Simulation method and system of solar ground source heat pump system

Abstract

The invention provides a simulation method and system for a solar ground source heat pump system, and relates to the technical field of solar ground source heat pump system simulation, and the method comprises the steps: firstly obtaining a soil initial temperature field, and calculating the soil temperature cumulative variation in a future time period through a one-dimensional radial simplified heat transfer model in combination with a predicted load; defining as a soil thermal imbalance risk index; according to comparison between the index and a preset threshold value, selecting an efficiency priority strategy with solar energy immediate utilization as priority or a heat balance priority strategy with soil temperature field adjustment as priority; linkage rules of all subsystems are determined according to a selected strategy, the net heat exchange amount of a geographical pipe heat exchanger and the net heat storage / release amount of a heat storage device are calculated by jointly solving a dynamic model, and then the soil temperature field and the state of the heat storage device are updated; and the simulation step length is iteratively propelled until the period is ended, and finally, the system energy efficiency coefficient, the soil heat balance degree and the time-varying curve of the key parameters are output.

Description

Technical Field

[0001] This invention relates to the field of solar ground source heat pump system simulation technology, specifically to a simulation method and system for a solar ground source heat pump system. Background Technology

[0002] As a highly efficient and renewable energy utilization method, solar ground source heat pump systems can significantly improve overall system energy efficiency and reduce dependence on traditional fossil fuels by coupling solar thermal collection and ground source heat pump technologies, resulting in good energy-saving and environmental benefits. However, solar energy is characterized by significant intermittency and fluctuation, and the soil thermal balance of ground source heat pump systems is also affected by long-term operating loads. The coupled system operation process is complex and exhibits significant dynamic characteristics. In practical engineering design and operation optimization, accurately simulating the system's dynamic response under varying weather conditions and load demands, and rationally coordinating the relationship between immediate solar energy utilization, thermal storage device scheduling, and soil thermal balance, becomes a key issue in improving system performance and operational stability.

[0003] In the prior art, the simulation method, apparatus, equipment, and medium for a solar ground source heat pump system disclosed in CN119416546A optimizes the initial heat extraction from shallow soil sources by constructing an overall model that includes a ground source heat pump sub-model, a solar collector energy conservation sub-model, a dynamic heat balance sub-model, and a heat exchange rate sub-model to obtain the target heat extraction. However, this scheme focuses on static or quasi-static load matching and heat optimization within a fixed preset time period, without fully considering the real-time dynamic decision-making and multi-mode switching mechanisms during system operation. Specifically, it lacks proactive prediction and risk assessment of future changes in the soil temperature field, and does not dynamically adjust the system operation strategy based on real-time prediction results. Therefore, it has certain limitations in real-time control of short-term load fluctuations, sudden changes in meteorological conditions, and the effects of soil heat accumulation, making it difficult to achieve the dynamic optimization goal of balancing efficient energy supply and soil heat balance in long-term system operation.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a simulation method and system for a solar ground source heat pump system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A simulation method for a solar ground source heat pump system, comprising the following steps: Step 1: Obtain the initial soil temperature field data and set the soil temperature field at the current simulation time accordingly. Based on the soil temperature field at the current simulation time and the predicted average load in the future target period, use a one-dimensional radial simplified heat transfer model to predict the cumulative change in soil temperature from the current simulation time to the end of the future target period, and define it as the soil thermal imbalance risk index. Step 2: Compare the soil thermal imbalance risk index with the preset risk threshold, and select a system operation strategy to guide the next simulation step based on the comparison results. The operation strategy includes an efficiency priority strategy that prioritizes the immediate utilization of solar energy, and a thermal balance priority strategy that prioritizes the active adjustment of the soil temperature field. Step 3: Based on the selected system operation strategy, determine the linkage rules of each subsystem in the next simulation time step, and then drive and jointly solve the dynamic mathematical model of each subsystem to calculate the net heat exchange of the geotube heat exchanger and the net heat storage / release of the heat storage device in the next simulation step. Step 4: Based on the net heat exchange of the geothermal heat exchanger, update the soil temperature field at the start of the next simulation time step. At the same time, based on the net heat storage / release of the heat storage device, update the temperature and remaining heat storage capacity of the heat storage device at the start of the next simulation time step. Step 5: Advance the simulation time by one step and repeat steps 1 to 4 until the set simulation cycle is completed. Based on the cumulative data of all simulation steps, generate curves of the system's comprehensive energy efficiency coefficient, soil thermal balance, and key parameters changing over time. The key parameters include soil temperature, heat storage device temperature, and system operation strategy.

[0007] Furthermore, depth-radial discrete grid temperature distribution data based on the geographic borehole center is obtained as the initial soil temperature field. The initial soil temperature field is initialized by assigning values ​​to the corresponding grid nodes to initialize the temperature values ​​of each calculation unit in the soil heat transfer model, thereby setting the soil temperature field at the current simulation moment. The method for determining the predicted average load during the future target period is as follows: acquiring historical meteorological data for the same season as the future target period and corresponding historical hourly building load data, wherein the meteorological data includes daily average outdoor temperature and daily average solar radiation intensity; secondly, acquiring short-term meteorological forecast data for the future target period, including predicted daily average outdoor temperature and predicted daily average solar radiation intensity. The linear meteorological correction factor method is used to correct historical hourly building load data. The formula used is as follows: In the formula, This represents the corrected load at time t within the future target time period, where t is the time variable of the future target time period; This represents the historical building load at time t within the future target time period; This represents the predicted daily average outdoor temperature at time t within the target future time period. This represents the historical daily average outdoor temperature at time t within the future target time period; This represents the predicted daily average solar radiation intensity at time t within the target future time period. This represents the historical daily average solar radiation intensity at time t within the future target time period; This is the temperature influence coefficient. The radiation impact coefficient must be met during the heating season. , During the cooling season, it meets the requirements. , .

[0008] The arithmetic mean of the corrected load at each time point within the future target period is taken, and the calculation result is calibrated as the predicted average load within the future target period. After setting the current soil temperature field and obtaining the predicted average load, the predicted average load is input as a constant boundary heat flux density into a one-dimensional radial simplified heat transfer model. The soil temperature field at the current simulation moment is used as the initial temperature distribution. The transient heat conduction control equation of the model is solved numerically to calculate the cumulative temperature change of the soil at the geographical pipe wall from the current simulation moment to the end of the future target time period. This change is defined as the soil thermal imbalance risk index.

