A method for optimizing design of a ground source heat pump borehole system

Abstract

The application belongs to the technical field of ground source heat pumps, and particularly discloses a ground source heat pump buried pipe system optimization design method, which comprises the following steps: firstly, obtaining rock-soil heat conductivity coefficient data in a preset buried pipe arrangement area and a specific direction of an adjacent area; then, calculating an internal difference coefficient representing internal geological uniformity of the area and a regional difference coefficient representing geological difference between the internal and external areas based on the data; and finally, adaptively deciding and outputting a uniform or non-uniform buried pipe layout mode according to comparison of the two coefficients with a set threshold value. Through utilization of limited exploration data, the application realizes quantitative evaluation of spatial heterogeneity of the site geology, overcomes the problem of blindness in traditional methods in a non-homogeneous site, can optimize heat exchange resource allocation, improves long-term operation energy efficiency and heat balance reliability of the system, and meanwhile, improves the pertinence and reliability of the layout decision in a real non-homogeneous site with insufficient data.

Description

Technical Field

[0001] This invention belongs to the field of ground source heat pump technology, and more specifically, relates to an optimized design method for a ground source heat pump buried pipe system. Background Technology

[0002] Traditional ground source heat pump designs, based on static loads, struggle to cope with year-round dynamic loads and long-term heat accumulation, leading to a decline in system energy efficiency.

[0003] Existing technologies, such as the Chinese invention patent application with application number 202210427830.7, disclose a composite buried pipe ground source heat pump system and its optimization method. This method addresses load imbalance by combining vertical and horizontal buried pipes, and uses the ratio of dominant to non-dominant loads as the core for analytical iteration and length optimization to solve the problem of soil heat accumulation or cold attenuation during long-term operation.

[0004] However, this method, based on a homogeneous geological model and static load assumptions, cannot adapt to the heat exchange environment of real heterogeneous sites. Furthermore, its lack of management and optimization of layout methods leads to heat accumulation and accelerated failure in areas with poor thermal conductivity, while potentially resulting in wasted investment in areas with good thermal conductivity. Consequently, the long-term thermal balance and operational efficiency of the system cannot be guaranteed.

[0005] Existing technologies, such as the ground source heat pump buried pipe system disclosed in Chinese invention patent application number 202510820644.3, involve acquiring data through multiphysics transient simulation, predicting long-term dynamics using an LSTM model, and employing multi-objective optimization to find the optimal solution. This overcomes the shortcomings of traditional design methods, such as insufficient accuracy and inability to accurately predict the long-term dynamic performance of the system.

[0006] While this system can describe heterogeneous conditions, its accuracy is highly dependent on detailed and accurate geological spatial data. In actual engineering projects, due to exploration costs and technological limitations, data is often missing or distorted, making it difficult to achieve the expected prediction accuracy.

[0007] In summary, both existing optimization techniques fail to adequately consider the geological spatial anisotropy of real-world sites, resulting in insufficient applicability in heterogeneous environments and inaccurate long-term performance predictions. Summary of the Invention

[0008] In view of this, in order to solve the technical problem that the existing technology leads to blind layout design and failure to guarantee long-term thermal balance in heterogeneous sites due to insufficient data or inadequate utilization, an optimization design method for ground source heat pump buried pipe system is proposed.

[0009] The objective of this invention can be achieved through the following technical solution: This invention provides an optimized design method for a ground source heat pump buried pipe system. The method includes: acquiring the thermal conductivity data of soil and rock at least three internal test points spatially distributed within a preset buried pipe layout area, and acquiring the thermal conductivity data of soil and rock at at least two external test points in different orientations within a neighboring area adjacent to the preset buried pipe layout area.

[0010] Based on the thermal conductivity data of soil and rock at internal and external test points, the internal difference coefficient characterizing the geological uniformity of the pre-set buried pipe layout area and the regional difference coefficient characterizing the geological differences between the pre-set buried pipe layout area and the adjacent area are calculated.

