Compensation regulation method for climate-adaptive medium-deep closed heat extraction geothermal heat supply

Abstract

The application discloses a climate-adaptive compensation regulation method for medium-deep closed heat extraction and heat supply, and belongs to the technical field of geothermal energy development and utilization and intelligent heat supply regulation. The method comprises the following steps: obtaining climate prediction data and building heat load prediction data of a target heat supply area in a future prediction period, and geological parameters and operation parameters of a medium-deep closed heat extraction and heat exchange hole group; establishing a non-steady-state heat transfer model of the medium-deep closed heat extraction and heat exchange hole group, and calculating a rock-soil temperature field, a hole wall temperature and a circulating working medium outlet temperature under different heat extraction powers and intermittent operation conditions; determining a geothermal sustainable heat extraction threshold according to the geological parameters and the geothermal temperature recovery characteristics, and determining a compensation heat load at each time in the prediction period based on the climate prediction data. The application can adaptively adjust the medium-deep geothermal heat extraction power and the compensation heat source output according to climate fluctuations and building load changes, improve the geothermal utilization efficiency, alleviate the geothermal temperature attenuation, and reduce the system operation energy consumption and carbon emissions.

Description

Technical Field

[0001] This invention relates to the field of geothermal energy development and utilization and intelligent heating regulation technology, specifically to a climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method. Background Technology

[0002] Medium-deep geothermal energy refers to the thermal energy contained in rock and soil masses at depths generally greater than 200 meters and temperatures above 25°C. Medium-deep geothermal energy boasts advantages such as large reserves, wide distribution, stability, reliability, and immunity to seasonal and weather influences, making it an important renewable energy source for building heating. Medium-deep closed-loop heat extraction technology, also known as medium-deep buried pipe heat exchange technology or coaxial sleeve heat exchange technology, is characterized by "heat extraction without water extraction." This involves circulating working fluid within a coaxial sleeve heat exchanger exchanging heat with the high-temperature rock and soil mass in a closed pipeline, extracting heat from the strata and transferring it to the surface heating system. This technology avoids the extraction of groundwater, thus preventing impacts on groundwater resources and the environment, and has seen increasing application in the field of clean heating in recent years.

[0003] Under typical geological structures, the temperature and heat transfer capacity of medium-deep geothermal heat exchange vents are closely related to strata lithology, geothermal gradient, thermal conductivity, volumetric heat capacity, and groundwater seepage conditions. For example, in the sedimentary rock areas of the North China Plain, the original geothermal temperature at a depth of 2000m is approximately 65–80℃, and the heat extraction power of a single vent is typically 300–400kW. In the granite areas of Northeast China, the geothermal gradient is higher, with the geothermal temperature reaching 90–110℃ at a depth of 2500m, resulting in a stronger heat extraction capacity per vent. In the limestone areas of South China, the geothermal gradient is lower, making medium-deep geothermal energy more suitable for use as a low-temperature heat source in conjunction with heat pumps. Engineering heat utilization analysis shows that the heat extraction power of heat exchange vents depends not only on geological conditions but is also significantly affected by factors such as operating mode, circulation flow rate, heat extraction temperature difference, and intermittent recovery time.

[0004] However, existing medium-deep closed-loop geothermal heating systems have the following prominent problems in operation and control: The operation mode is relatively crude. Most systems operate with constant flow and constant heat extraction power, and cannot adjust the heat extraction in a timely manner according to changes in outdoor climate conditions and building heat load. This results in excessive heat extraction during some periods and insufficient heat extraction during others, leading to low overall system energy efficiency.

[0005] The problem of geothermal temperature decay is prominent. The temperature recovery rate of the soil and rock surrounding medium-deep geothermal heat exchange holes is slow. If excessive heat is extracted continuously for a long period, the hole wall temperature will decrease year by year, the outlet temperature of the heat exchange hole will decrease, and the geothermal utilization efficiency will be significantly reduced. Current technologies lack regional rotation and active heat replenishment control methods based on the geothermal temperature recovery status.

[0006] The coupling and regulation of auxiliary heat sources with geothermal systems are not coordinated. Medium-deep geothermal systems are typically equipped with auxiliary heat sources such as air source heat pumps, gas boilers, electric boilers, or solar collectors to cope with extreme weather and peak loads. However, existing control strategies often start and stop auxiliary heat sources based on simple temperature thresholds, lacking feedforward control based on climate forecasts, which can easily lead to frequent start-ups and shutdowns of auxiliary heat sources, increased energy consumption, or insufficient heating.

[0007] Lack of adaptability to climate change. Short-term fluctuations and medium- to long-term changes in meteorological factors such as outdoor temperature, solar radiation, and wind speed have a significant impact on building heat load. Existing medium-deep geothermal heating systems rarely incorporate climate forecast data into their operation and control, and cannot fully utilize climate information for day-ahead scheduling and intraday correction, resulting in poor system operation economy and reliability.

[0008] Differences in geological conditions have not been fully considered in the regulation. The thermal response characteristics of heat exchange pores vary greatly under different geological structures. Existing regulation methods often use uniform operating parameters and fail to provide personalized regulation based on actual geological stratification, groundwater seepage, and geothermal recovery characteristics.

