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As the global energy trend continues, the importance of energy savings and efficient use is being emphasized, and the installation and operation of geothermal heat pump systems is increasing. In many buildings, where an actual geothermal heat pump system has been installed, problems of efficiency deterioration occur frequently because of the inefficient operation after installation of the heat pump system. The purpose of this study was to develop and verify the operating method for energy saving and performance improvement of multiple geothermal systems. A coefficient of performance (COP) prediction model using an artificial neural network for real-time COP predictions was developed. The operating method of a multi-geothermal heat pump system using a variable water flow rate control method and COP prediction model was developed. The geothermal heat pump system operates sequentially depending on the water flow rate of the circulation pump. The COP prediction model enabled real-time performance prediction during system operation. The circulation water flow rate was reduced by up to 29% compared to the existing operating method. Approximately 23% of the energy was saved. The COP system, including the consumption power of the circulation pump, was improved.

Development of Operating Method of Multi-Geothermal Heat Pump Systems Using Variable Water Flow Rate Control and a COP Prediction Model Based on ANN