DocumentCode :
176184
Title :
Modeling research on ground-coupled heat pump system based on artificial neural network
Author :
Yating Zhang ; Weichang Jiang ; Ruihua Wang
Author_Institution :
Coll. of Elctronic & Control Eng., Beijing Univ. of Technol., Beijing, China
fYear :
2014
fDate :
May 31 2014-June 2 2014
Firstpage :
2320
Lastpage :
2323
Abstract :
As a new technology of renewable energy, ground-coupled heat pump system has been rising in our country in recently years. However because of the nonlinear and high degree of coupling, it is not clear to find out the relationship between control variables and total energy consumption of the system. This paper proposes a modeling way for ground-coupled heat pump system that uses artificial neural network, it builds the relationship between control variables and total energy consumption of the system directly. Through the comparison we can find a better way for building the Ground-coupled heat pump System.
Keywords :
ground source heat pumps; neurocontrollers; renewable energy sources; artificial neural network; control variables; energy consumption; ground coupled heat pump system; renewable energy source; Artificial neural networks; Atmospheric modeling; Educational institutions; Energy consumption; Heat engines; Heat pumps; BP neural network; LM algorithm; RBF neural network; ground-coupled heat pump system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
Type :
conf
DOI :
10.1109/CCDC.2014.6852559
Filename :
6852559
Link To Document :
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