Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 153, Issue -, Pages 224-242Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2017.09.070
Keywords
Artificial neural networks; Comprehensive sensitivity analysis; Experimental study; Heat pumps; Soft computing and statistical tools
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A novel systematic practical approach to simulate the performance of heat pumps precisely is presented. In the proposed method, by conducting a number of experiments as well using soft computing techniques, the operation of all of the components is modeled comprehensively. The application of the method is examined for an experimental setup. The effective adjustable parameters are selected in a way that enabled them to be changed freely in the experimental setup. The Mean absolute error of prediction of coefficient of performance for validation measured experimental data is only 2.95%. In addition, to provide a comprehensive insight, an extensive sensitivity analysis considering nine performance parameters, such as mass flow rate of refrigerant and pressure drop of condenser, is conducted. It is found that the minimum possible is the best value of inlet temperature of water of condenser. Moreover, for inlet temperature of water of evaporator, frequency of compressor and degree of superheating which are the other adjustable effective parameters trade-offs among performance parameters are observed. For example, increasing the degree of superheating led to improve required work and isentropic efficiency of compressor as well as coefficient of performance and pressure drop of condenser, while it decreased the delivered heat.
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