[0011] The layout of underground pipes within the preset buried pipe layout area is determined and output based on the internal difference coefficient and the regional difference coefficient. The layout method can be either uniform or non-uniform.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention collects the thermal conductivity data of soil and rock in multiple preset orientations in the preset buried pipe layout area and the adjacent external area, and calculates the internal difference coefficient representing geological homogeneity and the regional difference coefficient representing regional difference, thereby realizing the quantitative evaluation of the spatial variability of site geological conditions. It provides an objective indicator for judging the degree of geological heterogeneity in the design stage, which helps to reduce the design deviation caused by assuming geological homogeneity or relying on unrepresentative data.

[0013] (2) Based on the internal difference coefficient and the regional difference coefficient, the present invention automatically determines the buried pipe layout method to be adopted. Then, according to the actual spatial distribution characteristics of the thermal conductivity of the stratum, it can adaptively select a uniform or non-uniform pipe layout strategy, so that standardized layout can be implemented in areas with good and uniform thermal conductivity to save costs, while targeted adjustments can be made in areas with large differences in thermal conductivity or weak areas, thereby optimizing the heat exchange resource configuration of the entire field and improving the overall energy efficiency of the system.

[0014] (3) By combining the building load type and the prevailing wind direction to select the location of external test points and assign differentiated weights, this invention can conduct targeted assessments of the main heat diffusion direction and potential heat barrier direction of the site boundary under limited exploration data conditions, thereby improving the pertinence and reliability of layout decisions in real heterogeneous sites with insufficient data.

[0015] (4) By calculating the thermal resistance tendency index, which reflects the spatial variation characteristics and relative thermal conductivity, this invention can accurately identify the direction that poses the greatest potential threat to regional thermal balance, thus providing a reliable data basis for subsequent calculation of regional difference coefficients. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the overall implementation process of the present invention.

[0018] Figure 2 This is a schematic diagram illustrating the overall process for determining the orientation of external test points in this invention.

[0019] Figure 3 This is a schematic diagram of the first test orientation determination process of the present invention.

[0020] Figure 4 This is a schematic diagram of the second test orientation determination process of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Currently, traditional ground source heat pump buried pipe designs typically assume that geological parameters are homogeneous and fixed values ​​for calculation. However, when faced with the spatial variability and uncertainty of parameters such as thermal conductivity and moisture content in actual sites, the design results based on the homogeneity assumption will deviate significantly from the heat transfer response in real heterogeneous strata. Existing methods may underestimate or ignore this, leading to problems such as localized heat accumulation, energy efficiency degradation, or investment waste during the long-term operation of buried pipe ground source heat pump systems.

[0023] This invention discloses an optimized design method for a ground source heat pump buried pipe system, which can effectively improve the adaptability of the design scheme to geological spatial heterogeneity and the reliability of long-term operation.

[0024] Specifically, please refer to Figure 1 As shown, Figure 1 This invention provides an optimized design method for a ground source heat pump buried pipe system. The method includes: S1, acquiring the thermal conductivity data of soil and rock at at least three internal test points spatially distributed within a preset buried pipe layout area, and acquiring the thermal conductivity data of soil and rock at at least two external test points in different orientations within a neighboring area adjacent to the preset buried pipe layout area.

[0025] The internal test points are spatially distributed in a triangular or grid pattern. When the area is approximately regular in shape, three points are selected at the center and relative edges of the area to form a triangle, maximizing spatial coverage representativeness. When the area is irregular in shape, a grid pattern is preferred to ensure that the internal test points are relatively evenly distributed within the pre-set buried pipe layout area, with a minimum of four points. The geographical coordinates of all test holes must be recorded.

[0026] Specifically, the thermal conductivity data of the soil and rock at the internal test points were collected in the following ways: thermal response tests were performed on each test borehole, or laboratory tests were conducted based on core samples to obtain the thermal conductivity data. For vertical boreholes, the thermal conductivity values ​​and corresponding layer thicknesses of different soil and rock layers were obtained along the borehole depth direction.

[0027] Traditional designs rely solely on the average parameters of a single or a few test points within a pre-defined buried pipe layout area, implicitly assuming uniform geological conditions and continuity with the outside. However, in actual engineering projects, significant differences (non-uniformity) may exist within the layout area, and the geological conditions outside its boundaries, such as lithology and water content, may be drastically different, thus forming barriers or channels for heat exchange. Therefore, this invention collects data from at least three spatially distributed points within the pre-defined buried pipe layout area, which can be used to preliminarily assess the dispersion of internal parameters.

