Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/841
Title: ICS solar water heater study using artificial neural networks
Authors: Souliotis, Manolis 
Tripanagnostopoulos, Yiannis 
Kalogirou, Soteris A. 
Souliotis, Manolis 
Tripanagnostopoulos, Yiannis 
Keywords: ICS solar water heaters
Artificial Neural Networks (ANN)
TRNSYS
Issue Date: 2006
Source: Proceedings of Eurosun 2006,Glasgow, UK.
Abstract: In this paper we present 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. We use the 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, to train the ANN. The ANN is then used though 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. We present the details of the calculation steps of both methods that aim to the accurate prediction of the system performance and we show that this new method can be used effectively for such predictions
URI: http://ktisis.cut.ac.cy/handle/10488/841
Rights: 2006 © Eurosun
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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