Performance optimization methods, devices, equipment and media for buried pipe heat exchange systems

Abstract

This invention provides a method, apparatus, equipment, and medium for performance optimization of a buried pipe network heat exchange system. The method includes: constructing a first dimensionless number to characterize the relative intensity of the convection effect and the thermal conductivity effect of the soil and rock caused by groundwater seepage, based on the thermal properties of the soil and rock and the seepage parameters of the groundwater; constructing a second dimensionless number to characterize the time scale of heat transfer affected by groundwater seepage and thermal diffusion of the soil and rock, based on the thermal properties of the soil and rock and the time parameters of the groundwater; constructing an integral form dimensionless temperature expression based on the first and second dimensionless numbers and the seepage parameters of the groundwater; iteratively updating the seepage parameters from a predetermined time, starting with the goal of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain target seepage parameters; and optimizing the performance of the buried pipe network heat exchange system based on the target seepage parameters.

Description

Technical Field

[0001] This invention relates to the field of ground source heat pump system optimization design technology, specifically to performance optimization methods, devices, equipment, and media for buried pipe group heat exchange systems. Background Technology

[0002] Buried pipe network heat exchange systems are widely used in various energy recovery and temperature control fields, especially in ground source heat pumps, underground thermal storage, heating, and cooling. These systems utilize the stable temperature environment of the Earth's surface through heat exchange between buried pipes and the ground to provide heating, cooling, and hot water to buildings. Compared to traditional air conditioning heating methods, buried pipe network heat exchange systems offer energy-saving advantages and can provide stable temperature control services to buildings without relying on traditional energy sources.

[0003] While current optimization of buried pipe network heat exchange systems takes into account the impact of groundwater seepage, it relies on the assumption of a homogenized seepage field or precise seepage parameters. However, directly and accurately measuring the seepage parameters of the groundwater seepage field in actual engineering sites is not only costly but also difficult to implement comprehensively. Therefore, the performance optimization of buried pipe network heat exchange systems still has shortcomings. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, equipment and medium for performance optimization of a buried pipe group heat exchange system.

[0005] One aspect of the present invention provides a performance optimization method for a buried pipe network heat exchange system based on the coupling effect of groundwater seepage and geothermal energy. The buried pipes in the network are each installed in boreholes within a soil layer to facilitate heat exchange between the multiple buried pipes and the soil within the soil layer. The performance optimization method includes: constructing a first dimensionless number based on the thermal properties of the soil and groundwater, as well as the groundwater seepage parameters, to characterize the relative intensity of the convection effect and the thermal conductivity effect of the soil caused by groundwater seepage; and constructing a second dimensionless number based on the thermal properties of the soil and groundwater, as well as a time parameter, to characterize the time scale of heat transfer affected by groundwater seepage and soil thermal diffusion. Based on the first and second dimensionless numbers and the groundwater seepage parameters, an integral form of dimensionless temperature expression is constructed. The range of the integral variable in the integral form is determined based on the first and second dimensionless numbers. This dimensionless temperature expression is used to determine the dimensionless temperature distribution of each buried pipe at different times and with different seepage parameters. Based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, the seepage parameters are iteratively updated with the objective of minimizing the difference between the dimensionless temperature in the dimensionless temperature distribution and the corresponding true temperature, resulting in target seepage parameters. Based on the target seepage parameters, the performance of the buried pipe group heat exchange system is optimized.

[0006] One aspect of the present invention provides a performance optimization device for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat. The buried pipes in the buried pipe group are each installed in boreholes within a soil layer to facilitate heat exchange between the multiple buried pipes and the soil within the soil layer. The performance optimization device includes: a first construction module for constructing a first dimensionless number characterizing the relative intensity of the convection effect and the thermal conductivity effect of the soil caused by groundwater seepage, based on the thermal properties of the soil and groundwater, and the seepage parameters of the groundwater; and a second construction module for constructing a second dimensionless number characterizing the time scale of heat transfer affected by groundwater seepage and thermal diffusion in the soil, based on the thermal properties of the soil and groundwater, and a time parameter. The third construction module is used to construct an integral form of a dimensionless temperature expression based on the first and second dimensionless numbers and the groundwater seepage parameters. The range of the integral variable in the integral form is determined based on the first and second dimensionless numbers. The dimensionless temperature expression is used to determine the dimensionless temperature distribution of each buried pipe at different times and with different seepage parameters. The iteration module is used to iteratively update the seepage parameters based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, with the goal of minimizing the difference between the dimensionless temperature in the dimensionless temperature distribution and the corresponding true temperature, to obtain the target seepage parameters. The optimization module is used to optimize the performance of the buried pipe group heat exchange system based on the target seepage parameters.

[0007] One aspect of the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above-described performance optimization method for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat.

[0008] One aspect of the present invention provides a computer-readable storage medium having a computer program or instructions stored thereon, wherein when the computer program or instructions are executed by a processor, the steps of the above-described method for optimizing the performance of a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat are implemented.

[0009] According to embodiments of the present invention, a dimensionless temperature expression is constructed based on the relative intensity of the convection effect and the thermal conductivity effect of soil and rock caused by groundwater seepage and the time scale of heat diffusion affected by groundwater seepage. This expression can determine the temperature field distribution around the buried pipe under the coupled effect of groundwater seepage and soil and rock thermal conductivity. Furthermore, by real-time monitoring of the actual temperature at the outlet of the buried pipe and combining iterative inversion analysis, the target seepage parameters are calculated. Based on the target seepage parameters, it is beneficial to more accurately predict changes in the heat exchange field, optimize the performance of the buried pipe group heat exchange system, improve the heat exchange efficiency and system stability of the buried pipe group heat exchange system, and at least partially solve complex problems that traditional static modeling methods cannot handle. This is conducive to the development and application of ground source heat pumps and other underground heat exchange technologies. Attached Figure Description

[0010] The above and other objects, features and advantages of the present invention will become clearer from the following description of embodiments of the invention with reference to the accompanying drawings.

[0011] Figure 1 A flowchart is shown below illustrating a performance optimization method for a buried pipe network heat exchange system based on the coupling effect of groundwater seepage and geothermal energy according to an embodiment of the present invention.

[0012] Figure 2 A schematic diagram illustrating the determination of target seepage parameters according to an embodiment of the present invention is shown.

[0013] Figure 3 A schematic diagram illustrating the effect of seepage on heat exchange of buried pipe groups according to a specific embodiment of the present invention is shown.

