Optimizing configuration of middle-deep buried pipe ground source heat pump systems
As a building heat source,middle-deep buried pipe ground source heat pump systems have the characteristics of high energy efficiency and low pollution.Aiming at the research on the optimizing configuration of middle-deep buried pipe ground source heat pump systems,based on the actual energy demand of buildings,the simulation results of the heat transfer model of middle-deep buried pipes are fit by the measured data through reverse calculation,so as to obtain the comprehensive thermal properties of underground rock and soil.Furthermore,the theoretical calculations and dynamic simulation methods are used to conduct dynamic simulation calculations of heat transfer in middle-deep buried pipes under different operating strategies.By analyzing the temperature changes of under-ground rock and soil,inlet and outlet temperature data of buried pipes,the optimizing configuration scheme of middle-deep buried pipe ground source heat pump systems is a-chieved.Under the calculation conditions in this article,when the middle-deep buried pipe ground source heat pump system bears the design heating load of the project,sixty-five buried pipe heat exchangers with 2 500 m depth need to be configured.To fully utilize the heating capacity of the middle-deep buried pipe ground source heat pump systems under the maximum constant heating load,only twenty-four buried pipe heat exchangers are needed to meet the cumulative heat load demand of the building.Therefore,to balance the initial investment and operational performance of the system,the heat source should adopt a composite system form of middle-deep buried pipe ground source heat pump and auxiliary heat source,with the middle-deep buried pipe ground source heat pump system bearing the basic load,to fully utilize the heating capacity of the system and improve sys-tem economy.
middle-deep geothermal energyground source heat pumpoptimizing con-figurationthermal response of rock and soildynamic simulationoperational strategy
万方数据
维普