[0009] Therefore, there is an urgent need for a climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method to solve the above problems. Summary of the Invention

[0010] The purpose of this invention is to provide a climate-adaptive, closed-loop geothermal heating compensation and control method. This method can dynamically optimize the geothermal heating power and compensation heat source output of the medium-deep geothermal system based on climate forecast data, building load prediction data and geological conditions, implement zone rotation and geothermal recovery compensation, improve geothermal utilization efficiency, reduce system operating costs and alleviate geothermal attenuation.

[0011] To achieve the above objectives, the present invention provides the following technical solution: A climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method includes the following steps: S1. Obtain climate forecast data and building heat load forecast data for the target heating area during the future forecast period, as well as the geological parameters and operating parameters of the medium-deep closed heat exchange hole group. S2. Establish an unsteady heat transfer model for a group of medium-deep closed heat extraction and heat exchange holes, and calculate the soil and rock temperature field, hole wall temperature and circulating working fluid outlet temperature under different heat extraction power and intermittent operation conditions. S3. Determine the sustainable geothermal heat extraction threshold based on geological parameters and geothermal recovery characteristics, and determine the compensation heat load for each time period within the forecast period based on climate forecast data; wherein, the sustainable geothermal heat extraction threshold is determined according to the following formula:

[0012] In the formula, Let be the thermal conductivity of the soil and rock in the i-th geological layer, in units of . ; ,i is the original geothermal temperature of the i-th layer, in °C; T_min,i is the minimum allowable borehole wall temperature of the i-th layer, in °C; The equivalent thermal resistance of the i-th layer is defined as the radial thermal resistance per unit length of the i-th geological layer, with units of m·K / W, and is calculated based on the radial heat transfer equation and the thermal resistance of the borehole tube for that layer; SF is the safety factor, with a value ranging from 1.2 to 1.5. S4. With the goal of minimizing the total system operating cost during the predicted period, and using geothermal heat extraction power, compensation heat source power, and thermal storage device power as optimization variables, the day-ahead scheduling plan is obtained by satisfying the constraints of heat load balance, geothermal heat extraction capacity, ground temperature recovery, and compensation heat source capacity. The total system operating cost includes electricity cost, fuel cost, and carbon emission cost under time-of-use pricing. S5. Real-time acquisition of outdoor temperature, circulating working fluid return water temperature, user-side supply and return water temperature and temperature of each hole in the geothermal heat exchange hole group, and feedforward-feedback composite control of circulating pump frequency, geothermal side electric regulating valve, compensation heat source and heat storage device. S6. Divide the heat exchange pore group into an operating zone, a recovery zone, and a standby zone. Rotate zones according to the temperature recovery rate of each pore wall. During low-load periods, use a compensating heat source or renewable energy to reinject heat into the formation to accelerate ground temperature recovery. The recovery rate γ is defined as:

[0013] In the formula, To restore the borehole wall temperature, T_min is the lowest borehole wall temperature during operation. This represents the original borehole wall temperature. The conditions for the zone rotation are as follows: when the temperature recovery degree γ of the hole wall in the recovery zone reaches 0.9, it is transferred to the standby zone; when the hole wall temperature in the operating zone is lower than the minimum allowable hole wall temperature T_min,i of that layer, it is cut off to the recovery zone; the standby zone is put into operation when the heat extraction capacity of the operating zone is insufficient. The heat reinjection medium is a circulating working fluid heated by solar energy collection, air source heat pump, or industrial waste heat, with a replenishment temperature of 35-60℃. S7. Update the parameters of the unsteady heat transfer model and load prediction model online using historical operating data and real-time monitoring data; The compensating heat source is an auxiliary heat source coupled to the geothermal system, selected from at least one of a gas boiler, an electric boiler, an air source heat pump, a solar collector, or an industrial waste heat exchanger.

[0014] Further, in step S1, the climate forecast data includes outdoor dry-bulb temperature, relative humidity, solar radiation, wind speed, and cloud cover; the building heat load forecast data is obtained by weighting a physical model and a data-driven model, wherein the physical model adopts the equivalent full load hours method, and the data-driven model adopts a multiple regression or neural network model based on historical meteorological data and heat load data, and the weighting coefficients are dynamically adjusted according to the prediction lead time and the historical prediction error of the model.

[0015] Furthermore, in step S2, the unsteady-state heat transfer model uses the finite difference method to discretize the coaxial tube heat exchanger, dividing the formation radially into a near-hole zone, a transition zone, and a far-hole zone, and discretizing the axial direction according to geological stratification, taking into account groundwater seepage and changes in formation thermal properties with temperature; the circulating working fluid in the inner and outer tubes and annular cavity of the coaxial tube heat exchanger is described by a one-dimensional convective heat transfer equation, and solved by coupling the thermal resistance of the tube with the formation heat transfer equation.

[0016] The formation thermal properties change with temperature using the following linear correction relationship:

[0017]

[0018] In the formula, ,ref and ,ref represents the reference temperature of the i-th layer. Thermal conductivity and volumetric heat capacity at i; This is the temperature correction factor for thermal conductivity, with a value ranging from -0.002 to 0.003 / ℃. This is the volumetric heat capacity temperature correction factor, with a value range of -0.001 to 0.002 / ℃.