[0014] Figure 4A A schematic diagram of the layout of the underground pipe group before optimization according to a specific embodiment of the present invention is shown.

[0015] Figure 4B A schematic diagram of the optimized layout of the underground pipe network according to a specific embodiment of the present invention is shown.

[0016] Figure 5 A structural block diagram of a performance optimization device for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat according to an embodiment of the present invention is shown.

[0017] Figure 6 A block diagram of an electronic device according to an embodiment of the present invention is shown, which is suitable for implementing a performance optimization method for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy. Detailed Implementation

[0018] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the invention. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the invention for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0019] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0020] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0021] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0022] In realizing the concept of this invention, it was discovered that the performance of buried pipe heat exchange systems is affected by various factors, such as the coupling effect of groundwater seepage and geothermal activity, the velocity and direction of groundwater seepage, heat exchange with surrounding soil and rock, changes in groundwater temperature, seasonal variations, and differences in geological environment. However, current static models simulating the buried pipe heat exchange process neglect the interaction between groundwater flow and heat transfer. For example, using the heat conduction equation to calculate heat conduction in soil and rock ignores the role of water flow in this process, resulting in an inaccurate reflection of the true heat exchange performance in practical applications.

[0023] Although with the development of science and technology, research on heat exchange performance has combined groundwater flow and heat conduction to construct more complex numerical models to accurately predict the performance of buried pipe heat exchange systems, it is still limited to static scenario analysis and has certain shortcomings in the control and optimization of heat exchange systems in complex environments.

[0024] In view of this, embodiments of the present invention provide a performance optimization method for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy.

[0025] The following will be through Figures 1-4B The performance optimization method of the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy according to the embodiments of the present invention is described in detail.

[0026] Figure 1 A flowchart is shown below illustrating a performance optimization method for a buried pipe network heat exchange system based on the coupling effect of groundwater seepage and geothermal energy according to an embodiment of the present invention.

[0027] like Figure 1 As shown, the performance optimization method of the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat includes operations S110 to S150.

[0028] In operation S110, based on the thermal properties of soil and groundwater, as well as the seepage parameters of groundwater, a first dimensionless number is constructed to characterize the relative intensity of the convection effect and the thermal conductivity effect of soil and rock caused by groundwater seepage.

[0029] In operation S120, based on the thermal properties of soil and groundwater, as well as time parameters, a second dimensionless number is constructed to characterize the time scale of heat transfer affected by groundwater seepage and thermal diffusion in soil and rock.

[0030] In operation S130, based on the first dimensionless number and the second dimensionless number, as well as the seepage parameters of groundwater, an integral form of dimensionless temperature expression is constructed.

[0031] In operation S140, based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, the seepage parameters are iteratively updated with the objective of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain the target seepage parameters.

[0032] In operation S150, the performance of the buried pipe group heat exchange system is optimized based on the target seepage parameters.

[0033] In this embodiment, the thermal properties of the soil and groundwater may include, but are not limited to, density, specific heat capacity, and thermal conductivity. Groundwater seepage parameters may include the seepage velocity and seepage direction.

[0034] The magnitude of the first dimensionless number can reflect the relative strength of the convection effect and the conduction effect.

[0035] The magnitude of the second dimensionless number can reflect the relative speed of the heat diffusion process under the influence of groundwater seepage.

[0036] In the integral form, the range of the integral variable can be determined based on the first and second dimensionless numbers. The integral form shows that the temperature field is the superposition of contributions from an infinite number of instantaneous heat sources, reflecting the cumulative effect of the heat diffusion process. The integral variable is used to represent the range of effective thermal effects contributing to the current temperature field from a predetermined time to the present time.

[0037] The dimensionless temperature expression is used to determine the dimensionless temperature distribution of each buried pipe at different times and with different seepage parameters.

[0038] For example, initial seepage parameters can be input into a dimensionless temperature expression to calculate the dimensionless temperature of groundwater in each buried pipe. Then, the difference between the dimensionless temperature of groundwater in each buried pipe and the corresponding measured true temperature is calculated. With the goal of minimizing this difference, seepage parameters are iteratively inverted, and the initial seepage parameters are updated accordingly. The difference calculation is then repeated, and this process is repeated until the seepage parameter obtained when the difference meets a threshold is taken as the target seepage parameter. The initial seepage parameters can be randomly determined.

[0039] For example, performance optimization of a buried pipe network heat exchange system can be achieved by adjusting the geometric parameters of the buried pipe design. This could include adjusting the spacing between the buried pipes, adjusting the number of buried pipes, etc.

[0040] Based on the relative strengths of the convection effect and the thermal conductivity effect of soil and rock caused by groundwater seepage, and the time scale of heat diffusion affected by groundwater seepage, a dimensionless temperature expression is constructed. This expression can determine the temperature field distribution around the buried pipe under the coupled effect of groundwater seepage and soil thermal conductivity. Furthermore, by real-time monitoring of the actual temperature at the buried pipe outlet and combining iterative inversion analysis, the target seepage parameters are calculated. Based on these target seepage parameters, it is beneficial to more accurately predict changes in the heat transfer field, optimize the performance of the buried pipe group heat exchange system, improve its heat transfer efficiency and system stability, and at least partially solve complex problems that traditional static modeling methods cannot address. This is conducive to the development and application of ground source heat pumps and other underground heat exchange technologies.

[0041] According to embodiments of the present invention, seepage parameters may include seepage direction and seepage velocity.

[0042] For example, regarding the above Figure 1Operation S130, as shown, constructs an integral-form dimensionless temperature expression based on the first dimensionless number, the second dimensionless number, and the groundwater seepage parameters. This can include: combining the first dimensionless number and the angle variable representing the seepage direction to construct an exponential function-form heat diffusion term based on the enhancing or attenuating effect of the groundwater seepage direction on heat transport; combining the zero-order Bessel function with an exponential decay factor dependent on the integral variable to construct an exponential decay term in the integral kernel based on the radial diffusion attenuation of heat in the soil due to thermal conduction and the angle-dependent convective dissipation caused by groundwater seepage; and obtaining the dimensionless temperature expression by multiplying the heat diffusion term and the exponential decay term.

[0043] The heat diffusion term can quantify how groundwater seepage fundamentally changes and dominates the direction and efficiency of heat transport, and the directional heat transport enhancement / attenuation factor reveals the core characteristic of heat propagation in the seepage field, namely strong asymmetry.

[0044] The exponential decay term can represent the directional heat transport and dissipation caused by groundwater seepage.