[0009] Furthermore, the risk threshold is a first threshold: When the soil thermal imbalance risk index is less than the first threshold, the soil thermal state is determined to be within a safe range, and the efficiency-first strategy is selected. When the soil thermal imbalance risk index is greater than or equal to the first threshold, it is determined that there is a risk of soil thermal imbalance, and the thermal balance priority strategy is selected.

[0010] Furthermore, based on the selected system operation strategy, the linkage rules of each subsystem within the next simulation time step are determined. The specific logic is as follows: if the efficiency priority strategy is selected, the linkage rules are set as follows: all the heat produced by the solar thermal collector subsystem is given priority to be directly supplied to the building load. When there is excess heat, it is stored in the heat storage device. Only when neither of them can meet the load demand will the heat pump unit be started to absorb heat from the geothermal heat exchanger or discharge heat to it. If the heat balance priority strategy is selected, the linkage rule is set as follows: with the goal of actively regulating the soil temperature field, the heat storage device and the solar collector subsystem are linked first to jointly provide or extract heat to the geothermal heat exchanger. Only when the soil temperature regulation target is achieved and there is remaining heating or cooling capacity will the heat be allocated to the building load. Based on the established linkage rules, at a single simulation time step Within the simulation, mathematical models reflecting the transient thermodynamic processes of each subsystem are invoked and solved simultaneously. These mathematical models include a variable operating condition model reflecting the coefficient of performance of the heat pump unit as a function of evaporation and condensation temperatures, a temperature change model of the heat storage device based on energy conservation, and a thermal resistance-capacity model describing the unsteady heat exchange between the geotextile and the surrounding soil. By coupling these models according to the system topology and control logic, and simultaneously solving their control equations within each simulation step, the temperature and flow distribution of the fluid in the geotextile, the working fluid in the heat storage device, and each connecting pipe are calculated synchronously and iteratively. This ultimately yields the net heat exchange of the geotextile heat exchanger, the net heat storage / release of the heat storage device, and the power consumption of the heat pump unit within that simulation step.

[0011] Furthermore, the expression for the variable operating condition model is as follows: In the formula, The coefficient of performance (COP) of a heat pump. The coefficient of performance (COP) of the heat pump; and These are the heat pump performance functions under heating and cooling conditions, respectively, which are obtained by fitting performance data tables provided by the equipment manufacturer. , These are the average heat exchange fluid temperatures of the evaporator and condenser, respectively, which are determined in the simultaneous solution of the system. For the power consumption of the heat pump unit; , These are the condenser's heating capacity and the evaporator's heat absorption, respectively. The expression for the temperature change model of the heat storage device is as follows: In the formula, The net heat storage / release of the heat storage device; Specific heat capacity of the heat storage medium; The average temperature of the medium inside the heat storage device. The ambient temperature; , These represent the fluid from the first... The mass flow rate and temperature of the heat storage device when it flows into the inlet. This serves as an index for the inlet within the thermal storage device. The number of inlets within the thermal storage device; and These represent the fluid from the first... The mass flow rate and temperature of the heat storage device when it exits the outlet. This is an index for the outlet within the thermal storage device. This refers to the number of outlets within the heat storage device. The heat loss coefficient of the heat storage device; The heat dissipation surface area of ​​the heat storage device; The expression for the thermal resistance-capacity model is as follows: In the formula, The instantaneous heat exchange between the geothermal tube heat exchanger and the soil is positive for heat absorption and negative for heat release. The average temperature of the circulating fluid within the geographical pipe; This indicates the soil temperature at the surface of the geotextile tube; This represents the total thermal resistance from the fluid to the soil; Will Defined as the net heat exchange capacity of a geotextile heat exchanger.

[0012] Furthermore, the calculated net heat transfer capacity of the geodesic tube heat exchanger is... As a term representing the heat source away from the ground, it is input into a three-dimensional numerical calculation model centered on the geodetic borehole and considering unsteady heat conduction in the radial and depth directions of the soil. In this three-dimensional numerical calculation model, the soil temperature field at the current simulation moment is used as the initial condition, and the far-field soil temperature is used as the constant boundary condition. By solving the transient heat conduction control equation, the calculation is performed over a single simulation time step under the influence of the heat source away from the ground. The temperature distribution across the entire computational domain was then analyzed, and the radial distance from the borehole wall was extracted. The soil temperature distribution is used as the updated soil temperature field for the start of the next simulation step; whereby... The preset radius of influence; The calculated net heat storage / release heat of the heat storage device As input, the total heat capacity of the thermal storage device is first considered. Calculate the resulting average temperature change Then, based on the temperature of the heat storage device at the current simulation moment... Calculate the temperature of the heat storage device at the start of the next simulation time step. The formula it is based on is as follows: Simultaneously, based on the current remaining heat storage capacity of the heat storage device, and combined with the net heat storage / release of the heat storage device... The updated remaining heat storage capacity is obtained using the following formula: in, This represents the current remaining heat storage capacity of the heat storage device.

[0013] Furthermore, after the simulation cycle is completed, the power consumption of the heat pump unit calculated in each simulation time step and the actual cooling / heating supplied to the building load in that simulation time step are extracted and accumulated. ;in, The value is obtained from the results of solving the mathematical model according to the linkage rules determined in step 3. Its physical meaning is the sum of the heat supplied to the load directly by the solar collector subsystem and the heat supplied to the load by the heat pump unit through the condenser. Based on the cumulative data from all simulation steps, the overall system energy efficiency coefficient and soil thermal balance are generated, using the following formulas: In the formula, The overall energy efficiency coefficient of the system; Indicates the first The power consumption of a heat pump unit with a simulated time step. For the simulation time step index, This represents the total number of simulation time steps; Indicates the first The actual cooling / heating supplied to the building load within each simulation time step; In the formula, Indicates the soil's heat balance; Indicates the first Net heat transfer of a geotube heat exchanger with a simulation time step; Meanwhile, the soil temperature, heat storage device temperature, and system operation strategy corresponding to each simulation step within the entire simulation cycle are arranged in chronological order, and curves of the soil temperature, heat storage device temperature, and system operation strategy changing over time are generated respectively.

