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Journal Articles Applied Energy Year : 2015

Numerical and experimental results of a novel and generic methodology for energy performance evaluation of thermal systems using renewable energies

Abstract

8 At present there is no reliable approach to model and characterize thermal systems using renewable energy for building 9 applications based on experimental data. The results of the existing approaches are valid only for specific conditions (climate type 10 and thermal building properties). The aim of this paper is to present a generic methodology to evaluate the energy performance of 11 such systems. Artificial neural networks (ANNs) have proved to be suitable to tackle such complex problems, particularly when 12 the system to be modelled is compact and cannot be divided up during the testing stage. Reliable "black box" ANN modelling is 13 able to identify global models of the whole system without any advanced knowledge of its internal operating principles. The 14 knowledge of the system's global inputs and outputs is sufficient. The proposed methodology is applied to evaluate three different 15 Solar Combisystems (SCSs) combined with a gas boiler or a heat pump as an auxiliary system. The ANN models developed were 16 able to predict, with a satisfactory degree of precision, the annual energy consumption of the systems in different conditions, 17 based on a learning sequence lasting only 12 days. Annual energy prediction errors using the artificial neural models were less 18 than 10% in most cases. Perspectives and methodology limitations are discussed as well. 19
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Dates and versions

hal-01923841 , version 1 (15-11-2018)

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Amine Lazrak, Antoine Leconte, David Chèze, Gilles Fraisse, Philippe Papillon, et al.. Numerical and experimental results of a novel and generic methodology for energy performance evaluation of thermal systems using renewable energies. Applied Energy, 2015, 158, pp.142 - 156. ⟨10.1016/j.apenergy.2015.08.049⟩. ⟨hal-01923841⟩
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