[0019] Furthermore, in step S3, the compensated heat load is the difference between the building heat load and the sustainable geothermal heat extraction power during the predicted period:

[0020] In the formula, , Predict the building heat load at time t. This refers to the system's thermal efficiency.

[0021] Further, in step S4, the ground temperature recovery constraint in the constraint conditions is: within one recovery cycle, the average temperature recovery rate of the heat exchange orifice wall is not less than 85%; the mapping relationship between the total power consumption and fuel consumption of the system and the optimization variables in the optimization objective is:

[0022]

[0023] In the formula, The power consumption of the circulating pump is proportional to the cube of the geothermal circulation flow rate. The power consumption of an air source heat pump is equal to the heat pump's heating capacity divided by its coefficient of performance (COP). ; Electricity consumption of an electric boiler is equal to the boiler's heating capacity divided by its efficiency. ; Powering the gas-fired boiler LHV represents the lower heating value of the gas-fired boiler.

[0024] Further, in step S5, the feedforward-feedback composite control specifically involves: generating a feedforward control curve based on the 24-hour climate forecast and load prediction; and adjusting the control based on the real-time return water temperature deviation. PI feedback correction is performed; when the outdoor temperature prediction deviation exceeds the set threshold, the model predictive control rolling optimization is triggered. The rolling optimization time domain is 4 to 8 hours, and the control step size is 10 to 30 minutes.

[0025] Furthermore, in step S6, the heat power of the heat reinjection does not exceed 50% to 80% of the normal heat extraction power of the hole.

[0026] Furthermore, in step S7, the online parameter update adopts extended Kalman filtering or particle filtering, using the circulating working fluid outlet temperature error as the observed value to update the formation equivalent thermal conductivity, volumetric heat capacity and orifice thermal resistance. The update cycle is 24 hours or triggered when the prediction error continuously exceeds twice the threshold.

[0027] In the extended Kalman filter, the process noise covariance Take 1% to 5% of the initial parameter values ​​to construct a diagonal matrix; measure the noise covariance. Take the square of the standard deviation of the circulating working fluid outlet temperature measurement; initial error covariance matrix. The squares of the initial standard deviations of the parameters are used to construct a diagonal matrix.

[0028] This invention also provides a climate-adaptive, mid-deep, closed-loop geothermal heating compensation and control system, comprising: The meteorological data acquisition module is used to acquire climate forecast data for the target heating area during the future prediction period; The load forecasting module is used to generate building heat load forecasting data based on climate forecast data, building thermal parameters, and historical heat consumption data; The geothermal heat transfer model module is used to establish an unsteady heat transfer model of a group of medium-deep closed heat extraction and exchange holes, and to calculate the temperature field of the soil and rock, the hole wall temperature and the outlet temperature of the circulating working fluid. The optimization scheduling module is used to solve the day-ahead scheduling plan for geothermal heat extraction power, compensation heat source power, and thermal storage device power with the goal of minimizing the total system operating cost within the predicted period; the total system operating cost includes electricity cost, fuel cost, and carbon emission cost under time-of-use pricing. The real-time control module is used to collect outdoor temperature, circulating working fluid return water temperature, user-side supply and return water temperature and temperature of each hole in the geothermal heat exchange hole group in real time, and to perform feedforward-feedback composite regulation of circulating pump frequency, geothermal side electric regulating valve, compensation heat source and heat storage device. The zone rotation management module is used to divide the heat exchanger orifice group into an operating zone, a recovery zone, and a standby zone, and to perform zone rotation based on the temperature recovery degree of each orifice wall, and control the heat reinjection during low-load periods; the recovery degree γ is defined as... ,in To restore the temperature of the borehole wall, This represents the lowest borehole wall temperature during operation. The original borehole wall temperature is used for the zone rotation. When the borehole wall temperature recovery rate γ in the recovery zone reaches 0.9, the zone is switched to the standby zone. When the borehole wall temperature in the operating zone is lower than the minimum allowable borehole wall temperature, the zone is switched to the recovery zone. The standby zone is put into operation when the heat extraction capacity of the operating zone is insufficient. The heat reinjection medium is a circulating working fluid heated by solar collectors, air source heat pumps, or industrial waste heat, with a supplementary temperature of 35-60℃. The data storage and model update module is used to store historical operating data and real-time monitoring data, and to update the parameters of the unsteady heat transfer model and load prediction model online.

[0029] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0030] Beneficial effects Compared with the prior art, the present invention has the following beneficial effects: This invention utilizes climate forecast data for day-ahead scheduling and intraday feedforward-feedback composite regulation, which can detect changes in outdoor temperature and solar radiation in advance, adaptively adjust geothermal heat extraction power and compensate for heat source output, avoid frequent start-up and shutdown of auxiliary heat sources and excessive heat extraction, and improve the reliability and economy of system heating.

[0031] This invention establishes an unsteady heat transfer model for a group of medium-deep, closed heat extraction and exchange orifices, and combines it with geological stratification, groundwater seepage, and geothermal recovery characteristics to accurately predict orifice wall temperature and outlet temperature under different operating conditions, providing a reliable basis for optimized regulation.