[0014] The present invention also provides a simulation system for a solar ground source heat pump system, wherein the simulation system is used to execute the above-described simulation method for a solar ground source heat pump system, comprising: The initialization and risk prediction module is used to acquire the initial soil temperature field data and set the soil temperature field at the current simulation time. Based on the soil temperature field at the current simulation time and the predicted average load in the future target period, a one-dimensional radial simplified heat transfer model is used to predict the cumulative change in soil temperature from the current simulation time to the end of the future target period, and it is defined as the soil thermal imbalance risk index. The strategy selection module is used to compare the soil thermal imbalance risk index with a preset risk threshold, and select a system operation strategy to guide the next simulation step based on the comparison result. The operation strategy includes an efficiency priority strategy that prioritizes the immediate utilization of solar energy, and a thermal balance priority strategy that prioritizes the active adjustment of the soil temperature field. The simulation calculation module is used to determine the linkage rules of each subsystem in the next simulation time step according to the selected system operation strategy, and then drive and jointly solve the dynamic mathematical model of each subsystem to calculate the net heat exchange of the geotube heat exchanger and the net heat storage / release of the heat storage device in the next simulation step. The state iteration update module is used to update the soil temperature field at the start of the next simulation time step based on the net heat exchange of the geographic pipe heat exchanger, and at the same time update the temperature and remaining heat storage capacity of the heat storage device at the start of the next simulation time step based on the net heat storage / release of the heat storage device. The cyclic output evaluation module is used to advance the simulation time by one step and repeat steps 1 to 4 until the set simulation cycle is completed. Based on the cumulative data of all simulation steps, it generates curves of the system's comprehensive energy efficiency coefficient, soil thermal balance, and key parameters changing over time. The key parameters include soil temperature, heat storage device temperature, and system operation strategy.

[0015] Compared with the prior art, the beneficial effects of the present invention are: First, this invention establishes a soil thermal imbalance risk index to assess the trend of soil temperature changes over a future period. When the index is below a set threshold, the system implements an efficiency-first strategy, prioritizing solar energy to meet building loads and storing excess heat in a thermal storage device to maximize energy utilization efficiency. If the index exceeds the threshold, the system automatically switches to a thermal balance-first strategy, actively utilizing the thermal storage device and solar energy resources to supplement or absorb heat from the soil, effectively preventing soil temperature imbalance and ensuring long-term stable operation of the system.

[0016] Secondly, this invention constructs a coupled simulation framework that integrates the heat pump variable operating condition performance model, the heat storage device energy balance model, and the geographic pipe unsteady-state heat exchange model. In each simulation step, the system dynamically determines the linkage mode of each subsystem according to the currently selected strategy and solves the control equations of each model simultaneously, thereby calculating the net heat exchange of the geographic pipe and the heat storage device's heat storage and release. This can more realistically reflect the dynamic response characteristics of the system under variable operating conditions.

[0017] In addition, after the simulation, the system automatically generates the comprehensive energy efficiency coefficient and soil thermal balance, and simultaneously plots the curves of soil temperature, heat storage device temperature and operating mode changes over time. This not only provides a quantitative evaluation basis for system performance, but also intuitively displays the evolution of operating status under different strategies, providing reliable data support and decision-making reference for design optimization, operation control and fault analysis. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2A vertical graph showing the net inflow of total heat flow, the net outflow of total heat flow, the temperature difference due to heat loss, and the net stored / released heat of the heat storage device; Figure 3 This is a schematic diagram of the overall system modules of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0020] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example: Please see Figure 1-2 The present invention provides a technical solution: A simulation method for a solar ground source heat pump system, comprising the following steps: Step 1: Obtain the initial soil temperature field data and set the soil temperature field at the current simulation time accordingly. Based on the soil temperature field at the current simulation time and the predicted average load in the future target period, use a one-dimensional radial simplified heat transfer model to predict the cumulative change in soil temperature from the current simulation time to the end of the future target period, and define it as the soil thermal imbalance risk index. In this embodiment, the temperature distribution data of the depth-radial discrete grid based on the geographical borehole center is obtained as the initial soil temperature field. The initial soil temperature field is initialized by assigning values ​​to the corresponding grid nodes to initialize the temperature values ​​of each calculation unit in the soil heat transfer model, thereby setting the soil temperature field at the current simulation time. The specific process for obtaining depth-radial discrete grid temperature distribution data based on the center of the buried borehole is as follows: Before the simulation begins, the initial soil temperature field data is obtained by measuring the temperature sensor array deployed on-site. Specifically, after the borehole construction is completed and before the system is officially put into operation, a distributed fiber optic temperature measurement system is deployed at fixed intervals along the borehole depth direction. At the same time, temperature measuring points are buried at different radial positions along the radial direction of each depth plane with the borehole center as the origin. After the system is left to stand for no less than 48 hours to allow the soil temperature field to return to its natural state, the soil temperature at each depth and radial position is collected synchronously to form a depth-radial discrete temperature dataset based on the borehole center. Finally, the measured discrete temperature data is mapped to each node of the pre-divided depth-radial structured computational grid through spatial interpolation to generate complete depth-radial discrete grid temperature distribution data, which serves as the initial soil temperature field.

[0022] The method for determining the predicted average load during the future target period is as follows: acquiring historical meteorological data for the same season as the future target period and corresponding historical hourly building load data, wherein the meteorological data includes daily average outdoor temperature and daily average solar radiation intensity; secondly, acquiring short-term meteorological forecast data for the future target period, including predicted daily average outdoor temperature and predicted daily average solar radiation intensity. The linear meteorological correction factor method is used to correct historical hourly building load data. The formula used is as follows: In the formula, This represents the corrected load at time t within the future target time period, where t is the time variable of the future target time period; This represents the historical building load at time t within the future target time period; This represents the predicted daily average outdoor temperature at time t within the target future time period. This represents the historical daily average outdoor temperature at time t within the future target time period; This represents the predicted daily average solar radiation intensity at time t within the target future time period. This represents the historical daily average solar radiation intensity at time t within the future target time period; This is the temperature influence coefficient. The radiation impact coefficient must be met during the heating season. , During the cooling season, it meets the requirements. , .

[0023] Set temperature influence coefficient during heating season This is because, under heating conditions, the lower the outdoor temperature, the greater the building's heat load demand. Therefore, when future temperatures are lower than historical averages for the same period, the corrective load should be increased. Taking a negative value can produce a positive correction for the temperature difference term; radiation influence coefficient This is because increased solar radiation reduces the building's heat demand; therefore, when future radiation levels are higher than historical values, the load should be reduced. Taking a positive value can result in a negative correction for the radiation difference term; temperature influence coefficient during the cooling season. This is because, under cooling conditions, the higher the outdoor temperature, the greater the building's cooling load demand. When future temperatures exceed historical temperatures, the corrective load needs to be increased. Taking a positive value will result in a positive correction for the temperature difference term; radiation influence coefficient This is because increased solar radiation increases the building's cooling load, and when future radiation levels are higher than historical values, the load should increase. Taking a negative value can produce a positive correction for the radiation difference term.