[0028] Meanwhile, traditional single-point or unstructured multi-point testing cannot determine whether the measured differences exhibit spatial trends. The spatial distribution requirements of the internal test points specified in this step ensure that regardless of whether the geological heterogeneity is distributed in strips, patches, or gradual variations, the sampling network can capture this variation from at least one or more directions. A triangular layout is a minimal and stable structure that effectively assesses the differences between the center and the edges. A grid layout provides more comprehensive spatial coverage. This provides a reliable data foundation for subsequent calculations of the internal difference coefficient, which accurately reflects the internal heterogeneity of the region.

[0029] It should be understood that the adjacent area refers to the annular area surrounding the planned buried pipe layout area, or a strip-shaped area extending a predetermined distance along its outer boundary. This predetermined distance can be determined based on site conditions and design requirements. In a preferred embodiment, the predetermined distance is set to 1 to 2 times the planned buried pipe borehole spacing. When the site space for the planned buried pipe layout area is limited, the predetermined distance can be set to approximately 1 times the planned buried pipe borehole spacing to obtain boundary geological information within a limited space. When site space is sufficient, it can be set to approximately 2 times the planned buried pipe borehole spacing to obtain more comprehensive surrounding geological data.

[0030] Further, please refer to Figures 2 to 4 As shown, the two different orientations include the first test orientation and the second test orientation, and the steps for determining the first test orientation and the second test orientation are as follows: A1. Obtain the annual dynamic cooling and heating load data (usually hourly data) of the buildings served by the preset buried pipe layout area, calculate the total heat discharged to the ground and the total heat extracted from the ground throughout the year, obtain the cumulative heat discharged and the cumulative heat extracted, and calculate the difference between the cumulative heat discharged and the cumulative heat extracted.

[0031] A2. If the difference is greater than 0, the building's dominant load type is determined to be heat exhaust type; otherwise, the building's dominant load type is determined to be heat extraction type.

[0032] A3. Obtain long-term (usually no less than 10 years) site meteorological data for the pre-defined buried pipe layout area. If the dominant load type is heat exhaust, extract the dominant wind direction for summer (usually June, July, and August). If the dominant load type is heat extraction, extract the dominant wind direction for winter (usually December, January, and February). Use the downwind direction (i.e., the direction the wind is blowing) of this dominant wind direction as the first test azimuth. This azimuth represents the dominant path direction in which atmospheric convection is most likely to drive the horizontal migration of shallow surface heat during the main operating season of the system, i.e., the dominant heat diffusion direction.

[0033] It should be understood that the downwind direction of the prevailing wind direction, as the external test orientation, is mainly used to assess shallow surface heat exchange conditions and potential heat diffusion paths, and its long-term impact on the deep geothermal field can be used as an auxiliary reference factor.

[0034] A4. Obtain engineering geological survey data of the preset buried pipe layout area, identify whether there are known adverse geological structures, and if so, take the extension direction of the adverse geological structure as the second test direction.

[0035] It should be understood that the engineering geological survey data includes, but is not limited to, preliminary geological survey reports, regional geological maps, topographic maps, remote sensing image interpretation results, or historical site data. The adverse geological structures mainly refer to geological features that may significantly hinder underground heat conduction, such as known fault zones, lithological abrupt change zones, and underground cavities.

[0036] A5. If not, combine the contour map of the thermal conductivity of soil and rock to analyze the rate of change of the thermal conductivity of soil and rock in the horizontal direction. Based on the rate of change, identify the direction of thermal balance influence and take the direction of thermal balance influence as the second test direction. That is, the second test direction represents the direction of the main thermal resistance.

[0037] At least two external test points are respectively set up at the first test location and the second test location. If the first test location and the second test location coincide, then at least two external test points are set up at that location.