[0032] This invention introduces a geothermal recovery index and a zoned rotation strategy, enabling the heat exchange pore group to operate and recover alternately. During low-load periods, it utilizes solar energy, air-source heat pumps, or industrial waste heat to supplement heat to the strata, effectively mitigating geothermal decay and extending the service life of the medium-deep geothermal system.

[0033] This invention employs model predictive control and online parameter updates, which can continuously revise the heat transfer model and load prediction model based on actual operating data, thereby improving the control accuracy and adapting to the uncertainties of geological conditions and the long-term impact of climate change. Attached Figure Description

[0034] Figure 1 This is an overall flowchart of the climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0036] Analysis of temperature and heat transfer of medium-deep geothermal pores and their engineering heat utilization under typical geological structures The thermal performance of medium-deep closed geothermal heat exchange vents is closely related to the geological structure. Typical geological structures include sedimentary rocks, igneous rocks, metamorphic rocks, and fractured aquifers with groundwater seepage. Table 1 presents the main thermophysical parameters and engineering heat utilization analysis data of medium-deep geothermal heat exchange vents under typical geological structures.

[0037] Table 1. Analysis of temperature and heat transfer of medium-deep geothermal pores under typical geological structures.

[0038] Note: Surface temperature in Table 1 A temperature of 15℃ is uniformly used as the typical calculation condition. H represents depth; heat exchange per meter The outlet temperature of the heat exchanger orifice is related to the circulation flow rate, heat extraction power, and formation thermal properties; this represents a typical operating condition range. In actual engineering... Based on local measurements.

[0039] Table 1 shows that the temperature and heat transfer capacity of medium-deep geothermal vents vary significantly under different geological structures. In practical engineering, the formation thermal properties should be determined based on the geological survey report, and the temperature response and heat extraction capacity of the vents should be calculated in conjunction with the vent depth, circulating fluid flow rate, and operating mode. The method of this invention is based on these differences in geological conditions, and achieves refined operation of medium-deep geothermal systems through an unsteady-state heat transfer model and climate adaptive regulation.

[0040] II. Detailed Steps of the Method of the Invention Figure 1 The overall flow of the method of the present invention is shown. The specific steps are described in detail below.

[0041] Step S1: Obtain climate forecast data and building heat load forecast data for the target heating area during the future forecast period, as well as the geological parameters and operating parameters of the medium-deep closed heat exchange pore group.

[0042] Climate forecast data can be obtained from meteorological numerical weather prediction interfaces, local weather stations, or sky imagers, including outdoor dry-bulb temperature, relative humidity, solar radiation, wind speed, and cloud cover. The forecast period is generally 24 to 72 hours in the future, with a time resolution of 1 hour or 15 minutes.

[0043] The method for obtaining building heat load forecasting data is as follows: a weighted forecast using a physical model and a data-driven model. The physical model employs the equivalent full-load hours method, which calculates hourly heat load based on the building envelope heat transfer coefficient, building area, indoor design temperature, and outdoor temperature.

[0044] In the formula, The physical model predicts the heat load at time t. The overall heat transfer coefficient of the building is given by A, where A is the building area. For indoor design temperature, Let t be the outdoor temperature. Heat is gained from solar radiation. To dissipate heat for people and equipment indoors.

[0045] Data-driven models can employ multiple linear regression, support vector machines, random forests, or neural networks, taking historical meteorological data, historical heat load data, date type, and time as input, and outputting predicted heat load. .

[0046] The weighted predicted heat load is:

[0047] In the formula, the weighting coefficient α(t) is dynamically adjusted based on the prediction lead time and the model's historical prediction error. For example, for predictions within the next 6 hours, the physical model weight α is 0.3–0.4; for predictions within the next 6–24 hours, α is 0.5–0.7; and for predictions within the next 24–72 hours, α is 0.6–0.8. Furthermore, if the average absolute percentage error of the data-driven model over the past 7 days is less than 5%, its weight is appropriately increased.

[0048] Geological parameters include the lithology and thermal conductivity of each geological stratum. Volumetric heat capacity geothermal gradient Surface temperature Groundwater seepage rate Including orientation, orifice structure parameters (inner tube outer diameter, outer tube outer diameter, orifice diameter, depth), thermal conductivity of backfill material, etc. Operating parameters include circulating working fluid type, specific heat capacity, density, flow range, circulating pump head, heat pump unit capacity and coefficient of performance, auxiliary heat source type and capacity, and thermal storage device capacity, etc.

[0049] Step S2: Establish an unsteady heat transfer model for a group of medium-deep closed heat extraction and heat exchange holes, and calculate the soil and rock temperature field, hole wall temperature, and circulating working fluid outlet temperature under different heat extraction power and intermittent operation conditions.

[0050] In a medium-deep coaxial tube heat exchanger, the outer tube is in contact with the formation, and an annular cavity is formed between the inner and outer tubes. The circulating working fluid flows into the annular cavity, enters the inner tube at the bottom of the borehole, and then flows out to the surface. The low-temperature working fluid in the annular cavity absorbs heat from the formation, while heat exchange occurs between the high-temperature working fluid in the inner tube and the low-temperature working fluid in the annular cavity.

