ANN based optimization of a geothermal assisted hybrid cooling system in Simav, Turkey

作者：Arslan Oguz^*; Ozgur M Arif

来源：Energy Education Science and Technology Part A: Energy Science and Research , 2012, 28(2): 835-842.

• Geothermal Assisted Hybrid Cooling System
• ANN
• COP

In this study, the optimization of the geothermal assisted hybrid compressor and ejector refrigeration system using different refrigerants such as R717, R141b, R134a and R123 was performed by means of an Artificial neural network (ANN) model based on the generator temperature, condenser temperature, intercooler temperature and fluid types. The back-propagation learning algorithm with three different variants, namely Levenberg-Marguardt (LM), Pola-Ribiere Conjugate Gradient (CGP), and Scaled Conjugate Gradient (SCG) were used in the network to attain best approach. As result, COP value obtained with the ANN is found to be 3.43 when the generator temperature, condenser temperature, intercooler temperature, evaporator temperature and the algorithm are respectively 100 degrees C, 15 degrees C 13 degrees C, 0 degrees C and LM with 12 neurons in single hidden layer, for R717.

• 出版日期2012-1