INTERNATIONAL CONGRESS ON RECENT ADVANCES IN SCIENCES AND TECHNOLOGY - Kuala Lumpur - Malaysia (2019-02-20)

Estimate the Ground Temperature around energy pile using Artificial Neural Networks
Ground source heat pump (GSHP) systems are using vertical ground heat exchangers, which are known as Borehole Heat Exchangers (BHEs), as a heat source or sink. The performance of the GSHP system strongly relies on the ground temperature surrounding the BHEs. This temperature depends on different parameters and varies during the operation times. Therefore, determination of the ground temperature is crucial to define the design the proper size of the BHEs so that the performance of the GSHP system is kept at the desired level. The current study aims to formulate the complex structure of artificial neural network (ANN) model in a mathematical equation that expresses the change in the ground temperature around BHEs due to heat injection in the long run. To fulfill the aim, a numerical model of BHEs was created using ANSYS to generate data. The generated data were used to train the ANN model, which was built for this study. The simulation shows that ANN can be used to determine the calculation of the ground in a GSHP system in high accuracy.
Dr. Mohamad Kharseh, Dr. Mohamed El koujok, Professor Holger Wallbaum