[0045] The dimensionless temperature expression can be constructed analytically based on the following complete process from physical principles to mathematical solutions:

[0046] 1. Constructing the Energy Equation for Heat Transfer Characteristics of Buried Pipes: Based on the law of conservation of energy, considering the heat storage in the surrounding soil and rock, the convective heat transfer brought by groundwater flow, and the heat diffusion of the soil and rock media themselves, an energy equation for the heat transfer characteristics of buried pipes is constructed to describe the coupled heat transfer process of groundwater seepage and geothermal heat. This energy equation can be used to describe the heat transfer process in buried pipe groups due to the combination of groundwater flow and thermal conductivity of the soil and rock media.

[0047] The energy equation for the heat transfer characteristics of the buried pipe can be expressed as shown in equation (1) below:

[0048] (1)

[0049] in, This indicates the density of soil and rock, expressed in kilograms per cubic meter (kg / m³). This indicates the specific heat capacity of soil and rock, expressed in joules per kilogram per degree Celsius (J / kg·°C). This indicates the density of groundwater, expressed in kilograms per cubic meter (kg / m³). This indicates the specific heat capacity of groundwater, expressed in joules per kilogram per degree Celsius (J / kg·°C). Indicates groundwater in The velocity component in the direction, in meters per second (m / s); This indicates temperature, expressed in degrees Celsius (°C). Thermal conductivity of soil and rock is expressed in watts per meter per degree Celsius (W / m·°C). It represents the rate of change of temperature T with respect to time t, indicating the change of temperature over time; Indicates temperature T at The spatial gradient of the direction, that is, the change of temperature T along the seepage direction; and These represent temperatures T at... and The second spatial derivative in the direction represents the diffusion effect of temperature T in space.

[0050] Because in equation (1) Indicates the thermal storage of soil and rock. This represents the convective heat transfer of groundwater. The expression represents the thermal diffusion of the soil and rock medium. Therefore, it can be shown that the temperature change in equation (1) is the result of the combined effects of the soil and rock medium, such as the thermal storage of soil, the convection effect of groundwater flow, and the thermal conductivity of the soil and rock medium.

[0051] 2. Set the initial and boundary conditions for the energy equation of the heat transfer characteristics of the buried pipe:

[0052] Initial conditions: The temperature of the entire computational domain is uniformly distributed at the initial moment, which can be expressed as the first equation shown in equation (2) below.

[0053] Boundary conditions: At the wall of the buried pipe, the heat flux density is assumed to be known. This condition can be expressed in polar coordinates as the second and third equations shown in equation (2).

[0054] (2)

[0055] in, This indicates the initial temperature of the soil and rock, expressed in °C. Indicates temperature T at The direction, or the radial gradient, reflects the change in heat flow; This represents the heat transfer per unit pipe length, expressed in watts per meter (W / m). It indicates the heat power transferred from the buried pipe system to the soil and rock medium per unit pipe length l. The radial coordinates in the polar coordinate system represent the distance from the center of the buried pipe to a certain point. This relationship converts the two-dimensional rectangular coordinate system (x, y) to the polar coordinate system. The x-axis direction; The vertical axis represents the direction.

[0056] Equations (1) and (2) together constitute a complete mathematical boundary value problem. Dimensionless analysis and analytical solution of the boundary value problem yield a dimensionless temperature expression.

[0057] In dimensionless analysis, lengths (such as the radius of a buried pipe) are introduced. Based on characteristics such as temperature difference, dimensionless coordinates, dimensionless time, and dimensionless temperature are defined. The original equation, which contains multiple physical parameters, is simplified into an equation governed by a key dimensionless number.

[0058] In the process of solving the problem, two dimensionless numbers are derived: the first dimensionless number, such as the Reynolds number R, and the second dimensionless number, such as the Fourier number F0.

[0059] The first dimensionless number can be determined based on the amount of heat that groundwater can transport per unit time through a unit cross-sectional area in the x direction under a unit temperature difference, the radius of the buried pipe, and the thermal conductivity of the soil and rock, as shown in the first equation in equation (3). The larger R is, the more significant the contribution of groundwater seepage to heat transport is, and the more dominant the convection effect is relative to the thermal conductivity effect.

[0060] The second dimensionless number can be determined based on the square of the heat that groundwater can transport per unit time through a unit cross-sectional area in the x direction under a unit temperature difference, time t, and the thermal conductivity, density, and specific heat capacity of the soil and rock, as shown in the second equation in equation (3). The larger F0 is, the faster the heat propagation speed is under the influence of seepage, and the shorter the time scale of the heat diffusion process.

[0061] Mathematical physics methods, such as the integral transform method, can be applied to solve the dimensionless equation and obtain the dimensionless temperature expression, as shown in the third equation in equation (3):

[0062] (3)

[0063] in, This represents the amount of heat that groundwater can transport per unit time through a unit cross-sectional area in the x-direction under a unit temperature difference. This heat is then compared with the radius of the buried pipe. Multiplying yields the thermal conductivity of the soil and rock. Dimensionally consistent terms This is to facilitate dimensionless comparisons.

[0064] Equation (3) above is the final result of the mathematical derivation starting from formulas (1) and (2). Among them, Represents angle; a variable in polar coordinates. The variable representing the integral is used to represent a certain dimension of the one-dimensional thermal diffusion process. It is introduced into the integral expression as an auxiliary variable for handling the thermal diffusion process, and its upper limit can be... .pass Within a certain range, the heat distribution in the system changes due to the influence of thermal diffusion. exp represents an exponential function. This represents the heat diffusion term in the form of an exponential function.

[0065] This represents the exponentially decaying term in the integral kernel. The integral term contains... This can represent the heat decay effect. Related to the thermal diffusion rate, This represents the change in heat controlled by R and diffusivity.

[0066] By constructing a dimensionless temperature expression that integrates groundwater seepage parameters, a precise analytical characterization of the seepage-conduction coupled heat transfer process is achieved. This facilitates a shift from relying on difficult-to-obtain precise seepage parameters for forward prediction to using easily monitored temperature data to identify equivalent seepage intensity in reverse, thereby reducing survey costs and providing a reliable and practical solution for the design and performance optimization of buried pipe group heat exchange systems.