[0024] For this formula, the dependent variable Its value directly reflects the heating or cooling load level required by the building at time t within a future target period under specific meteorological conditions: if A larger value means that, under the current predicted weather conditions, the building load demand is high, and the system needs to provide more cooling / heating; conversely, if... ; The calculation of corrected loads using data from future target periods and historical data from the same period is based on the strong correlation between building loads and meteorological parameters. Building loads are mainly affected by outdoor temperature and solar radiation intensity: during the heating season, the lower the outdoor temperature and the weaker the solar radiation, the greater the building heat load; during the cooling season, the higher the outdoor temperature and the stronger the solar radiation, the greater the building cooling load. Historical load data from the same period reflects the load baseline under specific meteorological conditions, while future weather forecast data provides the driving factors for load changes. By comparing the differences between future and historical meteorological conditions, historical loads can be dynamically corrected, thereby more accurately predicting future loads.

[0025] The arithmetic mean of the corrected load at each time point within the future target period is taken, and the calculation result is calibrated as the predicted average load within the future target period. After setting the current soil temperature field and obtaining the predicted average load, the predicted average load is input as a constant boundary heat flux density into a one-dimensional radial simplified heat transfer model, i.e., the heat flux density acting uniformly on the wall of the buried pipe. Replace the actual time-varying load, where The predicted average load for the target future time period is used to simplify the heat transfer model into a single-hole radial axisymmetric problem. Using the current depth-radial mesh temperature distribution as the initial condition, the finite difference method is employed to solve the unsteady heat conduction equations in cylindrical coordinates, including heat source terms. in, The soil thermal diffusivity has a range of values. - ; within the drilling radius Apply a third type of boundary condition at the location: A constant far-field temperature is taken at radial infinity; through time-progressing numerical calculations, the change history of soil temperature at the buried pipe wall from the current moment to the end of the future target time period is obtained, and the cumulative temperature change is finally defined as the soil thermal imbalance risk index. The soil thermal imbalance risk index is used to characterize the trend and degree of soil temperature deviation from the initial state under the continuous action of the predicted load. For soil temperature, Radial coordinates, The thermal conductivity of the soil is determined by soil thermophysical property tests.

[0026] Step 2: Compare the soil thermal imbalance risk index with the preset risk threshold, and select a system operation strategy to guide the next simulation step based on the comparison results. The operation strategy includes an efficiency priority strategy that prioritizes the immediate utilization of solar energy, and a thermal balance priority strategy that prioritizes the active adjustment of the soil temperature field. In this embodiment, the simulation step size is set to 1 hour; The risk threshold is the first threshold: When the soil thermal imbalance risk index is less than the first threshold, it indicates that the cumulative change in soil temperature in the future period is within an acceptable range and the soil thermal state is in a safe zone. At this time, the efficiency-first strategy is selected to make full use of solar energy and reduce the energy consumption of heat pump operation as the system operation goal. When the soil thermal imbalance risk index is greater than or equal to the first threshold, it indicates that the soil temperature will deviate significantly in the future period and there is a risk of thermal imbalance. In order to ensure the long-term thermal stability of the soil, the system switches to the thermal balance priority strategy and prioritizes the use of heat storage devices and solar energy resources to actively regulate the soil temperature in order to prevent the ground temperature from deteriorating.

[0027] The method for determining the first threshold is as follows: based on the design requirements for long-term stable operation of the system, the maximum cumulative change in the soil temperature field within a single operating cycle is taken as the basis, and the heat exchange characteristics of the geothermal heat exchanger and the soil thermal properties are combined to determine it through numerical simulation or engineering experience.

[0028] This threshold judgment and strategy switching mechanism enables dynamic optimization of system operation strategy while ensuring soil thermal balance, thus achieving the dual goals of efficiency and stability.

[0029] Step 3: Based on the selected system operation strategy, determine the linkage rules of each subsystem in the next simulation time step, and then drive and jointly solve the dynamic mathematical model of each subsystem to calculate the net heat exchange of the geotube heat exchanger and the net heat storage / release of the heat storage device in the next simulation step. In this embodiment, based on the selected system operation strategy, the linkage rules of each subsystem in the next simulation time step are determined. The specific logic is as follows: if the efficiency priority strategy is selected, the linkage rules are set as follows: all the heat produced by the solar thermal collector subsystem is given priority to be directly supplied to the building load. When there is excess heat, it is stored in the heat storage device. Only when neither of them can meet the load demand will the heat pump unit be started to absorb heat from the geothermal heat exchanger or discharge heat to it. If the heat balance priority strategy is selected, the linkage rule is set as follows: with the goal of actively regulating the soil temperature field, the heat storage device and the solar collector subsystem are linked first to jointly provide or extract heat to the geothermal heat exchanger. Only when the soil temperature regulation target is achieved and there is remaining heating or cooling capacity will the heat be allocated to the building load. Based on the established linkage rules, at a single simulation time step Within the simulation, mathematical models reflecting the transient thermodynamic processes of each subsystem are invoked and solved simultaneously. These mathematical models include a variable operating condition model reflecting the coefficient of performance of the heat pump unit as a function of evaporation and condensation temperatures, a temperature change model of the heat storage device based on energy conservation, and a thermal resistance-capacity model describing the unsteady heat exchange between the geotextile and the surrounding soil. By coupling these models according to the system topology and control logic, and simultaneously solving their control equations within each simulation step, the temperature and flow distribution of the fluid in the geotextile, the working fluid in the heat storage device, and each connecting pipe are calculated synchronously and iteratively. This ultimately yields the net heat exchange of the geotextile heat exchanger, the net heat storage / release of the heat storage device, and the power consumption of the heat pump unit within that simulation step.

[0030] The expression for the variable operating condition model is as follows: In the formula, The coefficient of performance (COP) of a heat pump. The coefficient of performance (COP) of the heat pump; and These are the heat pump performance functions under heating and cooling conditions, respectively, which are obtained by fitting performance data tables provided by the equipment manufacturer. , These are the average heat exchange fluid temperatures of the evaporator and condenser, respectively, which are determined in the simultaneous solution of the system. For the power consumption of the heat pump unit; , These are the condenser's heating capacity and the evaporator's heat absorption, respectively. The above calculation The formula describes the power consumption of the heat pump unit. Calculation methods under different operating modes: When the system is in heating mode, i.e. At that time, the power consumption of the heat pump unit is equal to When the system is in cooling mode, that is... At that time, the power consumption of the heat pump unit is equal to This reflects the direct relationship between heat pump power consumption, effective heat exchange, and coefficient of performance. That is, the energy consumption of a heat pump unit is directly proportional to the cooling / heating it provides and inversely proportional to the coefficient of performance, thus dynamically linking the energy consumption characteristics of the heat pump under varying operating conditions with the system load demand and operating mode.