[0038] It is understood that the analysis method of the rate of change is as follows: the thermal conductivity of the soil and rock at each external test point is marked on a plane coordinate map, and a spatial interpolation method (such as Kriging) is used to generate a contour map of the thermal conductivity of the soil and rock in the region. The contour map can be completed using professional geological or GIS software. The Kriging method is an existing spatial interpolation method, and the specific interpolation process will not be described in detail.

[0039] On the generated contour map, radial profile lines are drawn from the center of the region to multiple main horizontal directions (such as east, south, west, and north). Along the profile line of a certain direction, N interpolation points (N≥3) are taken at fixed intervals (such as every 5 meters). The distance between these points is used as the independent variable, and the thermal conductivity of these points is used as the dependent variable to perform linear regression. The absolute value of the slope of the obtained regression line is the rate of change of thermal conductivity of that horizontal direction.

[0040] It is also understandable that the specific method for identifying the direction of influence of thermal equilibrium is as follows: for each horizontal profile, calculate the arithmetic mean of the thermal conductivity values ​​corresponding to each interpolation point, and use this as the mean thermal conductivity of that horizontal direction, denoted as . , Indicates the horizontal azimuth number. In the embodiments of the present invention, The preferred value is 4.

[0041] The rate of change of thermal conductivity in each horizontal direction is denoted as... Calculate the thermal resistance tendency index in each direction, denoted as The horizontal direction with the largest thermal resistance tendency index is taken as the direction of thermal balance influence.

[0042] The formula for calculating the thermal resistance tendency index is as follows: , The arithmetic mean of the target thermal conductivity of all internal test points in the pre-set buried pipe layout area. For thermal conductivity, relatively The smaller the value, the worse the thermal conductivity. In other words, the tendency for thermal resistance in a horizontal direction is related to the degree of its change. It is positively correlated with the relative strength of its own thermal conductivity. It also shows a positive correlation, when The lower the value (i.e., the worse the thermal conductivity), the higher the ratio. The larger the index The higher the value, the greater the resistance to thermal diffusion in that direction, and the higher the risk.

[0043] This step, when calculating the thermal resistance tendency index, comprehensively considers the degree and relative magnitude of the change in thermal conductivity in that direction, thereby more accurately determining the external test directions that need to be given priority. At the same time, it can also accurately identify the direction that poses the greatest potential threat to the regional thermal balance, thus providing a data basis for subsequent assessment of the geological differences between the pre-set buried pipe layout area and the adjacent area.

[0044] Traditional buried pipe designs often randomly place external test points based on site conditions or construction convenience, making it difficult to specifically assess boundary heat transfer risks. However, during long-term operation, the net heat generated by the imbalance between heating and cooling loads needs to diffuse into the surrounding earth. The prevailing seasonal wind direction, as the main natural force driving the convection and diffusion of shallow surface heat, makes the downwind direction a channel for heat dissipation (or cooling replenishment). Therefore, test points need to be placed in this wind direction to directly detect external geological conditions.

[0045] Secondly, geological structures such as faults and abrupt lithological changes often form low thermal conductivity barriers with extending directions, which may hinder lateral heat transfer. Even if heat dissipation conditions are good in other directions, if one side of the pre-planned buried pipe area is adjacent to such a barrier, heat can still easily accumulate and form local hotspots. Therefore, identifying and assessing such directional geological weak zones, i.e., identifying a second test location, and placing test points in this location, can proactively detect potential heat exchange obstacles and effectively avoid the risk of local thermal runaway.

[0046] By arranging internal and external test points in this step and acquiring data on the thermal conductivity of soil and rock, the complex risks of soil thermal accumulation and boundary heat transfer obstruction can be objectively characterized and assessed using two specific indicators: the internal difference coefficient and the regional difference coefficient. This provides a reliable data foundation for the subsequent calculation of the internal difference coefficient and the regional difference coefficient.

[0047] S2. Based on the thermal conductivity data of the soil and rock at internal and external test points, calculate the internal difference coefficient characterizing the geological uniformity of the pre-set buried pipe layout area and the regional difference coefficient characterizing the geological differences between the pre-set buried pipe layout area and the adjacent area.