[0067] According to another embodiment of the present invention, the performance optimization method for a buried pipe group heat exchange system may include, in addition to the above-mentioned methods, the following: Figure 1 In addition to the operations S110 to S150 shown, the following may also be included: integrating and averaging the dimensionless temperature expression within a semi-circular profile perpendicular to the groundwater seepage direction, and obtaining an average dimensionless temperature expression including a first-order Bessel function and an exponential decay factor through mathematical transformation.

[0068] In this embodiment, the expression for the average dimensionless temperature can be used to determine the dimensionless temperature in the dimensionless temperature distribution while taking into account the borehole diameter.

[0069] Determining the overall strength of heat exchange between the buried pipe and the surrounding soil and rock is more engineering-significant than the temperature at a single point. A single index representing the overall thermal state of the soil and rock within a certain range around the borehole is needed; that is, the average dimensionless temperature considering the borehole diameter. Therefore, within the semi-circular profile perpendicular to the direction of groundwater seepage, i.e., within 0~π, the third equation shown in equation (3) above is integrated and averaged, and through mathematical transformation, the average dimensionless temperature expression shown in equation (4) is obtained:

[0070] (4)

[0071] in, This is a first-order Bessel function used to describe phenomena such as radiative heat transfer and vibration in circularly symmetric systems. In a first-order Bessel function, R / 2 is the independent variable. The stronger the seepage, i.e., the larger R, the larger the function value, and the higher the calculated heat transfer rate, or the wider the temperature influence range.

[0072] By integrating and averaging the dimensionless temperature expression within a semi-circular profile perpendicular to the groundwater seepage direction, the complex two-dimensional temperature distribution, which continuously varies with azimuth angle, is transformed into a single, stable, average dimensionless temperature that characterizes the thermal state of the entire vertical water flow profile. This temperature retains key heat transfer information in the upstream and downstream directions of the water flow, capturing the essential characteristics of the anisotropic thermal field. Furthermore, it simplifies the multidimensional field comparison problem in subsequent parameter inversion into a scalar optimization problem for a single eigenvalue. Thus, while ensuring physical accuracy, it significantly reduces the computational complexity of the inverse optimization algorithm, enhancing the overall engineering applicability and robustness of the method.

[0073] Figure 2 A schematic diagram illustrating the determination of target seepage parameters according to an embodiment of the present invention is shown.

[0074] According to embodiments of the present invention, for example, Figure 1 Operation S140, as shown, based on the initial seepage parameters and the dimensionless temperature expression, starts from a predetermined time and iteratively updates the seepage parameters with the objective of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain the target seepage parameters, which may include the following: Figure 2 Operations S241 to S244 are shown.

[0075] In operation S241, based on the initial seepage parameters, the dimensionless temperature of groundwater in each buried pipe is calculated using the expression for average dimensionless temperature.

[0076] In operation S242, a temperature matrix is ​​constructed based on the dimensionless temperature of groundwater in each buried pipe, with the buried pipe number in the buried pipe group as the matrix row and the time series as the matrix column.

[0077] In operation S243, based on the temperature matrix and the true temperature matrix, the square of the difference between the dimensionless temperature and the corresponding true temperature is calculated point by point.

[0078] In operation S244, based on the optimization algorithm, the seepage parameters are iteratively updated with the goal of minimizing the sum of multiple squared values ​​to obtain the target seepage parameters.

[0079] In this embodiment, the true temperature matrix is ​​constructed based on the true temperature of the groundwater in each buried pipe. Seepage parameters may include seepage velocity and seepage direction.

[0080] The dimensionless temperature of groundwater in each buried pipe can be calculated using the equation shown in the first equation of equation (5). The square of the difference between the dimensionless temperature and the corresponding true temperature can be calculated using the equation shown in the second equation of equation (5). With the goal of minimizing the sum of multiple squared values, an optimization objective function can be constructed as shown in the third equation of equation (5), and the target seepage parameters can be obtained from this function.

[0081] (5)

[0082] in, The underground pipe number is The average dimensionless temperature of the buried pipe. The underground pipe number is The underground pipe, in time The dimensionless temperature at that time. The underground pipe number is The underground pipe, in time The actual temperature at that time. The underground pipe number is The underground pipe, in time At an angle (That is, the direction of seepage) at the seepage velocity Dimensionless temperature at time. Seepage velocity. It can be an assumed flow rate, for example, typically 1×10⁻⁶. -7 ~5×10 -6 The value ranges from m / s. During the inversion process, the seepage velocity can be determined within this range for inversion. The buried pipe number is... … … . Indicates the angle (That is, the direction of seepage) at the seepage velocity The sum of multiple squared values ​​at time. This represents the objective function to be optimized.

[0083] This invention progressively refines seepage parameters until the target seepage parameters that best match the actual thermal response data are obtained. It achieves the inversion of groundwater seepage parameters from temperature monitoring data, improving the objectivity and accuracy of parameter calculations.

[0084] According to an embodiment of the present invention, the optimization algorithm may include a sequential quadratic programming algorithm. Based on the optimization algorithm, with the objective of minimizing the sum of multiple squared values, the seepage parameters are iteratively updated to obtain the target seepage parameters. This may include: using the seepage parameters of the (n-1)th round as the iteration point of the (n-1)th round, performing a second-order Taylor expansion on the objective function, and linearizing the constraints on the seepage parameters to construct a quadratic programming subproblem; solving the quadratic programming subproblem based on the sum of multiple squared values ​​of the (n-1)th round to obtain the nth adjustment amount of the seepage parameters; updating the seepage parameters of the (n-1)th round based on the nth adjustment amount to obtain the seepage parameters of the nth round; and obtaining the target seepage parameters when the seepage parameters of the nth round satisfy predetermined conditions.

[0085] In this embodiment, the objective function is constructed based on the sum of multiple squared values, where n is an integer greater than or equal to 1. The objective function can be represented by the equation shown in the second equation of equation (5) above. The (n-1)th iteration point can be expressed as... At the current iteration point The original problem is approximated by a second order, as shown in equation (6) below.

[0086] (6)

[0087] in, This represents the iteration point in the (n-1)th round. objective function The gradient; This represents the nth adjustment amount of the seepage parameter; Represents the Hessian matrix of the Lagrange function; This indicates transpose.

[0088] The constraints are linearized as shown in equation (7) below.