[0051] Unsteady heat transfer equation of formation:

[0052] In the formula, Let be the temperature of the i-th layer of soil and rock, t be time, r be the radial coordinate, and z be the axial coordinate. For the volumetric heat capacity of rock and soil, Thermal conductivity, The volumetric heat capacity of groundwater. This represents the groundwater seepage velocity.

[0053] Linear correction relationships are applied to the changes in formation thermal properties with temperature:

[0054]

[0055] In the formula, and The reference temperature of the i-th layer is respectively Thermal conductivity and volumetric heat capacity at i; This is the temperature correction factor for thermal conductivity, with a value ranging from -0.002 to 0.003 / ℃. This is the volumetric heat capacity temperature correction factor, with a value ranging from -0.001 to 0.002 / ℃. If measured temperature correction data is unavailable, it can be set as follows: and All values ​​are 0, degenerating into a constant property model.

[0056] Heat transfer equation for circulating working fluid inside the orifice: Circular cavity working fluid:

[0057] Inner tube working fluid:

[0058] In the formula, For the circulating working fluid mass flow rate, The specific heat capacity of the working fluid, The temperature of the working fluid in the annular cavity. The temperature of the working fluid in the inner tube. The temperature of the hole wall. The outer radius of the outer tube. The outer radius of the inner tube. The convective heat transfer coefficient between the annular cavity and the orifice wall is denoted as . The heat transfer coefficient of the inner tube wall is denoted as .

[0059] The above equations were discretized using the finite difference method. The radial grid was logarithmically refined, with a grid spacing of 0.01–0.1 m near the borehole and increasing to 1–10 m further away. The radial computational radius was generally taken as 10–50 m. Axial discretization was performed according to geological layers, with each layer having a grid length of 5–20 m. The time step was taken as 10–60 s to meet numerical stability requirements.

[0060] Based on the established model, different heat extraction powers can be calculated. Orifice wall temperature during intermittent operation and circulating working fluid outlet temperature The relationship between heat extraction power, circulation flow rate, and inlet / outlet temperature difference is as follows:

[0061] In the formula, The temperature of the working fluid entering the annular cavity from the ground. This refers to the outlet temperature of the inner tube.

[0062] Step S3: Determine the sustainable geothermal heat extraction threshold based on geological parameters and geothermal recovery characteristics, and determine the compensation heat load for each time period within the forecast period based on climate forecast data.

[0063] The sustainable geothermal heat extraction threshold refers to the heat power that a group of heat exchange pores can stably extract over a long period without causing a continuous decline in geothermal temperature beyond the allowable range. Based on geological stratification and the minimum allowable pore wall temperature, the sustainable geothermal heat extraction threshold is determined by the following formula:

[0064] In the formula, Let be the thermal conductivity of the soil and rock in the i-th geological layer, expressed in W / (m·K). The original geothermal temperature of the i-th layer is expressed in °C. This represents the minimum allowable hole wall temperature for the i-th layer, in °C. The equivalent thermal resistance of the i-th layer is defined as the radial thermal resistance per unit length of the i-th geological layer, with units of m·K / W, and is calculated based on the radial heat transfer equation and the thermal resistance of the borehole in that layer; SF is the safety factor, with a value ranging from 1.2 to 1.5.

[0065] Minimum allowable borehole wall temperature The value of i is generally taken as 70% to 80% of the original ground temperature of the layer, or a temperature drop limit of 5 to 10℃ based on engineering experience. Equivalent thermal resistance Calculated based on radial heat transfer resistance and borehole thermal resistance in geological stratification.

[0066] Compensating heat load is the difference between the building heat load and the sustainable geothermal heat extraction capacity during the forecast period.

[0067] In the formula, The system thermal efficiency includes heat loss from the heat exchange holes to the heat pump or heat exchanger.

[0068] When climate forecasts indicate a cold wave or prolonged low temperatures, the compensating heat load will increase, requiring advance arrangements for the operation of compensating heat sources or the storage of heat by heat storage devices.

[0069] Step S4: With the goal of minimizing the total operating cost of the system during the predicted period, and with geothermal heat extraction power, compensation heat source power, and thermal storage device power as optimization variables, the day-ahead scheduling plan is obtained by satisfying the constraints of heat load balance, geothermal heat extraction capacity, ground temperature recovery, and compensation heat source capacity.

[0070] The objective function is to minimize the total system operating cost within the prediction period.

[0071] In the formula, Let t be the time-of-use electricity price. This represents the total power consumption of the system. For gas or fuel prices, For gas consumption power, This is the carbon emission cost coefficient. This refers to carbon emissions.

[0072] The mapping relationship between the system's total electrical power consumption and fuel consumption power and the optimization variables is as follows:

[0073]

[0074] In the formula, The power consumption of the circulating pump is proportional to the cube of the geothermal circulation flow rate. The power consumption of an air source heat pump is equal to the heat pump's heating capacity divided by its coefficient of performance (COP). ; Electricity consumption of an electric boiler is equal to the boiler's heating capacity divided by its efficiency. ; Powering the gas-fired boiler LHV represents the lower heating value of the gas-fired boiler.

[0075] The constraints include: (1) Heat load balance constraint:

[0076] In the formula, For geothermal heat extraction power, To compensate for the output of the heat source, This refers to the heat release power of the heat storage device. The heat storage capacity of the heat storage device.

