DocumentCode :
3228845
Title :
Application of artificial neural network for electrical energy management of air-conditioning systems
Author :
Tsay, Ming-Tong ; Lin, Cheng-Pin
Author_Institution :
Dept. of Electr. Eng., Cheng-Shiu Inst. of Technol., Kaohsiung, Taiwan
Volume :
3
fYear :
2002
fDate :
28-31 Oct. 2002
Firstpage :
1954
Abstract :
In this paper, an artificial neural network (ANN) is employed to control the speed of compressor for accomplishing the electrical energy management of air-conditioning systems. On the basis of "the effective temperature figure" by ASHRAE, the theory of enthalpy was utilized to obtain both comfortable temperature point and minimizing the enthalpy of air-conditioning systems. The technology of the Levenberg-Marquardt (LM) procedure and radial basis function (RBF) neural network were introduced to perform the training and learning features. A practical air-conditioner with variable frequency control was used to measure the on-line room temperature and humidity change. The simulations of the ANN network have a good result with this standard and make possible an anticipated and optimal control strategy to balance thermal comfort, energy saving, and reliability.
Keywords :
air conditioning; angular velocity control; compressors; energy management systems; enthalpy; frequency control; humidity measurement; neurocontrollers; optimal control; radial basis function networks; temperature measurement; ANN; ASHRAE; Levenberg-Marquardt procedure; RBF neural network; air-conditioning systems; artificial neural network; comfortable temperature point; compressor; control strategy; effective temperature figure; electrical energy management; energy saving; enthalpy; humidity; learning features; radial basis function neural network; reliability; room temperature; thermal comfort; training; variable frequency control; Artificial neural networks; Control systems; Energy management; Frequency control; Frequency measurement; Humidity measurement; Neural networks; Optimal control; Temperature; Thermal variables measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN :
0-7803-7490-8
Type :
conf
DOI :
10.1109/TENCON.2002.1182721
Filename :
1182721
Link To Document :
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