[0089] (7)

[0090] in, This represents the iteration point in the (n-1)th round. At that time, for the underground pipe numbered Inequality constraint functions for buried pipes; This represents the iteration point in the (n-1)th round. At that time, for the underground pipe numbered The gradient of the inequality constraint function of the buried pipe; This represents the iteration point in the (n-1)th round. At that time, for the underground pipe numbered The equation constraint function for the buried pipe; This represents the iteration point in the (n-1)th round. At that time, for the underground pipe numbered The gradient of the equality constraint function for the buried pipe. The seepage direction within the constraint. and seepage velocity The following constraints in equation (8) must be satisfied:

[0091] (8)

[0092] in, and This can be based on empirical values, varying according to the geographical location of the underground pipe network. and These can all be different; for example, when the geographical location of the underground pipe group is location 1, and These can be 0.1m per day and 10m per day, respectively. When the geographical location of the buried pipe network is location 2, which is different from location 1, and These can be 0.5m per day and 5m per day, respectively. This is merely an illustrative example and does not represent the actual invention. and The specific numerical value is limited.

[0093] Predetermined conditions can be used as criteria for judging iterative convergence, such as the change in seepage parameters obtained from two consecutive iterations, which can be measured by the norm of the vector, such as the Euclidean norm being less than a preset minimum tolerance. ,Right now When the solution is stable, the iteration converges.

[0094] The iterative solution based on sequential quadratic programming allows the temperature obtained by gradually solving the inversion problem to approximate the true temperature, thereby obtaining the optimal seepage parameters.

[0095] According to embodiments of the present invention, for example, Figure 1 The operation S150 shown, which optimizes the performance of the buried pipe group heat exchange system based on the target seepage parameters, may include: determining the target layout optimization strategy that matches the target seepage parameters according to the preset mapping relationship between the seepage parameters and the layout optimization strategy, so as to optimize the layout of the buried pipe group.

[0096] The target seepage parameters may include the target seepage direction and the target seepage velocity.

[0097] The target layout optimization strategy, which matches the target seepage direction, can be used to indicate the orientation of new underground pipe networks. The orientation can be configured such that the extension direction of the new underground pipe network in the planar layout is perpendicular to the target seepage direction. As a result, the new underground pipe network can be biased upstream, establishing a thermal isolation zone along the direction perpendicular to the target seepage direction, thus achieving clear upstream and downstream zoning management.

[0098] A target layout optimization strategy matching the target seepage velocity is used to indicate the spacing between newly added buried pipes within a new buried pipe group. The spacing can be configured as follows: When the target seepage velocity is less than a first threshold, in the direction parallel to the target seepage direction, the spacing between the newly added buried pipes is reduced by a first predetermined percentage relative to a predetermined spacing; in the direction perpendicular to the target seepage direction, the predetermined spacing is maintained. When the target seepage velocity is greater than a second threshold, in the direction parallel to the target seepage direction, the new buried pipe group is configured as a single row to avoid multiple rows. If multiple rows are necessary, the row spacing needs to be greater than 50m. In the direction perpendicular to the target seepage direction, the spacing between the newly added buried pipes is reduced by a second predetermined percentage relative to the predetermined spacing, forming a dense heat exchange wall. The first predetermined percentage is less than the second predetermined percentage. The first threshold is less than the second threshold. When the target seepage velocity is less than or equal to the second threshold and greater than or equal to the first threshold, in the direction parallel to the target seepage direction, the spacing between the newly added buried pipes is increased by a third predetermined percentage relative to the predetermined spacing, setting up a thermal insulation zone; in the direction perpendicular to the target seepage direction, the predetermined spacing is maintained. The second reservation ratio is less than the third reservation ratio.

[0099] The first threshold, second threshold, first predetermined ratio, second predetermined ratio, and third predetermined ratio can all be empirical values. For example, the first threshold can be 0.05 m / day; when the target seepage velocity is less than the first threshold, it belongs to the low-velocity zone, and the first predetermined ratio can be, for example, 10%. The second threshold can be 0.5 m / day; when the target seepage velocity is greater than the second threshold, it belongs to the high-velocity zone, and the second predetermined ratio can be 50%-70%. When the target seepage velocity is less than or equal to the second threshold, and the target seepage velocity is greater than or equal to the first threshold, it belongs to the medium-velocity zone, and the third predetermined ratio is 250%-700%.

[0100] Based on the target seepage direction of groundwater, the buried pipe network is arranged perpendicular to this direction to maximize heat exchange area and convective heat transfer effect. The spacing of the buried pipe network is differentiated according to the target seepage velocity; for example, the spacing is appropriately increased in low-velocity zones, while thermal isolation zones are set parallel to the target seepage direction or dense heat exchange walls are constructed perpendicular to the target seepage direction in medium- and high-velocity zones. This effectively breaks up heat accumulation, significantly reduces thermal interference between pipes, improves heat exchange efficiency and heat extraction / release capacity at the system level, and ensures regional thermal balance.

[0101] According to embodiments of the present invention, the performance optimization method for a buried pipe network heat exchange system may include, in addition to the above-described methods, the following: Figure 1In addition to operations S110 to S150, the following may also be included: determining the temperature deviation value for the historical cooling phase based on the first historical temperature value of the groundwater at the outlets of the multiple buried pipes and the initial equilibrium temperature value of the soil and rock collected during the historical cooling phase; determining the temperature deviation value for the historical heating phase based on the second historical temperature value of the groundwater at the outlets of the multiple buried pipes and the initial equilibrium temperature value of the soil and rock collected during the historical heating phase; obtaining the thermal imbalance index by the ratio of the absolute value of the difference between the temperature deviation value for the historical cooling phase and the temperature deviation value for the historical heating phase to the initial equilibrium temperature value of the soil and rock; and determining the current time as the predetermined time if the thermal imbalance index is determined to be greater than a predetermined threshold.

[0102] In this embodiment, the historical cooling period can be a cooling season. The historical heating period can be a heating season.

[0103] For example, the first historical temperature value of the groundwater at the outlet of each buried pipe in the buried pipe group at the end of the cooling season can be collected, thereby obtaining the first average historical temperature value of the groundwater at the outlet of the buried pipe. The difference between the first average historical temperature value and the initial equilibrium temperature value of the soil and rock is determined as the temperature deviation value of the historical cooling stage, as shown in the following formula (9):

[0104] (9)

[0105] in, This indicates the temperature deviation during the historical refrigeration period, expressed in °C. The larger the value, the more severe the underground heat accumulation. This represents the first historical groundwater temperature value at the outlet of the buried pipe in the i-th monitoring well at the end of the cooling season, in °C. The average value of the temperature sensor readings at the outlet of the buried pipe in each well can be selected within 24 hours at the end of the cooling season to avoid the influence of instantaneous fluctuations. This indicates the number of monitoring holes in the buried pipe heat exchange system. It is usually no less than 2% of the total number of boreholes. Based on geological surveys and the layout of the buried site, monitoring holes located at different positions such as the center and the edge can be selected, and the average value can be taken to represent the entire site. This represents the initial equilibrium temperature of the soil and rock, expressed in °C. Before the initial operation of the buried pipe network heat exchange system, or during the recovery period after a long period of shutdown, the undisturbed, stable ground temperature is measured using temperature sensors placed at different depths in the monitoring boreholes. Different depths typically represent the average temperature of the isothermal layer, approximately 15-20 meters underground.

