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Study on the Optimum Design of a Ground Heat Pump System Using Optimization Algorithms

机译:优化算法采用地热泵系统的最优设计研究

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摘要

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.
机译:地热能量引起了作为可以全年使用的高效能源的关注,但它具有相对较高的初始投资成本。对于地面源热泵(GSHP)系统的设计,通常使用用于确定系统能力以满足目标建筑物的峰值负荷的计算方法。然而,这种方法需要过度的系统能力设计,特别是关于具有部分负载操作的建筑物。在这项研究中,鉴于生命周期成本的成本,执行系统设计的优化。考虑了几种优化算法,例如离散的Armijo梯度算法,粒子群优化(PSO)算法和坐标搜索方法算法。优化的结果描述了系统能力(热泵,地面热交换器,热储罐等)和成本性能,表明与现有设计相比,总投资成本降低。

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