Abstract
In the present work, Artificial Neural Network (ANN) model has been developed to predict the energy and exergy efficiency of a roughened solar air heater (SAH). Total fifty data sets of samples, obtained by conducting experiments on SAHs with three different specification of wire-rib roughness on the absorber plates, have been used in this work. These experimental data and calculated values of thermal efficiency and exergy efficiency have been used to develop an ANN model. Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) learning algorithm were used to train the proposed ANN model. Six numbers of neurons were found with LM learning algorithm in the hidden layer as the optimal value on the basis of statistical error analysis. In the input layer, the time of experiments, mass flow rate, ambient temperature, mean temperature of air, absorber plate temperature and solar radiation intensity have been taken as input parameters; and energy efficiency and exergy efficiency have been taken as output parameters in the output layer. The 6-6-2 neural model has been obtained as the optimal model for prediction. Performance predictions using ANN were compared with the experimental data and a close agreement was observed. Statistical error analysis was used to evaluate the results. Citation:  Ghritlahre, H. K. (2018). Development of feed-forward back-propagation neural model to predict the energy and exergy analysis of solar air heater. Trends in Renewable Energy, 4, 213-235. DOI: 10.17737/tre.2018.4.2.0078
Highlights
In view of limited reserves of fossil fuels on the earth, it is necessary to develop efficient systems to use alternative sources of energy
The neural model has been developed with multilayer perceptron (MLP) structure using 6 parameters in the input layer and 2 parameters in the output layer
The 6-6-2 neural structure with LM learning algorithm is obtained as the optimal neural model for prediction of data
Summary
In view of limited reserves of fossil fuels on the earth, it is necessary to develop efficient systems to use alternative sources of energy. Many types of renewable energy are available on the earth, in which solar energy is one of the most abundant and clean sources of energy. Solar energy can be utilized in two ways: active and passive. In passive solar energy utilization, sun rays are directly used without the aid of any equipment. In the active way of utilization of solar energy, sun rays are not directly used, and some kind of mechanical equipment is needed for conversion of the solar energy into other forms of energy. Solar air heater (SAH) comes in the category of active solar energy utilization
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