[0106] The second historical temperature value of groundwater at the outlet of each buried pipe in the buried pipe group at the end of the heating season can be collected, thereby obtaining the second average historical temperature value of groundwater at the outlet of the buried pipe. The difference between the second average historical temperature value and the initial equilibrium temperature of the soil and rock is determined as the temperature deviation value of the historical heating period, as shown in the following formula (10):

[0107] (10)

[0108] in, This indicates the temperature deviation during the historical heating period, expressed in °C. The larger the value, the more severe the underground cooling. This represents the second historical groundwater temperature value at the outlet of the buried pipe of the i-th monitoring well at the end of the heating season, in °C. It can be the average value of the temperature sensor readings at the outlet of the buried pipe in each monitoring well within 24 hours at the end of the heating season.

[0109] thermal imbalance index As shown in equation (11):

[0110] (11)

[0111] The predetermined threshold can be an empirical value, for example, 0.5. When the value is greater than 0.5, the underground pipe network heat exchange system has a serious imbalance, indicating that the difference between the heat output and the heat taken out throughout the year is huge. This is the fundamental driving force for the unidirectional deterioration of the ground temperature and requires engineering intervention.

[0112] If the thermal imbalance index is less than or equal to a predetermined threshold, no action is required, or if it is less than 0.2... When the value is ≤0.5, the buried pipe heat exchange system exhibits mild to moderate imbalance. Possible causes include changes in building load and system control strategies, and its annual trend should be closely monitored. If... The increasing imbalance year by year indicates that the imbalance is worsening, and engineering intervention should be considered. When the value is ≤0.2, the underground pipe group heat exchange system is in a good or acceptable thermal balance state and no intervention is required.

[0113] This invention dynamically determines the optimization starting point by introducing a thermal imbalance coefficient, and then performs iterative inversion of seepage parameters based on this, ultimately achieving adaptive and refined optimization of the performance of the buried pipe group heat exchange system.

[0114] Based on the above explanation of the performance optimization method for buried pipe group heat exchange system under the coupling effect of groundwater seepage and geothermal heat, the following specific examples further illustrate the performance optimization method for buried pipe group heat exchange system under the coupling effect of groundwater seepage and geothermal heat.

[0115] Figure 3 A schematic diagram illustrating the effect of seepage on heat exchange of buried pipe groups according to a specific embodiment of the present invention is shown.

[0116] Specifically, in the process of implementing the embodiments of the present invention, it was found that numerical simulation methods that couple groundwater flow and heat transfer can be used to clearly reveal the core physical mechanism and key design challenges of the impact of groundwater seepage on the heat exchange of buried pipes.

[0117] For example, such as Figure 3 The image shows a temperature field shift map dominated by convection, obtained after simulating a westward-to-eastward flow direction for a buried pipe network. In the upstream region, low-temperature groundwater (dark color) continuously flows through the pipe network and is heated, forming a high-temperature downstream region (light color). This demonstrates that underground heat transfer is primarily governed by forced convection, rather than uniform heat conduction, revealing the true working environment of the buried pipe network heat exchange system. Figure 3 As shown, due to the significant temperature gradient along the seepage direction, under the current parallel water flow layout, the buried pipe in the downstream area of ​​the seepage is actually working in the soil and rock that has been heated by the upstream area of ​​the seepage. Its heat exchange efficiency will be significantly reduced, resulting in heat accumulation. This leads to the problem of thermal imbalance and overall efficiency reduction in the traditional buried pipe group heat exchange system.

[0118] Figure 4A A schematic diagram of the layout of the underground pipe group before optimization according to a specific embodiment of the present invention is shown. Figure 4B A schematic diagram of the optimized layout of the underground pipe network according to a specific embodiment of the present invention is shown. It should be noted that... Figure 4A and Figure 4B The middle circles represent boreholes, in which buried pipes are laid.

[0119] Based on this, the present invention addresses, for example Figure 4A The buried pipe network heat exchange system before optimization was tested. When the heat imbalance index reached 36%, continuous monitoring revealed a continuously increasing trend, such as a -2°C temperature deviation at the end of two consecutive heating seasons, and an average outlet water temperature 2°C higher in the eastern boreholes than in the western boreholes, with this trend expanding eastward over time. Therefore, based on randomly determined seepage angles and velocities, and the aforementioned dimensionless temperature expression, the goal is to minimize the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution. The seepage angles and velocities are iteratively updated, resulting in a target seepage angle of θ = 90° (the angle formed by the northward and eastward directions) and a target seepage velocity of 0.1 m / day.

[0120] Regarding the characteristic of seepage with θ=90°, i.e., due east direction, it can be done as follows: Figure 4BAs shown, a reinforced heat exchange zone was established in the vertical seepage direction, i.e., north-south. By adding a group of vertically arranged boreholes at the eastern boundary of the site, a heat exchange wall was formed, physically blocking the continuous migration of heat along the seepage direction. This asymmetrical layout, dense in the west and sparse in the east, fully utilizes the advantage of cold water in the upstream region (west side) of the seepage, while setting up a sparse thermal buffer zone in the downstream region (east side), effectively alleviating the heat accumulation phenomenon in the downstream region and fundamentally preventing the occurrence of thermal short circuits.

