| Summary: | Geothermal energy has attracted attention as a high-efficiency energy source that can be used year-round, but it has a relatively higher initial investment cost. For the design of ground source heat pump (GSHP) systems, a calculation method to determine the capacity of a system to meet the peak load of the target building is usually used. However, this method requires excessive system capacity design, especially regarding buildings with partial load operations. In this study, the optimization of a system design was performed in the view of the cost of the lifecycle cost. Several optimization algorithms were considered, such as the discrete Armijo gradient algorithm, a particle swarm optimization (PSO) algorithm, and a coordinate search method algorithm. The results of the optimization described the system capacity (heat pump, ground heat exchanger, thermal storage tank, etc.) and the cost performance, showing that the total investment cost was reduced compared to the existing design.
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