[0031] The expression for the temperature change model of the heat storage device is as follows: In the formula, The net heat storage / release of the heat storage device; Specific heat capacity of the heat storage medium; The average temperature of the medium inside the heat storage device. The ambient temperature; , These represent the fluid from the first... The mass flow rate and temperature of the heat storage device when it flows into the inlet. This serves as an index for the inlet within the thermal storage device. The number of inlets within the thermal storage device; and These represent the fluid from the first... The mass flow rate and temperature of the heat storage device when it exits the outlet. This is an index for the outlet within the thermal storage device. This refers to the number of outlets within the heat storage device. The heat loss coefficient of the heat storage device was determined experimentally. The heat dissipation surface area of ​​the heat storage device; For this formula, the dependent variable Used to characterize the net heat storage / release of the heat storage medium in the heat storage device within a single simulation step; when its value is positive, it indicates that the device stores net heat within that step, and when its value is negative, it indicates that the device releases net heat. The absolute value of the value directly reflects the intensity of heat storage or release of the device per unit time: the larger the value, the faster the rate of heat storage or release and the stronger the energy regulation capability of the device; the smaller the value, the smoother the energy exchange of the device.

[0032] The mass flow rate and temperature of the fluid during inflow affect the energy input of the device: a larger inflow rate and higher temperature result in more heat input, promoting heat storage; conversely, a smaller inflow rate reduces heat input. The mass flow rate and temperature of the fluid during outflow affect the energy output of the device: a larger outflow rate and higher temperature result in more heat output, promoting heat release. Therefore... along with Increase and increase, with The term decreases as the temperature difference term decreases. The device's heat dissipation conditions relative to the environment: When the temperature of the medium inside the device is higher than the ambient temperature, heat is dissipated into the environment through the walls, leading to... Decrease.

[0033] This formula is based on the principle of energy conservation and describes the energy change of the thermal storage device during dynamic operation: the net heat storage / release within the device is obtained by subtracting the total heat flowing in from the total heat flowing out, and then deducting the heat loss to the outside. The formula has a clear structure and a clear physical meaning. It takes into account the general configuration of multiple inlets and outlets, and also includes the unavoidable heat loss in actual operation. It can realistically simulate the transient thermal behavior of the thermal storage device under varying operating conditions, and provides a reliable mathematical model basis for the dynamic energy scheduling of the system.

[0034] Table 1: Net Heat Storage / Release Statistics It should be noted that in Table 1, the net inflow of total heat flow, net outflow of total heat flow, heat loss error, and net stored / released heat correspond to the formulas in the table. , , and item.

[0035] Based on the analysis of the 15 sets of data in Table 1, it can be seen that... The change is a direct reflection of the combined effect of net inflow to total heat flow, net outflow to total heat flow, and the temperature difference due to heat loss: when the increase in net inflow to total heat flow dominates, It shows an upward trend; conversely, when the increase in net outflow of total heat flow or the increase in heat loss error dominates, Then it turns to decrease: for example, in time steps 1-3, the net inflow of total heat flux increases significantly, while the net outflow of total heat flux and the heat loss error remain constant. The significant increase from 2.7 to 9.7 clearly demonstrates a positive driving effect; however, when comparing control variables, the negative suppressive effect of net outflow total heat flow and heat loss error is equally significant: in time steps 3-5 where net inflow total heat flow and heat loss error remain constant, the increase in net outflow total heat flow directly leads to The value decreased from 9.7 to 2.7; similarly, in time steps 5-7, the increase in heat loss error also caused... It further decreased from 1.95 to 0.45.

[0036] The expression for the thermal resistance-capacity model is as follows: In the formula, The instantaneous heat exchange between the geothermal tube heat exchanger and the soil is positive for heat absorption and negative for heat release. The average temperature of the circulating fluid within the geographical pipe; This indicates the soil temperature at the surface of the geotextile tube; This represents the total thermal resistance from the fluid to the soil; Will Defined as the net heat exchange capacity of a geotextile heat exchanger.

[0037] For this formula, the dependent variable This value characterizes the instantaneous heat exchange between the geotextile heat exchanger and the surrounding soil per unit time. A positive value indicates that the geotextile absorbs heat from the soil, while a negative value indicates that the geotextile releases heat into the soil. The absolute value directly reflects the heat exchange intensity. The larger the absolute value, the faster the heat exchange rate and the more intense the energy exchange between the geotextile tube and the soil; conversely, the heat exchange process is relatively gentle.

[0038] This reflects the temperature difference between the fluid inside the buried pipe and the soil outside the pipe wall. According to the basic principle of heat conduction, heat always flows from a high-temperature region to a low-temperature region. The greater the temperature difference, the stronger the driving force of heat transfer. Follow It increases with the increase of; This reflects the resistance encountered during the transfer of heat from the fluid inside the buried pipe to the surrounding soil, including the thermal resistance of the pipe wall material, the thermal resistance of the soil, and the contact thermal resistance. The greater the thermal resistance, the more difficult the heat transfer. and They are inversely proportional.

[0039] This formula is a simplified expression of a typical steady-state thermal resistance model. It is based on the analogy of Ohm's law of heat transfer, that is, heat flow equals temperature difference divided by thermal resistance. Although the heat exchange between the buried pipe and the soil is actually a non-steady-state process, when a small time step is used in the simulation, it can be approximated that the heat exchange process is in a quasi-steady state within each step. Thus, the simplified model can be used to quickly calculate the instantaneous heat exchange.

[0040] Step 4: Based on the net heat exchange of the geothermal heat exchanger, update the soil temperature field at the start of the next simulation time step. At the same time, based on the net heat storage / release of the heat storage device, update the temperature and remaining heat storage capacity of the heat storage device at the start of the next simulation time step. In this embodiment, the calculated net heat exchange capacity of the geotextile heat exchanger is used. As a term representing the heat source away from the ground, it is input into a three-dimensional numerical calculation model centered on the geodetic borehole and considering unsteady heat conduction in the radial and depth directions of the soil. In this three-dimensional numerical calculation model, the soil temperature field at the current simulation moment is used as the initial condition, and the far-field soil temperature is used as the constant boundary condition. By solving the transient heat conduction control equation, the calculation is performed over a single simulation time step under the influence of the heat source away from the ground. The temperature distribution across the entire computational domain was then analyzed, and the radial distance from the borehole wall was extracted. The soil temperature distribution is used as the updated soil temperature field for the start of the next simulation step; whereby... The preset radius of influence is set based on the thermal diffusion characteristics of the soil around the geodetic borehole and the simulation time step.