[0048] In application scenarios with severe imbalances in heating and cooling loads, the long-term imbalance between underground heat input and extraction is the root cause of soil heat accumulation or cold decay. However, the spatial heterogeneity of geological conditions can alter and amplify the local effects of this thermal imbalance. This step aims to quantify the risk of this thermal imbalance by calculating two internal and regional difference coefficients.

[0049] Specifically, the implementation steps for calculating the internal difference coefficient characterizing the geological uniformity of the pre-designed buried pipe layout area are as follows: S21, for each internal and external test point, obtain its soil thermal conductivity data. For boreholes, the data includes the thermal conductivity values ​​of each soil layer traversed and the corresponding layer thickness.

[0050] S22. If the thermal conductivity data of a certain test point corresponds to only a single soil layer, then the thermal conductivity value of that layer is directly used as the target soil thermal conductivity of that point. If the thermal conductivity data of a certain test point corresponds to multiple soil layers, then the layer thickness of each soil layer corresponding to that test point is extracted.

[0051] S23. Divide the thickness of each soil and rock layer by the total thickness of all layers to obtain the thickness weighting coefficient of each layer. This coefficient is used to reflect the actual contribution ratio of strata of different thicknesses to the overall heat transfer capacity of the borehole.

[0052] S24. The thermal conductivity values ​​of each soil and rock layer are linearly weighted and summed with their corresponding thickness weight coefficients. The final result is taken as the target soil and rock thermal conductivity. The linear weighted summation uses an existing formula and will not be shown again.

[0053] S25. Collect the target soil thermal conductivity values ​​of all internal and external test points respectively, and construct the internal dataset accordingly. and external data sets The internal and external data sets are merged to obtain a fused data set. , , This represents the union operator.

[0054] S26. Assign weights to each data point in the fused data set, wherein data points in the internal data set are assigned a first weight value, data points in the external data set are assigned a second weight value, and the first weight value is greater than the second weight value.

[0055] The first weight value is preferably a fixed value of 1, which is used to ensure the dominant position of internal test data in the fused data set.

[0056] The second weight value is determined based on the layout orientation of its corresponding external test point, and is assigned a differentiated value according to the importance of different orientations to the thermal balance of the system, with a value range of [0, 1). The point located in the first test orientation is given the highest weight, for example, 0.8; the point located in the second test orientation is given the second highest weight, for example, 0.5; and the point located in other orientations is given the lowest weight, for example, 0.1.

[0057] Furthermore, in practical applications, implementers can make adaptive adjustments based on the risk control requirements of specific projects, while maintaining the aforementioned order of importance.

[0058] S27. Based on the fused data set and its corresponding weight allocation, the weight is multiplied by the target soil thermal conductivity value of the corresponding data point to obtain each weighted target soil thermal conductivity value, and a weighted target soil thermal conductivity value sequence is constructed. The mean and standard deviation of the sequence are calculated, and the standard deviation is divided by the mean to obtain the coefficient of variation. The coefficient of variation is output as the internal difference coefficient. The internal difference coefficient directly quantifies the dispersion of the heat exchange capacity of different points within the preset buried pipe layout area.

[0059] Traditional uniformity assessments calculate the coefficient of variation based solely on data from a few points within a pre-defined buried pipe layout area, failing to differentiate the importance of internal and external data. This step first aggregates the target soil thermal conductivity coefficients from all internal and external test points into a unified dataset. Simultaneously, to rationally utilize external reference data while ensuring the assessment focuses on the internal area, all values ​​from internal test points are assigned a higher fixed weight (the first weight value), while values ​​from external test points are assigned a lower weight (the second weight value) based on their specific location.

[0060] By setting this differentiated weight, the internal difference coefficient can be calculated based on the target soil thermal conductivity value of the internal test point. While making full use of the surrounding geological information to supplement the analysis, it avoids interference from abnormal test points on the true judgment of internal uniformity. This allows for a more accurate reflection of the actual dispersion level of the geological heat exchange capacity within the preset buried pipe area.

[0061] Specifically, the calculation process of the regional difference coefficient is as follows: calculate the arithmetic mean of the thermal conductivity of the target soil and rock corresponding to all internal test points in the preset buried pipe layout area, and use it as the internal mean.

