Optimization of Working Ground Heat Storage With Seasonal Regeneration Available to Purchase

The aim of the research was an optimization of long-term heat storage with seasonal regeneration. Energy consumption for central heating during wintertime, transfererred from ground energy storage using a heat exchange device, is the operating principle of such systems. Warmed working fluid is then used in a heat pump system. However, more accurate calculations showed that over time of usage, there is a trend toward cooling at deeper round layers. Such a situation leads to a lowering of ground potential when using heat pump systems. A possible solution to this problem is the application of summer regeneration: during summer months, the working fluid is firstly warmed in solar collectors, and then forced into the same boreholes. The numerical model of a vertical, ground heat exchange device (configured as a "pipe in pipe", known as a Fields' pipe) was specially developed. Temperature distribution of the working fluid along the pipe was one of the boundary conditions, for the co-axial, time-variable, heat conduction task, which described the heat flow in energy storage. The numerical simulation of solar collectors work was based on the Hottel - Whillier - Bliss equation, in which energy flow from the solar collector is calculated, dependant on external parameters such as: insulation or ambience temperature. The combination of three computational parts- the ground heat exchange device, energy storage area and solar collectors battery- allows the target function to be defined for task optimization. The subject of optimization was an energy quantity, which can be taken from energy underground storage, and then utilized by the heat pump system. In the summarized paper, a combination of the input data, which influenced the efficiency of energy storage, was chosen. Hypothetical data were: outside diameter and length of heat exchange device, distance between pipes, fluid flow through the pipe during charge and discharge processes or temperature of inlet working fluid. The influence of individual parameters on the target function, holding all input data constant, was analyzed. A developed evolutionary numerical code known as GENOCOP I (GEnetic algorithm for Numerical Optimization for COnstrained Problems) [3] was used for optimization. After preliminary correction of boundary values of the input data, nine attempts of optimization were taken up. The research results identified optimal values of input parameters for which maximum energy could be taken from ground storage.