[0041] The calculated net heat storage / release heat of the heat storage device As input, the total heat capacity of the thermal storage device is first considered. Calculate the resulting average temperature change Then, based on the temperature of the heat storage device at the current simulation moment... Calculate the temperature of the heat storage device at the start of the next simulation time step. The formula it is based on is as follows: Simultaneously, based on the current remaining heat storage capacity of the heat storage device, and combined with the net heat storage / release of the heat storage device... The updated remaining heat storage capacity is obtained using the following formula: in, This represents the current remaining heat storage capacity of the heat storage device.

[0042] The above process first uses the net heat storage / release calculated using the current step size. Combined with the total heat capacity of the thermal storage device The average temperature change of the medium inside the device caused by this heat change was calculated. This updates the temperature of the heat storage device for the next moment. This temperature update reflects the actual thermal state change of the thermal storage device after absorbing or releasing heat, and is a key parameter for evaluating its energy storage capacity and system thermal matching.

[0043] Meanwhile, based on the current remaining heat storage capacity With net heat storage / release Update to obtain the remaining heat storage capacity at the next moment. ; It directly characterizes the available energy storage space of the thermal storage device at the current temperature. Its value increases with heat storage and decreases with heat release, providing a basis for energy scheduling and strategy selection in subsequent simulation steps. Through this iterative update mechanism, the system can continuously track the temperature and capacity status of the thermal storage device in the simulation to more realistically simulate its response and regulation in actual operation.

[0044] Step 5: Advance the simulation time by one step and repeat steps 1 to 4 until the set simulation cycle is completed. Based on the cumulative data of all simulation steps, generate curves of the system's comprehensive energy efficiency coefficient, soil thermal balance, and key parameters changing over time. The key parameters include soil temperature, heat storage device temperature, and system operation strategy. In this embodiment, after the simulation cycle is completed, the power consumption of the heat pump unit calculated in each simulation time step and the actual cooling / heating supplied to the building load in that simulation time step are extracted and accumulated. ;in, The value is obtained from the results of solving the mathematical model according to the linkage rules determined in step 3. Its physical meaning is the sum of the heat supplied to the load directly by the solar collector subsystem and the heat supplied to the load by the heat pump unit through the condenser. Based on the cumulative data from all simulation steps, the overall system energy efficiency coefficient and soil thermal balance are generated, using the following formulas: In the formula, The overall energy efficiency coefficient of the system; Indicates the first The power consumption of a heat pump unit with a simulated time step. For the simulation time step index, This represents the total number of simulation time steps; Indicates the first The actual cooling / heating supplied to the building load within each simulation time step; For this formula, the dependent variable Used to characterize the overall energy utilization efficiency of the entire solar ground source heat pump system within a set simulation period; The higher the value, the higher the energy efficiency of the system in meeting the building load, meaning the more cooling / heating is provided per unit of electricity consumption, and the better the system's economy and energy saving; conversely, if... A smaller value indicates lower system energy efficiency, relatively higher energy consumption of the heat pump unit or the overall system, and the need to improve energy utilization efficiency.

[0045] Indicates the first The cumulative value of the actual cooling / heating supplied to the building load within each simulation step. This reflects the system's total energy supply effect throughout the entire simulation cycle. A larger value indicates that the system outputs more effective energy, which is beneficial for improving performance. ; Indicates the first The cumulative power consumption of each step-size internal heat pump unit This represents the total electrical energy consumed by the system to drive the heat pump. The higher this value, the higher the system energy consumption, which will lead to… reduce.

[0046] This formula is based on the basic definition of energy efficiency, which is the ratio of the system's effective output energy to its input energy. It conforms to the general criteria for evaluating the energy efficiency of heat pump systems. In the simulation, by accumulating and comparing the energy supplied and consumed at each time step, it can comprehensively reflect the overall energy efficiency performance of the system in dynamic operation, rather than being limited to a certain instantaneous operating condition.

[0047] In the formula, Indicates the soil's heat balance; Indicates the first Net heat transfer of a geotube heat exchanger with a simulation time step; For this formula, the dependent variable It characterizes the degree of heat exchange balance between the buried pipe heat exchanger and the soil during the simulation period, reflecting the overall trend of soil heat accumulation or heat release. The closer the value is to 1, the more likely the buried pipe absorbs and releases heat from the soil during the entire simulation, indicating that the soil thermal state is in equilibrium; conversely, if... A smaller value indicates that the soil has a significant net heat absorption or release within a cycle, and there is a tendency for heat accumulation or heat loss. Long-term operation may lead to a continuous increase or decrease in soil temperature, affecting system stability and heat exchange efficiency.

[0048] This represents the cumulative net heat exchange between the buried pipe and the soil throughout the entire simulation period. A positive value indicates that the buried pipe absorbs net heat from the soil, and the soil temperature tends to decrease; a negative value indicates that the buried pipe releases net heat to the soil, and the soil temperature tends to increase. The larger the absolute value of this cumulative value, the more severe the soil thermal imbalance, leading to an increase in the numerator in the formula, and thus... The net heat exchange decreases; therefore, the cumulative value of net heat exchange directly affects the calculation results of soil heat balance, reflecting the long-term impact of system operation on the soil thermal environment.

[0049] This formula quantifies the balance of soil heat exchange by comparing the absolute value of net heat exchange with the ratio of total heat exchange. Its design is reasonable because the numerator represents the net heat change of the soil in a cycle, while the denominator represents the intensity of the total heat exchange activity. The smaller the ratio between the two, the lower the proportion of net heat change to total heat exchange, that is, the more balanced the soil thermal state.

[0050] Meanwhile, the soil temperature, heat storage device temperature, and system operation strategy corresponding to each simulation step within the entire simulation cycle are arranged in chronological order, and curves of the soil temperature, heat storage device temperature, and system operation strategy changing over time are generated respectively.

