilisation as of the year 2006. In terms of the installed solar thermal collector capacity, Austria leads the statistics amongst the countries studied with 223W th collector capacity per capita, followed by Greece with 207W th. Except for Greece, it is observed that the countries with high solar radiation income are lacking to realise their solar potential. Regarding the installed photovoltaic power per capita, Luxembourg leads the pack by a wide margin with 47W p capacity, followed by Germany with 30W p. Fiscal instruments to invigorate the deployment of solar energy have also been identified in this work. [Copyright &y& Elsevier]

Abstract: Light pipes are simple means of directing daylight (diffuse and direct light) into interior spaces. Previous work by the authors described the initial work on a luminous flux and illuminance predictive model for straight light pipes, using a basic equation for illuminance distribution as a function of horizontal distance. Further work has now produced a model that uses the cosine law of illuminance to describe the distribution of light from the light pipe diffuser as well as takes into account pipe elbow pieces or bends. The resulting illuminance model can be described as a quartic cosine model. By producing a “luxplot” prediction for any given light pipe application, it is possible to maximise the potential of these daylight providers and design their configuration to suit any given need. As part of this study, wide-ranging illuminance and luminous flux data were collected both for the formulation of this model (as the formula is semi-empirical) and its validation. [Copyright &y& Elsevier]

Delta-T Device Limited of Cambridge, UK have developed an integrated device which enables simultaneous measurement of horizontal global and diffuse irradiance as well as sunshine status at any given instance in time. To evaluate the performance of this new device, horizontal global and diffuse irradiance data were simultaneously collected from Delta-T device and Napier University's CIE First Class daylight monitoring station. To enable a cross check a Kipp & Zonen CM11 global irradiance sensor has also been installed in Currie, south-west Edinburgh. Sunshine duration data have been recorded at the Royal Botanical Garden, Edinburgh using their Campbell-Stokes recorder. Hourly data sets were analysed and plotted within the Microsoft Excel environment. Using the common statistical measures, Root Mean Square Difference (RMSD) and Mean Bias Difference (MBD) the accuracy of measurements of Delta-T sensor's horizontal global and diffuse irradiance, and sunshine duration were investigated. The results show a good performance on the part of Delta-T device for the measurement of global and diffuse irradiance. The sunshine measurements were found to have a lack of consistency and accuracy. It is argued herein that the distance between the respective sensors and the poor accuracy of Campbell-Stokes recorder may be contributing factors to this phenomenon. [ABSTRACT FROM PUBLISHER]

Provides information on a study on two models used to compute solar irradiance, namely the meteorological radiation model (MRM) and the cloud-cover radiation model (CRM). Overview on the models; Comparison between MRM and CRM; Conclusions.

Accurate solar radiation data are essential for the development of solar energy application systems. The limited availability of solar radiation data, and especially diffuse irradiance values, makes it vital to develop models to estimate these data. The development of estimation models has been the objective of many studies. This paper presents an extended review of the diffuse ratio (k) vs. clearness index (kt) annual, monthly, daily, and hourly frequency regression models. It is however interesting to note that there is a dearth of such knowledge for diffuse ratio–clearness index regressions that are based on averaged data. Monthly-averaged daily global irradiation data are now easily available from the NASA website for any global location. Using existing models, it is possible to decompose the daily to averaged-hourly global irradiation values. The missing link so far has been hourly averaged diffuse irradiation. This article presents regression equations which could be used to estimate that information. For this purpose, hourly global and diffuse irradiation data was pooled from 19 different locations to obtain three latitude-dependent regression models relating the monthly-averaged hourly diffuse ratio ( k ¯ ) to the clearness index ( k t ¯ ). The results show a high relationship between both variables. These regression equations could be used to estimate the averaged diffuse irradiation values from averaged global irradiation values, which are more easily available. [ABSTRACT FROM AUTHOR]

In the absence of ground reflected radiation measured data, an average albedo value of 0.2, which describes the reflective properties of the bare ground is generally used. The variation of albedo based on different foreground surfaces and under different atmospheric conditions is an area which is under research. This paper presents an experimental investigation of albedos of different foreground materials that can be used for photovoltaic (PV) applications. Overcast skies are predominant in northerly locations and will have a high frequency of low solar altitudes, and thus ground reflection is an important contributor towards total solar energy gain. The foreground surfaces include common materials: Grass, sand, and cement slabs, and some non-conventional materials: White pebbles, white boards, white tiles, and aluminium foil. The impact of factors, such as ageing, solar elevation, rain, and cloud cover (sky conditions) is analysed to determine the changes in albedos of these materials. Each material was observed to have individual performance characteristics under these factors. It was found that the non-conventional materials were least prone to weather-related changes and have higher albedo values as compared to the conventional materials, and also have good potential to replace the conventional materials for any given PV application. [ABSTRACT FROM AUTHOR]