[0077] (2) Geothermal heat extraction capacity constraints:

[0078] In the formula, To determine the maximum allowable heat extraction power of the heat exchanger group, we can take... It is 1.1 to 1.3 times that of the previous year, but ground temperature recovery constraints must be met.

[0079] (3) Ground temperature recovery constraints: Within one recovery cycle, the average temperature recovery of the heat exchanger orifice wall is no less than 85%. The recovery rate γ is defined as:

[0080] In the formula, To restore the temperature of the borehole wall, This represents the lowest borehole wall temperature during operation. This represents the original pore wall temperature.

[0081] (4) Compensation for heat source capacity constraints:

[0082] (5) Constraints of the thermal storage device:

[0083]

[0084]

[0085]

[0086] In the formula, To store heat in the heat storage device, For heat dissipation loss rate, and These are the heat storage and heat release efficiencies, respectively. This represents the upper limit of the heat storage capacity.

[0087] The optimization problem can be solved using mixed-integer linear programming, dynamic programming, or genetic algorithms. The solution yields the day-ahead scheduling plan for geothermal heat extraction power, compensation heat source output, and heat storage and release from the thermal storage device for the next 24–72 hours.

[0088] Step S5: Real-time acquisition of outdoor temperature, circulating working fluid return water temperature, user-side supply and return water temperature, and temperature of each hole in the geothermal heat exchange hole group; and feedforward-feedback composite control of circulating pump frequency, geothermal side electric regulating valve, compensation heat source, and heat storage device.

[0089] Feedforward control generates a feedforward control curve based on the 24-hour climate forecast and load prediction, and adjusts the frequency of the geothermal circulating pump and the opening of the electric regulating valve in advance. For example, when the outdoor temperature is predicted to drop by 3°C, the frequency of the circulating pump is increased by 5-10 Hz 2 hours in advance to increase the circulation flow and increase the heat extraction power.

[0090] Feedback control is based on real-time return water temperature deviation. Perform PI adjustment:

[0091]

[0092] In the formula, Set the return water temperature. To measure the return water temperature, and These are the parameters for the PI controller.

[0093] When the outdoor temperature prediction deviation exceeds a set threshold (e.g., 2°C), Model Predictive Control (MPC) rolling optimization is triggered. MPC uses the current measured conditions as initial conditions, with a rolling optimization time domain of 4–8 hours, a control step size of 10–30 minutes, and the objective function being the minimum weighted sum of the squares of heating deviations and operating costs over the time domain. MPC outputs real-time control commands for the circulating pump frequency, electric regulating valve opening, compensation heat source power, and thermal storage device power.

[0094] Step S6: Divide the heat exchange hole group into an operating zone, a recovery zone, and a standby zone. Rotate the zones according to the temperature recovery rate of each hole wall. During low-load periods, use a compensating heat source or renewable energy to inject heat back into the formation to accelerate the recovery of ground temperature.

[0095] Suppose there are N holes in the heat exchanger hole group, and they are divided into groups according to the temperature recovery γ of each hole wall: Operating range: γ is within the normal operating range and undertakes the main heat extraction task; Recovery zone: When γ is below the set lower limit, heat extraction is temporarily stopped, and the heat is replenished by natural formation or active heat replenishment. Standby area: γ has reached above 0.9 and is ready to be put into operation at any time.

[0096] The zone rotation conditions are as follows: when the orifice wall temperature recovery degree γ in the recovery zone reaches 0.9, it is transferred to the standby zone; when the orifice wall temperature in the operating zone is lower than the minimum allowable orifice wall temperature for that layer, it is transferred to the standby zone. It is switched out to the recovery zone; the standby zone is put into operation when the heat extraction capacity of the operating zone is insufficient.

[0097] During low-load periods (such as nighttime or transitional seasons), solar thermal collectors, air-source heat pumps, or industrial waste heat are used to heat the circulating working fluid to 35–60°C. This heat is then supplied to the formation via a coaxial tube heat exchanger to accelerate the recovery of the borehole wall temperature. The reinjection heat power is determined based on the borehole wall temperature in the recovery zone and the formation's thermal response characteristics, and generally does not exceed 50%–80% of the normal heat extraction power of the borehole.

[0098] Step S7: Update the parameters of the unsteady heat transfer model and load prediction model online using historical operating data and real-time monitoring data.

[0099] Due to the uncertainty of geological parameters and the potential for changes in formation thermal properties with temperature and time, online updates of model parameters are necessary. This invention employs extended Kalman filtering or particle filtering, using the circulating working fluid outlet temperature error as the observed value, to update the formation's equivalent thermal conductivity, volumetric heat capacity, and borehole thermal resistance.

[0100] The state-space model is as follows:

[0101]

[0102]

[0103] In the formula, For the parameter vector to be updated, For process noise, To measure the outlet temperature of the circulating working fluid, Calculate the outlet temperature for the model. For measuring noise.

[0104] Extended Kalman filter update steps:

[0105]

[0106]

[0107] In the formula, For the observation matrix, To measure the noise covariance, To estimate the error covariance.

