Influence of the time step in ann modelling of thermal stratification of solar storage

Research output: Conference contribution

Abstract

In the present work an artificial neural network (ANN) model is introduced which was elaborated for modelling the layer temperatures in a storage tank of a solar thermal system. The model calculates the temperatures of 8 equal layers of the storage tank in several time interval from the average time interval data of the solar radiation, the water consumption, the ambient temperature, the mass flow rate of collector loop and the temperature of the layers in the previous time-step. The used time intervals are one hour, 30, 10, 5, 2 and 1 minutes. The introduced ANN model is convenient for describing the system in every case, and the identified models give acceptable results inside the training interval. The average deviation was 0.53°C during the training and 0.76°C during the validation in case of hourly data and these data were 0.07°C and 0.08 in case of 1 minute time interval. The optimal time interval was found at 5 minutes.

Original languageEnglish
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Edition1 PART 1
DOIs
Publication statusPublished - dec. 1 2008
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of
Duration: júl. 6 2008júl. 11 2008

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume17
ISSN (Print)1474-6670

Other

Other17th World Congress, International Federation of Automatic Control, IFAC
CountryKorea, Republic of
CitySeoul
Period7/6/087/11/08

ASJC Scopus subject areas

  • Control and Systems Engineering

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    Farkas, I. (2008). Influence of the time step in ann modelling of thermal stratification of solar storage. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC (1 PART 1 ed.). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 17, No. 1 PART 1). https://doi.org/10.3182/20080706-5-KR-1001.2907