[0062] Calculate the average value of the thermal conductivity of the target soil and rock at all external test points in the adjacent area, and use it as the external mean.

[0063] The absolute value of the relative deviation between the external mean and the internal mean is calculated and used as the regional difference coefficient.

[0064] This invention collects thermal conductivity data of soil and rock at multiple preset locations within the pre-set buried pipe layout area and its adjacent external areas, and calculates the internal difference coefficient representing geological homogeneity and the regional difference coefficient representing regional variability. This enables a quantitative evaluation of the spatial variability of site geological conditions, providing an objective indicator for judging the degree of geological heterogeneity during the design phase. It helps to reduce design deviations caused by assuming geological homogeneity or relying on unrepresentative data.

[0065] S3. Based on the internal difference coefficient and the regional difference coefficient, determine and output the layout mode of the buried pipe in the preset buried pipe layout area. The layout mode is either uniform or non-uniform.

[0066] Traditional decisions regarding the layout of underground pipelines often rely on the experience and judgment of designers, lacking unified quantitative standards. Faced with complex and heterogeneous geological spatial data, experience-based judgments are prone to bias, either leading to over-design due to excessive conservatism or under-design due to excessive optimism.

[0067] Based on this, this step determines and outputs the layout of underground pipes within the preset buried pipe layout area based on the internal difference coefficient and the regional difference coefficient.

[0068] Specifically, determining and outputting the layout of buried pipes within the preset buried pipe layout area includes: judging whether both the internal difference coefficient and the regional difference coefficient are less than the corresponding set threshold.

[0069] Understandably, the thresholds can be determined based on industry-recognized permissible levels of variation. For example, for most civil building projects, when the internal variation coefficient is below 0.25 and the regional variation coefficient is below 0.15, the site geological conditions can be considered to meet the requirements for uniform distribution. That is, the set thresholds for the internal variation coefficient and the regional variation coefficient can be 0.25 and 0.15, respectively.

[0070] If both the internal difference coefficient and the regional difference coefficient are less than their corresponding set thresholds, then the geological conditions of the preset buried pipe layout area are determined to meet the uniform layout requirements, and an instruction to adopt a uniform layout method is output. The uniform layout method refers to using a uniform drilling spacing and drilling depth for hole layout within the preset buried pipe layout area.

[0071] If at least one of the internal difference coefficient and the regional difference coefficient is greater than or equal to its set threshold, it is determined that there is a risk of local heat accumulation or a boundary heat exchange barrier, and an instruction to adopt a non-uniform layout method is output.

[0072] Understandably, the non-uniform layout method includes adjusting the borehole spacing of the buried pipe according to the spatial distribution of the thermal conductivity of the target soil and rock at the internal test points.

[0073] In one specific embodiment, the rule for adjusting the drilling spacing of the buried pipe is as follows: based on the spatial distribution of the internal test points, the preset buried pipe layout area is divided into multiple sub-regions, ensuring that each sub-region contains at least one internal test point, and the target soil thermal conductivity of the internal test points contained in each sub-region is taken as the target soil thermal conductivity of that sub-region.

[0074] If the thermal conductivity of the target soil and rock in a certain sub-region is higher than If the sub-region is determined to be a relatively efficient heat exchange zone, the borehole spacing can be increased. For example, it can be adjusted to 1.1 to 1.3 times the standard spacing. The higher the thermal conductivity of the target soil and rock, the closer the adjustment factor is to 1.3.

[0075] If the thermal conductivity of the target soil and rock in a certain sub-region is less than If the sub-region is determined to be a relatively inefficient heat exchange zone, the borehole spacing can be reduced, for example, by adjusting the borehole spacing to 0.7 to 0.9 times the standard spacing, and the smaller the thermal conductivity of the target soil and rock, the closer it is to 0.7.

[0076] If the thermal conductivity of the target soil and rock in a certain sub-region is equal to If so, the drilling spacing is set to the standard spacing.

[0077] Among them, standard spacing refers to the spacing based on The recommended borehole spacing is derived from the design methods recorded in the Technical Specification for Ground Source Heat Pump System Engineering, taking into account the building's design heating and cooling loads.

