Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/4332
Title: | Modelling of an ICS solar water heater using artificial neural networks and TRNSYS | Authors: | Souliotis, Manolis Kalogirou, Soteris A. Tripanagnostopoulos, Yiannis |
Major Field of Science: | Engineering and Technology | Field Category: | Environmental Engineering | Keywords: | Solar water heaters;Integrated Collector Storage (ICS) system;Artificial Neural Networks (ANN);TRNSYS | Issue Date: | May-2009 | Source: | Renewable Energy, 2009, vol. 34, no. 5, pp. 1333-1339 | Volume: | 34 | Issue: | 5 | Start page: | 1333 | End page: | 1339 | Journal: | Renewable Energy | Abstract: | A study, in which a suitable artificial neural network (ANN) and TRNSYS are combined in order to predict the performance of an Integrated Collector Storage (ICS) prototype, is presented. Experimental data that have been collected from outdoor tests of an ICS solar water heater with cylindrical water storage tank inside a CPC reflector trough were used to train the ANN. The ANN is then used through the Excel interface (Type 62) in TRNSYS to model the annual performance of the system by running the model with the values of a typical meteorological year for Athens, Greece. In this way the specific capabilities of both approaches are combined, i.e., use of the radiation processing and modelling power of TRNSYS together with the “black box” modelling approach of ANNs. The details of the calculation steps of both methods that aim to perform an accurate prediction of the system performance are presented and it is shown that this new method can be used effectively for such predictions. | URI: | https://hdl.handle.net/20.500.14279/4332 | ISSN: | 09601481 | DOI: | 10.1016/j.renene.2008.09.007 | Rights: | © Elsevier | Type: | Article | Affiliation : | University of Patras Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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