Aquifer thermal energy storage (ATES) air conditioning system can contribute to energy conservation by using the ground thermal energy and waste heat from buildings. The purpose of this study is to estimate its introduction effect and the influence of various conditions such as heat storage temperature in winter and operation methods in summer on energy conservation. In this study, we develop an ATES simulation model with a simulation tool using Modelica. We conduct simulation studies for 1case of an existing system and 3cases of ATES by changing the conditions of heat storage temperature and operation method. Through this simulation study, we show that setting the heat storage temperature at 13 degrees in winter improves the performance of the refrigerator compared to setting it at 6 degrees. In addition, we show that ATES, which sets the heat storage temperature at 13 degrees in winter and conducts heat source use in summer, is more effective for energy conservation, and that it can reduce power consumption by about 30.9% in a year compared with the existing system.

Since it is now possible to obtain detailed data for HVAC systems, it has become increasingly clear that there has been wastage during the operation of HVAC systems, which so far went unnoticed, and that there is room for further energy-saving. The aim of this study is to develop an optimal operation technology for HVAC systems. In order to achieve this, HVAC systems must operate according to the outside air conditions and load conditions to eliminate wasteful operation. A heat source system was modeled using an energy simulation tool, and the energy consumption of the system was calculated. The outside air conditions, load conditions, and cooling water temperature set point (outlet of cooling tower) were discretized for a case study. The influence of change in cooling water temperature set point on the energy consumption of the system was examined. By analyzing the trend, a relational formula for the optimal set point of cooling water temperature was derived. Using the relational formula, an optimal control method was applied to an actual heat source system. By introducing this method, the energy consumption of the system could be reduced by 3.3%. The effectiveness of the method was confirmed by a demonstration experiment.