[0051] Please see Figure 3 A simulation system for a solar ground source heat pump system, comprising: The initialization and risk prediction module is used to acquire the initial soil temperature field data and set the soil temperature field at the current simulation time. Based on the soil temperature field at the current simulation time and the predicted average load in the future target period, a one-dimensional radial simplified heat transfer model is used to predict the cumulative change in soil temperature from the current simulation time to the end of the future target period, and it is defined as the soil thermal imbalance risk index. The strategy selection module is used to compare the soil thermal imbalance risk index with a preset risk threshold, and select a system operation strategy to guide the next simulation step based on the comparison result. The operation strategy includes an efficiency priority strategy that prioritizes the immediate utilization of solar energy, and a thermal balance priority strategy that prioritizes the active adjustment of the soil temperature field. The simulation calculation module is used to determine the linkage rules of each subsystem in the next simulation time step according to the selected system operation strategy, and then drive and jointly solve the dynamic mathematical model of each subsystem to calculate the net heat exchange of the geotube heat exchanger and the net heat storage / release of the heat storage device in the next simulation step. The state iteration update module is used to update the soil temperature field at the start of the next simulation time step based on the net heat exchange of the geographic pipe heat exchanger, and at the same time update the temperature and remaining heat storage capacity of the heat storage device at the start of the next simulation time step based on the net heat storage / release of the heat storage device. The cyclic output evaluation module is used to advance the simulation time by one step and repeat steps 1 to 4 until the set simulation cycle is completed. Based on the cumulative data of all simulation steps, it generates curves of the system's comprehensive energy efficiency coefficient, soil thermal balance, and key parameters changing over time. The key parameters include soil temperature, heat storage device temperature, and system operation strategy.

[0052] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0053] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0054] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0055] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A simulation method for a solar ground source heat pump system, characterized in that, The specific steps include: Step 1: Obtain the initial soil temperature field data and set the soil temperature field at the current simulation time accordingly. Based on the soil temperature field at the current simulation time and the predicted average load in the future target period, use a one-dimensional radial simplified heat transfer model to predict the cumulative change in soil temperature from the current simulation time to the end of the future target period, and define it as the soil thermal imbalance risk index. Step 2: Compare the soil thermal imbalance risk index with the preset risk threshold, and select a system operation strategy to guide the next simulation time step based on the comparison results. The operation strategy includes an efficiency priority strategy that prioritizes the immediate utilization of solar energy, and a thermal balance priority strategy that prioritizes the active adjustment of the soil temperature field. Step 3: Based on the selected system operation strategy, determine the linkage rules of each subsystem in the next simulation time step, and then drive and jointly solve the dynamic mathematical model of each subsystem to calculate the net heat exchange of the geotube heat exchanger and the net heat storage / release of the heat storage device in the next simulation step. Step 4: Based on the net heat exchange of the geothermal heat exchanger, update the soil temperature field at the start of the next simulation time step. At the same time, based on the net heat storage / release of the heat storage device, update the temperature and remaining heat storage capacity of the heat storage device at the start of the next simulation time step. Step 5: Advance the simulation time by one step and repeat steps 1 to 4 until the set simulation cycle is completed. Based on the cumulative data of all simulation steps, generate curves of the system's comprehensive energy efficiency coefficient, soil thermal balance, and key parameters changing over time. The key parameters include soil temperature, heat storage device temperature, and system operation strategy.

2. The simulation method for a solar ground source heat pump system according to claim 1, characterized in that: The temperature distribution data of the depth-radial discrete grid with the geographic borehole center as the reference is obtained as the soil initial temperature field. The soil initial temperature field is initialized by assigning values ​​to the grid nodes to initialize the temperature values ​​of each calculation unit in the soil heat transfer model, thereby setting the soil temperature field at the current simulation time. The method for determining the predicted average load during the future target period is as follows: acquiring historical meteorological data for the same season as the future target period and corresponding historical hourly building load data, wherein the meteorological data includes daily average outdoor temperature and daily average solar radiation intensity; secondly, acquiring short-term meteorological forecast data for the future target period, including predicted daily average outdoor temperature and predicted daily average solar radiation intensity. The linear meteorological correction factor method is used to correct historical hourly building load data. The formula used is as follows: In the formula, This represents the corrected load at time t within the future target time period, where t is the time variable of the future target time period; This represents the historical building load at time t within the future target time period; This represents the predicted daily average outdoor temperature at time t within the target future time period. This represents the historical daily average outdoor temperature at time t within the future target time period; This represents the predicted daily average solar radiation intensity at time t within the target future time period. This represents the historical daily average solar radiation intensity at time t within the future target time period; This is the temperature influence coefficient. The radiation impact coefficient must be met during the heating season. , During the cooling season, it meets the requirements. , ; The arithmetic mean of the corrected load at each time point within the future target period is taken, and the calculation result is calibrated as the predicted average load within the future target period. After setting the current soil temperature field and obtaining the predicted average load, the predicted average load is input as a constant boundary heat flux density into a one-dimensional radial simplified heat transfer model. The soil temperature field at the current simulation moment is used as the initial temperature distribution. The transient heat conduction control equation of the model is solved numerically to calculate the cumulative temperature change of the soil at the geographical pipe wall from the current simulation moment to the end of the future target time period. This change is defined as the soil thermal imbalance risk index.

3. The simulation method for a solar ground source heat pump system according to claim 2, characterized in that: The risk threshold is the first threshold: When the soil thermal imbalance risk index is less than the first threshold, the soil thermal state is determined to be within a safe range, and the efficiency-first strategy is selected. When the soil thermal imbalance risk index is greater than or equal to the first threshold, it is determined that there is a risk of soil thermal imbalance, and the thermal balance priority strategy is selected.

4. The simulation method for a solar ground source heat pump system according to claim 3, characterized in that: Based on the selected system operation strategy, the linkage rules of each subsystem within the next simulation time step are determined. The specific logic is as follows: if the efficiency priority strategy is selected, the linkage rules are set as follows: all the heat produced by the solar thermal collector subsystem is given priority to be directly supplied to the building load. When there is excess heat, it is stored in the heat storage device. Only when neither of them can meet the load demand will the heat pump unit be started to absorb heat from the geothermal heat exchanger or discharge heat to it. If the heat balance priority strategy is selected, the linkage rule is set as follows: with the goal of actively regulating the soil temperature field, the heat storage device and the solar collector subsystem are linked first to jointly provide or extract heat to the geothermal heat exchanger. Only when the soil temperature regulation target is achieved and there is remaining heating or cooling capacity will the heat be allocated to the building load. Based on the established linkage rules, at a single simulation time step Within the simulation, mathematical models reflecting the transient thermodynamic processes of each subsystem are invoked and solved simultaneously. These mathematical models include a variable operating condition model reflecting the coefficient of performance of the heat pump unit as a function of evaporation and condensation temperatures, a temperature change model of the heat storage device based on energy conservation, and a thermal resistance-capacity model describing the unsteady heat exchange between the geotextile and the surrounding soil. By coupling these models according to the system topology and control logic, and simultaneously solving their control equations within each simulation step, the temperature and flow distribution of the fluid in the geotextile, the working fluid in the heat storage device, and each connecting pipe are calculated synchronously and iteratively. This ultimately yields the net heat exchange of the geotextile heat exchanger, the net heat storage / release of the heat storage device, and the power consumption of the heat pump unit within that simulation step.