[0108] The parameters of the extended Kalman filter are initialized as follows: process noise covariance Take 1% to 5% of the initial parameter values ​​to construct a diagonal matrix; measure the noise covariance. Take the square of the standard deviation of the circulating working fluid outlet temperature measurement; initial error covariance matrix. The squares of the initial standard deviations of the parameters are used to construct a diagonal matrix.

[0109] The update cycle is 24 hours, or an update is triggered immediately when the prediction error exceeds twice the threshold for consecutive periods.

[0110] The present invention will be further described in detail below through specific embodiments. These embodiments are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0111] Example 1: A certain industrial park has a heating area of ​​100,000 square meters. The geological conditions are sandstone with a thermal conductivity of [missing information]. The geothermal gradient is 3.1℃ / 100m, the heat exchange borehole depth is 2000m, with a total of 5 heat exchange boreholes. The heat extraction capacity of each borehole is 360kW, and the total geothermal capacity is 800kW. The auxiliary heat sources are an air source heat pump (total heating capacity of 500kW) and a 150m³ hot water storage tank. The local peak-valley electricity price difference is significant, with a peak price of 0.98 yuan / kWh and a valley price of 0.28 yuan / kWh.

[0112] Using the method of this invention, the optimization objective in step S4 focuses on time-of-use electricity pricing. Optimization results show that during off-peak hours (23:00–7:00), the geothermal heat extraction power remains at 600kW, the air source heat pump operates on off-peak electricity and stores heat, and the hot water storage tank is full; during peak hours (8:00–11:00, 18:00–22:00), the geothermal heat extraction power increases to 750kW, the hot water storage tank releases heat, and the air source heat pump stops operating; during off-peak hours, adjustments are made flexibly based on load and electricity price.

[0113] Through climate-adaptive regulation and thermal storage optimization, the system's operating electricity costs are reduced by 32% compared to a strategy without thermal storage. The outlet temperature of the geothermal heat exchanger holes drops by only 1.8℃ in a heating season, far lower than the 4.5℃ drop during continuous full-load operation.

[0114] Example 2: Medium-deep geothermal energy + cooling tower, heating and cooling A residential project located in the International Port Area has a total construction area of ​​134,800 square meters, comprising 10 residential buildings, a property management office building, a kindergarten, and a waste treatment plant, housing approximately 1,600 households. The heating and cooling system utilizes medium-deep geothermal technology, employing a "heat extraction without water extraction" approach and a "closed-loop, non-interference under-hole heat exchange" process. Only six medium-deep heat exchange holes are drilled within the complex, without connection to the municipal pipeline network, allowing for independent operation within the project. The system is equipped with integrated geothermal energy supply units, with radiant floor heating for terminal heating and fan coil units for cooling.

[0115] The method of this invention is used for heating and cooling regulation. In step S1, local weather forecast data is accessed to obtain parameters such as outdoor dry-bulb temperature, solar radiation, and relative humidity, while simultaneously predicting the building's heating and cooling loads. Since the system needs to consider both winter heating and summer cooling conditions, the load prediction model needs to establish physical models and data-driven models for heating and cooling modes respectively. The weight α of the physical model in heating mode is set to 0.6–0.7, while the weight of the data-driven model in cooling mode is appropriately increased to better capture the impact of solar radiation and indoor thermal disturbance on the cooling load.

[0116] Step S2 establishes an unsteady heat transfer model for a group of six medium-deep heat exchange wells. The geothermal gradient in this area is approximately 3.0℃ / 100m, the well depth is approximately 2000~2100m, and the initial geothermal temperature at the well bottom is approximately 75℃. The strata are discretized using the finite difference method, with a radial computational radius of 35m and a grid size of 90. Axial discretization is performed according to geological strata, with each layer having a grid length of 15m. Formation thermal property temperature correction factors are applied. Take 0.001 / ℃, We take 0.0005 / ℃. According to the model calculation, after the heat pump unit boosts the heat exchange holes, the total geothermal heat extraction capacity of the six holes is approximately 3200~3600kW.

[0117] Step S3: Determine the sustainable geothermal heat extraction threshold. The allowable load is 860kW (with a safety factor of 1.3). Since the project does not include any additional peak-shaving auxiliary heat sources such as gas-fired or electric boilers, the compensation heat load is entirely borne by the peak-shaving function of the variable frequency system. When weather forecasts indicate extreme cold weather, the compensation heat load increases. The variable frequency system then increases the geothermal circulation flow and the compressor frequency of the heat pump unit to achieve tiered peak-shaving.

[0118] Step S4 involves day-ahead scheduling with the goal of minimizing daily operating costs. Since the system has no other primary energy supplementation, the optimization variables are mainly geothermal heat extraction power and circulation pump frequency. During extreme cold weather warnings, the optimized scheduling plan automatically increases geothermal heat extraction power to 1.2 times the sustainable heat extraction threshold, utilizing the thermal inertia of the strata for short-term overload heat extraction, while ensuring that the ground temperature recovery rate during the recovery period is not less than 85%.

[0119] In step S5, the feedforward-feedback composite control system adjusts its operating parameters in advance based on climate forecast data. When the outdoor temperature is predicted to drop by more than 5°C in the next 24 hours, the circulation pump frequency and compressor frequency are adjusted in stages and increments 4 hours in advance to achieve rapid response. The feedback control performs PI correction based on the return water temperature deviation on the user side to maintain stable supply and return water temperatures under heating and cooling conditions.