[0078] In this invention, the standard spacing refers to the arithmetic mean of the target thermal conductivity of the internal test points within the preset buried pipe layout area. The recommended borehole spacing, calculated based on the design heating and cooling loads of the building and the design methods specified in the Technical Specifications for Ground Source Heat Pump Systems, can be adjusted according to the actual engineering geological conditions, following the non-uniform layout principle of increasing the spacing in high-efficiency heat exchange zones and decreasing the spacing in low-efficiency heat exchange zones.

[0079] Furthermore, when the regional difference coefficient is greater than or equal to its set threshold, a monitoring hole or a reserved extension area is planned and set outside the preset buried pipe layout area.

[0080] This step automatically determines the appropriate buried pipe layout based on internal and regional difference coefficients. It can then adaptively select uniform or non-uniform pipe layout strategies according to the actual spatial distribution characteristics of the formation's thermal conductivity. This allows for standardized layouts to be implemented in areas with good and uniform thermal conductivity to save costs, while targeted adjustments can be made in areas with significant differences in thermal conductivity or weak areas. This optimizes the overall heat exchange resource allocation and improves the overall energy efficiency of the system.

[0081] This invention transforms the complex assessment of geological spatial heterogeneity into a clear numerical judgment by proposing two quantitative indicators: the internal difference coefficient and the regional difference coefficient. Furthermore, by combining information such as building load type, prevailing wind direction, and adverse geological structures, it guides the orientation and layout of external test points. This enables the accurate capture of boundary geological information that has the greatest impact on the system's thermal balance with limited exploration costs, thereby realizing the transformation from experience-based judgment or high-cost detailed simulation to quantitative decision-making based on limited data.

[0082] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. An optimized design method for a ground source heat pump buried pipe system, characterized in that, The method includes: The thermal conductivity data of the soil and rock at at least three internal test points spatially distributed within the preset buried pipe layout area are obtained, as well as the thermal conductivity data of the soil and rock at at least two external test points in different orientations within the adjacent area adjacent to the preset buried pipe layout area. Based on the thermal conductivity data of soil and rock at internal and external test points, calculate the internal difference coefficient characterizing the geological uniformity of the pre-set buried pipe layout area and the regional difference coefficient characterizing the geological differences between the pre-set buried pipe layout area and the adjacent area. The layout of underground pipes within the preset buried pipe layout area is determined and output based on the internal difference coefficient and the regional difference coefficient. The layout method can be either uniform or non-uniform.

2. The optimized design method for a ground source heat pump buried pipe system as described in claim 1, characterized in that: The spatial distribution of the internal test points is either triangular or grid-like.

3. The optimized design method for a ground source heat pump buried pipe system as described in claim 1, characterized in that: The adjacent area is a ring-shaped or strip-shaped area that is at a preset distance from the boundary of the preset buried pipe arrangement area.

4. The optimized design method for a ground source heat pump buried pipe system as described in claim 1, characterized in that: The two different orientations include a first test orientation and a second test orientation, and the steps for determining the first test orientation and the second test orientation are as follows: Obtain the annual dynamic heating and cooling load data of the buildings served by the preset buried pipe layout area, and calculate the net value of the cumulative heat dissipation and cumulative heat extraction; Based on the net value, the dominant load type of the building is determined, which is either heat exhaust-dominated or heat extraction-dominated. If the dominant load type is heat exhaust type, the dominant wind direction in summer of the preset buried pipe layout area is extracted; if the dominant load type is heat extraction type, the dominant wind direction in winter of the preset buried pipe layout area is extracted, and the downwind direction of the dominant wind direction is taken as the first test direction. Obtain engineering geological survey data of the preset buried pipe layout area, identify whether there are known adverse geological structures, and if so, take the extension direction of the adverse geological structure as the second test orientation. If not, combine the contour map of the thermal conductivity of soil and rock to calculate the rate of change of the thermal conductivity of soil and rock in the horizontal direction, identify the direction of thermal balance influence based on the rate of change, and take the direction of thermal balance influence as the second test direction; The at least two external test points are respectively set up at the first test location and the second test location. If the first test location and the second test location coincide, then at least two external test points are set up at that location.