[0121] Because groundwater seepage is highly dynamic, the characteristics of water flow and temperature variations in different regions can affect geothermal energy harvesting efficiency. Therefore, this invention, through dynamic inversion of the groundwater seepage process, can more accurately capture changes in groundwater flow and temperature distribution, optimizing the efficiency of geothermal energy harvesting and transmission. In traditional buried pipe network heat exchange systems, groundwater seepage is often not fully considered. However, through inversion technology, the heat exchange process can be dynamically adjusted, making the coupling of groundwater and geothermal energy more efficient, optimizing heat exchange effects, and ensuring efficient operation of the heat exchange system under various environmental conditions. Furthermore, by dynamically inverting groundwater seepage, the operating status of the buried pipes can be adjusted in real time, preventing heat loss during the heat exchange process and improving the long-term stability and reliability of the heat exchange system. In addition, accurate groundwater seepage inversion allows for more efficient design of the layout and operation mode of the buried pipe network heat exchange system. This is beneficial for improving heat recovery efficiency, reducing system energy consumption, and lowering energy consumption and operating costs. With improved energy utilization efficiency, the system becomes more environmentally friendly, meeting the modern society's demands for energy conservation and environmental protection. Furthermore, the design and operation of the heat exchange system can be adjusted based on real-time feedback under different regional conditions, groundwater flow rates, and temperatures, thereby improving the system's versatility and adaptability.

[0122] Figure 5 A structural block diagram of a performance optimization device for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat according to an embodiment of the present invention is shown.

[0123] like Figure 5 As shown, the performance optimization device 500 for the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat includes a first construction module 510, a second construction module 520, a third construction module 530, an iteration module 540, and an optimization module 550.

[0124] The buried pipes in the underground pipe group are each laid in the boreholes of the rock and soil layer so that multiple buried pipes can exchange heat with the rock and soil layer.

[0125] The first construction module 510 is used to construct a first dimensionless number to characterize the relative intensity of the convection effect and the thermal conductivity effect of the soil and rock caused by groundwater seepage, based on the thermal properties of the soil and rock and the seepage parameters of the groundwater.

[0126] The second construction module 520 is used to construct a second dimensionless number to characterize the time scale of thermal diffusion in soil and rock based on the thermal physical properties of the soil and rock, the geometric parameters of the buried pipe group, and the time parameters.

[0127] The third construction module 530 is used to construct an integral form of dimensionless temperature expression based on the first dimensionless number and the second dimensionless number, as well as the seepage parameters of groundwater. The range of the integral variable in the integral form is determined based on the first dimensionless number and the second dimensionless number. The dimensionless temperature expression is used to determine the dimensionless temperature distribution of each buried pipe at different times and with different seepage parameters.

[0128] The iteration module 540 is used to iteratively update the seepage parameters based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, with the goal of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain the target seepage parameters.

[0129] The optimization module 550 is used to optimize the performance of the buried pipe group heat exchange system based on the target seepage parameters.

[0130] According to embodiments of the present invention, any multiple modules among the first building module 510, the second building module 520, the third building module 530, the iteration module 540, and the optimization module 550 can be merged into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of the present invention, at least one of the first building module 510, the second building module 520, the third building module 530, the iteration module 540, and the optimization module 550 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the first building module 510, the second building module 520, the third building module 530, the iteration module 540, and the optimization module 550 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0131] It should be noted that the performance optimization device part of the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy in the embodiments of the present invention corresponds to the performance optimization method part of the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy in the embodiments of the present invention. For a detailed description of the performance optimization device part of the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy, please refer to the performance optimization method part of the buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy, which will not be repeated here.

[0132] Figure 6 A block diagram of an electronic device according to an embodiment of the present invention is shown, which is suitable for implementing a performance optimization method for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal energy.

[0133] like Figure 6 As shown, an electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory ROM 602 or a program loaded from a storage portion 608 into a random access memory RAM 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0134] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 executes various operations of the method flow according to embodiments of the present invention by executing programs in ROM 602 and / or RAM 603. It should be noted that programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in one or more memories.

[0135] According to an embodiment of the present invention, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to a bus 604. The electronic device 600 may also include one or more of the following components connected to the input / output (I / O) interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.

[0136] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0137] According to embodiments of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of the present invention, a computer-readable storage medium may include ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603 described above.

[0138] Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of the present invention.

[0139] When the computer program is executed by the processor 601, it performs the functions defined in the system / apparatus of this invention. According to embodiments of the invention, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0140] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and / or installed from the removable medium 611. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0141] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, it performs the functions defined in the system of this embodiment of the invention. According to embodiments of the invention, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0142] According to embodiments of the present invention, program code for executing the computer programs provided in the embodiments of the present invention can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0143] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0144] Those skilled in the art will understand that the features described in the various embodiments of the present invention can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention can be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or combinations fall within the scope of the present invention.

[0145] The embodiments of the present invention have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of the invention. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of the invention, and all such substitutions and modifications should fall within the scope of the invention.

Claims

1. A performance optimization method for a buried pipe network heat exchange system based on the coupling effect of groundwater seepage and geothermal energy, characterized in that, The buried pipes in the buried pipe group are each laid in boreholes in the soil and rock layer, so that the multiple buried pipes can exchange heat with the soil and rock layer; the performance optimization method includes: Based on the thermal properties of the soil and groundwater, and the seepage parameters of the groundwater, a first dimensionless number is constructed to characterize the relative intensity of the convection effect and the thermal conductivity effect of the soil caused by the seepage of the groundwater. Based on the thermal properties of the soil and groundwater, as well as the time parameters, a second dimensionless number is constructed to characterize the time scale of heat transfer affected by groundwater seepage and thermal diffusion in the soil and rock. Based on the first dimensionless number and the second dimensionless number, as well as the seepage parameters of the groundwater, an integral form of dimensionless temperature expression is constructed, wherein the range of the integral variable in the integral form is determined based on the first dimensionless number and the second dimensionless number, and the dimensionless temperature expression is used to determine the dimensionless temperature distribution of each of the buried pipes at different times and with different seepage parameters. Based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, the seepage parameters are iteratively updated with the goal of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain the target seepage parameters. Based on the target seepage parameters, the performance of the buried pipe group heat exchange system is optimized.

2. The performance optimization method according to claim 1, characterized in that, The seepage parameters include the seepage direction and the seepage velocity; The integral form of the dimensionless temperature expression, based on the first dimensionless number, the second dimensionless number, and the groundwater seepage parameters, includes: Based on the enhancing or attenuating effect of the seepage direction of the groundwater on heat transport, the first dimensionless number and the angular variable characterizing the seepage direction are combined to construct a heat diffusion term in the form of an exponential function. Based on the radial diffusion attenuation of heat in the soil and rock due to thermal conduction, and the angle-dependent convective dissipation due to groundwater seepage, the zero-order Bessel function is combined with the exponential decay factor that depends on the integral variable to construct the exponential decay term in the integral kernel. The dimensionless temperature expression is obtained by multiplying the heat diffusion term and the exponential decay term.

