Thermosiphon solar domestic water heating systems: long-term performance prediction using artificial neural networks

Solar Energy ◽  
2000 ◽  
Vol 69 (2) ◽  
pp. 163-174 ◽  
Author(s):  
Soteris A Kalogirou ◽  
Sofia Panteliou
Solar Energy ◽  
1999 ◽  
Vol 65 (6) ◽  
pp. 335-342 ◽  
Author(s):  
SOTERIS A. KALOGIROU ◽  
SOFIA PANTELIOU ◽  
ARGIRIS DENTSORAS

1983 ◽  
Vol 105 (4) ◽  
pp. 430-439 ◽  
Author(s):  
S. A. Klein ◽  
A. H. Fanney

A rating procedure for solar domestic hot water systems is described which combines the advantages of short-term system tests and correlations of long-term thermal performance. The testing procedure consists of two indoor tests which are in accordance with ASHRAE Standard 95-1981, except for one additional measurement needed only for systems employing a heat exchanger between the collector fluid and the potable water. The test results are plotted in a manner in which they can be used to estimate the long-term performance of the solar water heating system for any location where site-specific, monthly-average meterological data are available. The annual solar function obtained in this manner provides the recommended rating indicator. The validity of this rating procedure is first demonstrated by simulations. Further support is provided by experiments conducted at the National Bureau of Standards.


2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Huai S. Xue

Long-term performance estimations were performed on a nonstandard domestic solar water heating system by f-Chart, interactive F-Chart software, and φ¯,f-Chart methods. Results of estimations were compared to gain insight of their applicability. Results from F-Chart software and f-Chart agree well and are greater than those from the φ¯,f-Chart method. Energy dumping should be given thorough reconsideration for the refinement of f-Chart and F-Chart software.


2016 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  

Abstract. This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R, of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analysed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations  >  85 %. Therefore, we can conclude that the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks on short-term and long-term timescales and, thus, it is suitable to be used in climate analysis.


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