5. The optimized design method for a ground source heat pump buried pipe system as described in claim 4, characterized in that: The method of identifying the location of thermal equilibrium influence based on the rate of change includes: Draw radial profiles from the center of the region outwards in multiple horizontal directions on the contour map; Along the profile lines in each horizontal direction, take a number of interpolation points at fixed intervals, calculate the arithmetic mean of the thermal conductivity values ​​corresponding to each interpolation point, and obtain the mean thermal conductivity value for each horizontal direction, denoted as . , Indicates the location number. ; Calculate the arithmetic mean of the target thermal conductivity at all internal test points within the pre-defined buried pipe layout area, denoted as . ; The rate of change of thermal conductivity of soil and rock in each horizontal direction is denoted as... Calculate the thermal resistance tendency index for each horizontal orientation. , ; The horizontal direction with the largest thermal resistance tendency index is taken as the direction of thermal balance influence.

6. The optimized design method for a ground source heat pump buried pipe system as described in claim 4, characterized in that: The calculation of the internal difference coefficient includes: For each of the internal and external test points, the thermal conductivity data of the soil and rock is obtained. For the data obtained through borehole testing, the thermal conductivity data of the soil and rock includes the thermal conductivity values ​​of different soil and rock layers in the borehole and the corresponding layer thickness. Based on the soil thermal conductivity data, determine the target soil thermal conductivity value for each test point; Collect the target soil thermal conductivity values ​​from all internal and external test points, construct internal and external datasets respectively, and integrate the internal and external datasets to obtain a fused dataset; A weight is assigned to each data point in the fused data set, wherein data points belonging to the internal data set are assigned a first weight value, and data points belonging to the external data set are assigned a second weight value, wherein the first weight value is a fixed value and the first weight value is greater than the second weight value; Based on the target soil thermal conductivity coefficient and its assigned weight for each data point in the fused dataset, a weighted target soil thermal conductivity coefficient sequence is constructed, the coefficient of variation of the sequence is calculated, and the coefficient of variation is output as the internal difference coefficient.

7. The optimized design method for a ground source heat pump buried pipe system as described in claim 6, characterized in that: The process for determining the thermal conductivity value of the target soil and rock is as follows: If the thermal conductivity data of the soil and rock at the test point corresponds to only a single soil and rock layer, then the thermal conductivity value of that layer is directly used as the target soil and rock thermal conductivity at that point. If the thermal conductivity data of the soil and rock at the test point corresponds to multiple soil and rock layers, extract the layer thickness of each soil and rock layer corresponding to the test point. Divide the thickness of each soil layer by the total thickness of all layers to obtain the thickness weighting coefficient of each layer. The thermal conductivity values ​​of each soil and rock layer are weighted and summed with their corresponding thickness weighting coefficients, and the final result is taken as the target soil and rock thermal conductivity.

8. The optimized design method for a ground source heat pump buried pipe system as described in claim 6, characterized in that: The second weight value is determined based on the layout orientation of its corresponding external test point. The point deployed in the first test orientation has the highest weight, the point deployed in the second test orientation has the second highest weight, and the point deployed in other orientations has the lowest weight.

9. The optimized design method for a ground source heat pump buried pipe system as described in claim 4, characterized in that: The calculation process for the regional difference coefficient is as follows: Calculate the arithmetic mean of the thermal conductivity of the target soil and rock corresponding to all internal test points in the preset buried pipe layout area and all external test points in the adjacent area, and use them as the internal mean and external mean, respectively. The absolute value of the relative deviation between the external mean and the internal mean is calculated and used as the regional difference coefficient.

10. The optimized design method for a ground source heat pump buried pipe system as described in claim 1, characterized in that: The method for determining and outputting the layout of underground pipes within the preset buried pipe layout area includes: Determine whether both the internal difference coefficient and the regional difference coefficient are less than the corresponding set threshold; If both are less than their set thresholds, the layout of the underground pipes in the preset buried pipe layout area will be a uniform layout. Otherwise, the output will show a non-uniform layout of the underground pipes within the preset buried pipe layout area.

Images