Application of ANN technique to predict the performance of solar collector systems - A review

Harish Kumar Ghritlahre and Radha Krishna Prasad

Renewable and Sustainable Energy Reviews, 2018, vol. 84, issue C, 75-88

Abstract: The solar collector is the heart of any solar energy collection system designed for operation in the low to medium temperature ranges. So, an efficient design of solar collector system, giving optimum performance is required. Though system performance is optimized by many different techniques, however, intelligent system design is an useful technique to optimize the efficiency of such systems. One of the intelligence techniques is Artificial Neural Network (ANN), and it is used in modeling, simulation and control of the system. ANN tool is faster and more accurate to solve complex and nonlinear problems as compared to other conventional techniques. ANN technique is applied in the field of Science, Engineering, Medicine, Defense, Business and Manufacturing etc. The main task of ANN tool is training of structure, which is done by collected experimental data of solar energy systems and in this method separate programming is not required as in other conventional methods. The aim of this study is to review the applications of ANN to predict the performance of solar energy collector and to identify the research gap for future work. Published research works presented in this paper, show that the ANN technique is very appropriate tool to predict the performance of solar collector systems

Keywords: Solar energy collector; Artificial Neural Network; Learning algorithm; Multi-layer perceptron; Thermal performance (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (24)

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DOI: 10.1016/j.rser.2018.01.001

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