The Experts below are selected from a list of 72 Experts worldwide ranked by ideXlab platform
S. O. Enibe - One of the best experts on this subject based on the ideXlab platform.
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thermal analysis of a natural circulation solar air heater with phase change material energy storage
Renewable Energy, 2003Co-Authors: S. O. EnibeAbstract:The transient thermal analysis of a natural convection solar air heater is presented. The heater consists of a single-glazed flat plate solar collector integrated with a paraffin type phase change material (PCM) energy storage subsystem and a rectangular enclosure which serves as the working chamber. The PCM is prepared in modules, with the modules equispaced across the absorber plate. The underside of the absorber plate, together with the vertical sides of the PCM module container, serve as air heating vanes. Air flow through the system is by natural convection. Energy balance equations are developed for each major component of the heater and linked with heat and mass balance equations for the heated air flowing through the system. The airflow rate is determined by balancing the buoyancy head resulting from thermally induced density differences and the friction head due to various flow resistances. The predicted performance of the system is compared with experimental data under daytime no-load conditions over the ambient temperature range of 19–41 °C and Daily Global Irradiation of 4.9–19.9 MJ m–2. Predicted temperatures at specific locations on the absorber plate, heat exchanger plate, glazing, and heated air agree closely with experimental data to within 10, 6, 8, and 10 °C, respectively. Maximum predicted cumulative useful and overall efficiencies of the system are within the ranges 2.5–13 and 7.5–18%, respectively. Correlations of the predicted efficiencies are presented.
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performance of a natural circulation solar air heating system with phase change material energy storage
Renewable Energy, 2002Co-Authors: S. O. EnibeAbstract:The design, construction and performance evaluation of a passive solar powered air heating system is presented. The system, which has potential applications in crop drying and poultry egg incubation, consists of a single-glazed flat plate solar collector integrated with a phase change material (PCM) heat storage system. The PCM is prepared in modules, with the modules equispaced across the absorber plate. The spaces between the module pairs serve as the air heating channels, the channels being connected to common air inlet and discharge headers. The system was tested experimentally under daytime no-load conditions at Nsukka, Nigeria, over the ambient temperature range of 19–41 °C, and a Daily Global Irradiation range of 4.9–19.9 MJ m−2. Peak temperature rise of the heated air was about 15 K, while the maximum airflow rate and peak cumulative useful efficiency were about 0.058 kg s−1 and 22%, respectively. These results show that the system can be operated successfully for crop drying applications. With suitable valves to control the working chamber temperature, it can also operate as a poultry egg incubator.
F O Akuffo - One of the best experts on this subject based on the ideXlab platform.
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the frequency distribution of Daily Global Irradiation at kumasi
Solar Energy, 1993Co-Authors: F O Akuffo, A BrewhammondAbstract:Abstract Cumulative frequency distribution curves (CDC) for Daily Global Irradiation on the horizontal produced by Liu and Jordan in 1963 have until recently been considered to have universal validity. Results obtained by Saunier et al. in 1987 and Ideriah and Suleman in 1989 for two tropical locations, Ibadan in Nigeria and Bangkok in Thailand, respectively, have thrown into question the universal validity of the Liu and Jordan generalized CDC. Saunier et al. , in particular, showed that their results disagreed with the generalized CDC mainly because of differences in the values of the maximum clearness index (Kmax), as well as the underlying probability density functions. Consequently, they proposed two expressions for determining Kmax and probability densities in tropical locations. This paper presents the results of statistical analysis of Daily Global Irradiation for Kumasi, Ghana, also a tropical location. The results show that the expressions of Saunier et al. provide a better description of the observations than the generalized CDC and, in particular, the empirical equation for Kmax may be valid for Kumasi. Furthermore, the results show that the values of the minimum clearness index (Kmin) for Kumasi are much higher than the generally accepted value of 0.05 for overcast sky conditions. A comparison of the results for Kumasi and Ibadan shows that there is satisfactory agreement when the values of Kmax and Kmin are comparable; in cases where there are discrepancies in the Kmax and Kmin values, the CDC also disagree.
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correlations between monthly average Daily Global Irradiation and relative duration of sunshine at kumasi
Energy Conversion and Management, 1992Co-Authors: E A Jackson, F O AkuffoAbstract:Abstract The Angstrom-Page type correlation between monthly average, Daily Global Irradiation on the horizontal and the monthly average relative duration of sunshine has been derived for Kumasi, Ghana, using 20 years data of measured values by the Ghana Meteorological Services Department. The correlations were carried out at three levels: for each month of the year; for the dry, wet and harmattan seasons; and for the full year. At the three levels, the maximum absolute errors in the estimated Global Irradiation are 0.59, 4.24 and 8.34%, respectively. The analyses were repeated after incorporating multiple reflections between the ground and sky and non-burning of the sunshine recorder chart when the solar elevation was below 4°. These latter considerations did not significantly affect the results.