3. The performance optimization method according to claim 2, characterized in that, The performance optimization method also includes: The dimensionless temperature expression is integrated and averaged within a semi-circular profile perpendicular to the seepage direction of the groundwater, and through mathematical transformation, an average dimensionless temperature expression including a first-order Bessel function and an exponential decay factor is obtained. The average dimensionless temperature expression is used to determine the dimensionless temperature in the dimensionless temperature distribution considering the borehole diameter.

4. The performance optimization method according to claim 3, characterized in that, Based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, the seepage parameters are iteratively updated with the objective of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain the target seepage parameters, including: Based on the initial seepage parameters, the dimensionless temperature of the groundwater in each buried pipe is calculated using the average dimensionless temperature expression. Using the serial numbers of the buried pipes in the buried pipe group as the matrix rows and the time series as the matrix columns, a temperature matrix is ​​constructed based on the dimensionless temperature of the groundwater in each buried pipe. Based on the temperature matrix and the real temperature matrix, the square of the difference between the dimensionless temperature and the corresponding real temperature is calculated point by point. The real temperature matrix is ​​constructed based on the real temperature of the groundwater in each of the buried pipes. Based on the optimization algorithm, the seepage parameters are iteratively updated with the goal of minimizing the sum of multiple squared values ​​to obtain the target seepage parameters.

5. The performance optimization method according to claim 4, characterized in that, The optimization algorithm includes a sequential quadratic programming algorithm; The optimization algorithm, aiming to minimize the sum of multiple squared values, iteratively updates the seepage parameters to obtain the target seepage parameters, including: Using the seepage parameters of the (n-1)th round as the iteration point of the (n-1)th round, a second-order Taylor expansion is performed on the objective function, and the constraints on the seepage parameters are linearized to construct a quadratic programming subproblem, wherein the objective function is constructed based on the sum of multiple squared values; Based on the sum of multiple squared values ​​in the (n-1)th round, the quadratic programming subproblem is solved to obtain the nth adjustment of the seepage parameter; The seepage parameters for the (n-1)th round are updated based on the nth adjustment amount to obtain the seepage parameters for the nth round. The target seepage parameter is obtained when the seepage parameters of the nth round meet the predetermined conditions, where n is an integer greater than or equal to 1.

6. The performance optimization method according to claim 1, characterized in that, The performance optimization of the buried pipe group heat exchange system based on the target seepage parameters includes: Based on the preset mapping relationship between seepage parameters and layout optimization strategies, a target layout optimization strategy matching the target seepage parameters is determined so as to optimize the layout of the buried pipe group. The target seepage parameters include the target seepage direction and the target seepage velocity; A target layout optimization strategy matching the target seepage direction is used to indicate the layout orientation of the new underground pipe group, wherein the layout orientation is configured such that the extension direction of the new underground pipe group in the planar layout is perpendicular to the target seepage direction. A target layout optimization strategy, matched to the target seepage velocity, is used to indicate the spacing between newly added underground pipes within the newly added underground pipe group. The spacing is configured such that, when the target seepage velocity is less than a first threshold, the spacing between the newly added buried pipes is reduced by a first predetermined proportion relative to a predetermined spacing in a direction parallel to the target seepage direction, and the predetermined spacing is maintained in a direction perpendicular to the target seepage direction. When the target seepage velocity is greater than the second threshold, the newly added underground pipe group is configured as a single row in the direction parallel to the target seepage direction, and the spacing between the newly added underground pipes is reduced by a second predetermined proportion relative to the predetermined spacing in the direction perpendicular to the target seepage direction, wherein the first predetermined proportion is less than the second predetermined proportion, and the first threshold is less than the second threshold. When the target seepage velocity is less than or equal to the second threshold and the target seepage velocity is greater than or equal to the first threshold, the spacing between the newly added buried pipes is increased by a third predetermined proportion relative to the predetermined spacing in a direction parallel to the target seepage direction, and the predetermined spacing is maintained in a direction perpendicular to the target seepage direction, wherein the second predetermined proportion is less than the third predetermined proportion.

7. The performance optimization method according to claim 1, characterized in that, The performance optimization method also includes: Based on the first historical temperature value of the groundwater and the initial equilibrium temperature value of the soil and rock at the outlets of the multiple buried pipes collected during the historical cooling phase, the temperature deviation value of the historical cooling phase is determined. The temperature deviation value of the historical heating period is determined based on the second historical temperature value of the groundwater at the outlet of each of the multiple buried pipes collected during the historical heating period and the initial equilibrium temperature value of the soil and rock. The thermal imbalance index is obtained by comparing the absolute value of the difference between the temperature deviation values ​​during the historical cooling phase and the temperature deviation values ​​during the historical heating phase with the initial equilibrium temperature value of the soil and rock. If the thermal imbalance index is determined to be greater than a predetermined threshold, the current time is determined as the predetermined time.

8. A performance optimization device for a buried pipe group heat exchange system based on the coupling effect of groundwater seepage and geothermal heat, characterized in that, The buried pipes in the buried pipe group are each laid in the borehole of the rock and soil layer so that the multiple buried pipes can exchange heat with the rock and soil in the rock and soil layer. The performance optimization device includes: The first construction module is used to construct a first dimensionless number to characterize the relative intensity of the convection effect and the thermal conductivity effect of the soil and rock based on the thermal properties of the soil and rock and the seepage parameters of the groundwater. The second construction module is used to construct a second dimensionless number to characterize the heat transfer time scale affected by groundwater seepage and thermal diffusion of the soil and groundwater, based on the thermal physical properties of the soil and groundwater and the time parameters. The third construction module is used to construct an integral form of a dimensionless temperature expression based on the first dimensionless number and the second dimensionless number, as well as the seepage parameters of the groundwater. The range of the integral variable in the integral form is determined based on the first dimensionless number and the second dimensionless number. The dimensionless temperature expression is used to determine the dimensionless temperature distribution of each buried pipe at different times and with different seepage parameters. An iterative module is used to iteratively update the seepage parameters based on the initial seepage parameters and the dimensionless temperature expression, starting from a predetermined time, with the goal of minimizing the difference between the dimensionless temperature and the corresponding true temperature in the dimensionless temperature distribution, to obtain the target seepage parameters. The optimization module is used to optimize the performance of the buried pipe group heat exchange system based on the target seepage parameters.

9. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the performance optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, characterized in that, When the instruction is executed by the processor, it causes the processor to implement the performance optimization method according to any one of claims 1 to 7.

Images