5. The simulation method for a solar ground source heat pump system according to claim 4, characterized in that: The expression for the variable operating condition model is as follows: In the formula, The coefficient of performance (COP) of a heat pump. The coefficient of performance (COP) of the heat pump; and These are the heat pump performance functions under heating and cooling conditions, respectively, which are obtained by fitting performance data tables provided by the equipment manufacturer. , These are the average heat exchange fluid temperatures of the evaporator and condenser, respectively, which are determined in the simultaneous solution of the system. For the power consumption of the heat pump unit; , These are the condenser's heating capacity and the evaporator's heat absorption, respectively. The expression for the temperature change model of the heat storage device is as follows: In the formula, The net heat storage / release of the heat storage device; Specific heat capacity of the heat storage medium; The average temperature of the medium inside the heat storage device; Ambient temperature; , These represent the fluid from the first... The mass flow rate and temperature of the heat storage device when it flows into the inlet. This serves as an index for the inlet within the thermal storage device. This refers to the number of inlets within the thermal storage device; and These represent the fluid from the first... The mass flow rate and temperature of the heat storage device when it exits the outlet. This is an index for the outlet within the thermal storage device. This refers to the number of outlets within the heat storage device. The heat loss coefficient of the heat storage device; The heat dissipation surface area of ​​the heat storage device; The expression for the thermal resistance-capacity model is as follows: In the formula, The instantaneous heat exchange between the geothermal tube heat exchanger and the soil is positive for heat absorption and negative for heat release. The average temperature of the circulating fluid within the pipe; This indicates the soil temperature at the surface of the geotextile tube; This represents the total thermal resistance from the fluid to the soil; Will Defined as the net heat exchange capacity of a geotextile heat exchanger.

6. The simulation method for a solar ground source heat pump system according to claim 5, characterized in that: The calculated net heat exchange capacity of the geothermal heat exchanger As a term representing the heat source away from the ground, it is input into a three-dimensional numerical calculation model centered on the geodetic borehole and considering unsteady heat conduction in the radial and depth directions of the soil. In this three-dimensional numerical calculation model, the soil temperature field at the current simulation moment is used as the initial condition, and the far-field soil temperature is used as the constant boundary condition. By solving the transient heat conduction control equation, the calculation is performed over a single simulation time step under the influence of the heat source away from the ground. The temperature distribution across the entire computational domain was then analyzed, and the radial distance from the borehole wall was extracted. The soil temperature distribution is used as the updated soil temperature field for the start of the next simulation step; whereby... The preset radius of influence; The calculated net heat storage / release heat of the heat storage device As input, the total heat capacity of the thermal storage device is first considered. Calculate the resulting average temperature change ; Then, based on the temperature of the heat storage device at the current simulation moment... Calculate the temperature of the heat storage device at the start of the next simulation time step. The formula it is based on is as follows: Simultaneously, based on the current remaining heat storage capacity of the heat storage device, and combined with the net heat storage / release of the heat storage device... The updated remaining heat storage capacity is obtained using the following formula: in, This represents the current remaining heat storage capacity of the heat storage device.

7. The simulation method for a solar ground source heat pump system according to claim 1, characterized in that: After the simulation cycle is completed, the heat pump unit power consumption calculated in each simulation time step and the actual cooling / heating supplied to the building load in that simulation time step are extracted and accumulated. ;in, The value is obtained from the results of solving the mathematical model according to the linkage rules determined in step 3. Its physical meaning is the sum of the heat supplied to the load directly by the solar collector subsystem and the heat supplied to the load by the heat pump unit through the condenser. Based on the cumulative data from all simulation steps, the overall system energy efficiency coefficient and soil thermal balance are generated, using the following formulas: In the formula, The overall energy efficiency coefficient of the system; Indicates the first The power consumption of a heat pump unit with a simulated time step. For the simulation time step index, This represents the total number of simulation time steps; Indicates the first The actual cooling / heating supplied to the building load within each simulation time step; In the formula, Indicates the soil's heat balance; Indicates the first Net heat transfer of a geotube heat exchanger with a simulation time step; Meanwhile, the soil temperature, heat storage device temperature, and system operation strategy corresponding to each simulation step within the entire simulation cycle are arranged in chronological order, and curves of the soil temperature, heat storage device temperature, and system operation strategy changing over time are generated respectively.

8. A simulation system for a solar ground source heat pump system, characterized in that: The simulation system for a solar ground source heat pump system is used to execute the simulation method for a solar ground source heat pump system according to any one of claims 1-7, comprising: The initialization and risk prediction module is used to acquire the initial soil temperature field data and set the soil temperature field at the current simulation time. Based on the soil temperature field at the current simulation time and the predicted average load in the future target period, a one-dimensional radial simplified heat transfer model is used to predict the cumulative change in soil temperature from the current simulation time to the end of the future target period, and it is defined as the soil thermal imbalance risk index. The strategy selection module is used to compare the soil thermal imbalance risk index with a preset risk threshold, and select a system operation strategy to guide the next simulation step based on the comparison result. The operation strategy includes an efficiency priority strategy that prioritizes the immediate utilization of solar energy, and a thermal balance priority strategy that prioritizes the active adjustment of the soil temperature field. The simulation calculation module is used to determine the linkage rules of each subsystem in the next simulation time step according to the selected system operation strategy, and then drive and jointly solve the dynamic mathematical model of each subsystem to calculate the net heat exchange of the geotube heat exchanger and the net heat storage / release of the heat storage device in the next simulation step. The state iteration update module is used to update the soil temperature field at the start of the next simulation time step based on the net heat exchange of the geographic pipe heat exchanger, and at the same time update the temperature and remaining heat storage capacity of the heat storage device at the start of the next simulation time step based on the net heat storage / release of the heat storage device. The cyclic output evaluation module is used to advance the simulation time by one step and repeat steps 1 to 4 until the set simulation cycle is completed. Based on the cumulative data of all simulation steps, it generates curves of the system's comprehensive energy efficiency coefficient, soil thermal balance, and key parameters changing over time. The key parameters include soil temperature, heat storage device temperature, and system operation strategy.

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