F J Batlles - One of the best experts on this subject based on the ideXlab platform.
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Daily solar Irradiation estimation over a mountainous area using artificial neural networks
Renewable Energy, 2008Co-Authors: J L Bosch, Gabriel Lopez, F J BatllesAbstract:In order to design both active and passive solar energy systems, radiation data are needed for the studied location. The implementation of such renewable energy systems is especially important in places like natural parks, where acoustic and fossil fuel derived contamination has to be completely avoided. Measure of solar radiation is usually accomplished by means of radiometric station nets with a low spatial resolution. To estimate the radiation in sites located away from the stations, different interpolation/extrapolation techniques may be used. These methods are valid on places where the spatial variability of radiation is not significant, but becomes less accurate if complex terrain areas are present in between the radiometric stations. As an alternative, artificial intelligence techniques have been used in this work, along with a 20m resolution digital model of terrain. The inputs to the network have been selected using the automatic relevance determination methodology. The data set contains 3 years’ data of Daily Global radiation measured at 12 different stations located in the north face of the Sierra Nevada National Park in the surroundings of Hueneja (Granada), a town located in the South East of Spain. The stations altitude varies from 1000 to 1700m. The goal of this work has been to estimate Daily Global Irradiation on stations located in a complex terrain, and the values estimated by the neural network model have been compared with the measured ones leading to a root mean square error (RMSE) of 6.0% and a mean bias error (MBE) of 0.2%, both expressed as a percentage of the mean value. Performance achieved individually for each of the stations lies in the range [5.0–7.5]% for the RMSE and [−1.2 to +2.1]% for the MBE. Results point out artificial neural networks as an efficient and easy methodology for calculating solar radiation levels over complex mountain terrains from only one radiometric station data. In addition, this methodology can be applied to other areas with a complex topography.
A Khalil - One of the best experts on this subject based on the ideXlab platform.
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a profile free non parametric approach towards generation of synthetic hourly Global solar Irradiation data from Daily totals
Renewable Energy, 2021Co-Authors: Muhammed A Hassan, Mohamed Abubakr, A KhalilAbstract:Abstract Solar radiation is an essential input in the design and operation of many engineering systems. However, access to high-resolution data (hourly or sub-hourly) is usually limited, especially in developing countries, either due to its unavailability or expensive costs. A novel data-driven approach is proposed to predict the hourly Global Irradiation profiles from the cheaper and more likely available records of Daily Global Irradiation. The proposed approach is based on a prior categorization of hourly observations using the K-means clustering algorithm, followed by non-parametric function approximation using the multi-layered perceptron artificial neural network. This approach is applied to measured data (130,000 data points) at six locations in the North African Sahara, and the developed models are benchmarked against all existing parametric models in the literature. The artificial neural network-based models outperformed all existing models, with maximum and minimum coefficients of determination of 0.960 and 0.930, respectively. The non-parametric models also captured the true asymmetric profiles of hourly Irradiation with enhanced distributions of the residuals. Hence, the suggested models can be used to generate synthetic hourly data for multiple applications, most notably for building energy simulations and scheduling the operation of power generation systems.
Ahmad R Faghih - One of the best experts on this subject based on the ideXlab platform.
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empirical models for estimating Global solar radiation a review and case study
Renewable & Sustainable Energy Reviews, 2013Co-Authors: Fariba Besharat, A A Dehghan, Ahmad R FaghihAbstract:Solar radiation is a primary driver for many physical, chemical, and biological processes on the earth’s surface. Solar energy engineers, architects, agriculturists, hydrologists, etc. often require a reasonably accurate knowledge of the availability of the solar resource for their relevant applications at their local. In solar applications, one of the most important parameters needed is the long-term average Daily Global Irradiation. For regions where no actual measured values are available, a common practice is to estimate average Daily Global solar radiation using appropriate empirical correlations based on the measured relevant data at those locations. These correlations estimate the values of Global solar radiation for a region of interest from more readily available meteorological, climatological, and geographical parameters. The main objective of this study is to chronologically collect and review the extensive Global solar radiation models available in the literature and to classify them into four categories, i.e., sunshine-based, cloud-based, temperature-based, and other meteorological parameter-based models, based on the employed meteorological parameters as model input. Furthermore, in order to evaluate the accuracy and applicability of the models reported in this paper for computing the monthly average Daily Global solar radiation on a horizontal surface, the geographical and meteorological data of Yazd city, Iran was used. The developed models were then evaluated and compared on the basis of statistical error indices and the most accurate model was chosen in each category. Results revealed that all the proposed correlations have a good estimation of the monthly average Daily Global solar radiation on a horizontal surface in Yazd city, however, the El-Metwally sunshine-based model predicts the monthly averaged Global solar radiation with a higher accuracy.