[0120] In step S6, the six heat exchange orifices are divided into an operating zone (4 orifices) and a recovery zone (2 orifices) during the heating season, and the zones are readjusted according to the cooling load demand during the cooling season. During the low-load period of the transition season, heat is reinjected into the ground using the heat discharged from the cooling tower to replenish the temperature to 38°C, with a reinjection heat power of approximately 60kW, accelerating the recovery of the heat exchange orifice wall temperature. The alternating operation between the heating and cooling seasons allows the ground to obtain heat reinjection compensation through the heat discharged from the cooling tower during the cooling season, effectively mitigating the ground temperature decay throughout the year.

[0121] After the project was implemented, the heat pump unit achieved a coefficient of performance (COP) of 7.80 and a system COP of 6.46 under the condition of condensate-side water supply temperature of 45℃ and evaporator-side outlet water temperature of 20℃. It can replace 2,720 tons of coal annually, reducing gas consumption by approximately 1 million m³. After a full heating and cooling season, the outlet temperature of the heat exchanger holes only decreased by 1.5℃, far below the expected attenuation during continuous full-load operation. Annual operating costs can be saved by approximately 1.5 million yuan.

[0122] Example 3: Medium-deep geothermal energy + cooling tower for heating, cooling and domestic hot water supply A university student living area energy supply project is located in Xixian New Area, with a total construction area of ​​294,600 square meters. It comprises 23 main buildings, including dormitories, supporting commercial facilities, a canteen, a student supermarket, and a gym, with 7,541 rooms. Utilizing medium-deep geothermal heating technology, the project features 17 heat exchange holes and 7 medium-deep geothermal units, providing heating, cooling, and domestic hot water services for the entire project. It commenced operation in September 2024, providing 24-hour hot water service to the apartments and cooling service to the canteen for nearly 10,000 faculty and students on campus. The project also achieved its first year of clean heating using medium-deep geothermal energy during the 2024-2025 heating season.

[0123] The method of this invention is used for integrated regulation of heating, cooling, and domestic hot water. In step S1, since the project simultaneously has three loads—heating, cooling, and domestic hot water—the building load forecasting adopts a sub-item forecasting method, modeling the building heating load, air conditioning cooling load, and domestic hot water load separately. The domestic hot water load forecasting uses a data-driven model, performing time series forecasting based on students' daily routines, holiday schedules, and historical hot water consumption data. The physical model weight α for hot water load is set to 0.1–0.2, with the data-driven model as the primary driver.

[0124] Step S2 establishes an unsteady-state heat transfer model for a group of 17 heat exchange holes. The geothermal gradient in this area is approximately 3.1℃ / 100m, and the depth of the heat exchange holes is approximately 2000m. Due to the large number of holes, the model needs to consider the thermal interference effect between the holes. A radial calculation radius of 50m is used, and adjacent heat exchange holes are included in the same calculation domain. The thermal interference between holes is handled by the superposition principle. According to the model calculation, the total geothermal heat extraction capacity of the 17 holes is approximately 7000~8000kW.

[0125] Step S3: Determine the sustainable geothermal heat extraction threshold. The allowable power is 2400kW (with a safety factor of 1.3). Compensation for heat load occurs during extreme winter weather and peak summer cooling periods. The system is equipped with cooling towers to handle heat dissipation during cooling conditions. During low-load periods, the dissipated heat is reinjected into the ground through heat exchange vents, forming a cross-seasonal heat storage cycle of "winter heat extraction – summer reinjection".

[0126] In step S4, the optimization scheduling aims to minimize the total annual operating cost, taking into account the different load structures of the heating season, cooling season, and transitional season. Domestic hot water load exists year-round; optimized scheduling prioritizes utilizing the geothermal base load to meet hot water demand. When the heating and cooling season loads overlap, wide-range adjustment of the variable frequency heat pump unit adapts to load changes. The hot water system adopts a main and auxiliary tiered water tank design. The main water tank and two auxiliary water tanks are put into operation in stages according to actual hot water usage, reducing heat loss caused by hot water not being used promptly after production.

[0127] In step S5, the feedforward-feedback composite control system ensures that the heat pump unit, with its wide-range heat source inlet water temperature and high evaporation temperature, maintains efficient operation even when the evaporator outlet water temperature is 20°C, adapting to seasonal fluctuations in geothermal working fluid temperature. The feedforward control adjusts the energy supply mode in advance based on weather forecasts, performing system pre-adjustment 48 hours before the switch between heating and cooling seasons.

[0128] In step S6, the 17 heat exchange orifices are divided into a heating operation zone, a cooling reinjection zone, and a standby recovery zone. During the heating season, heat is primarily extracted from the operation zone. During the cooling season, heat exhausted from the cooling tower is reinjected into the ground through some of the heat exchange orifices, supplementing the temperature by 40°C with a reinjection power of approximately 300kW, thus achieving cross-seasonal heat compensation. The primary side piping network is designed with the heat exchange orifices grouped and aligned with the main pipeline to ensure uniform flow distribution at each heat exchange orifice, thereby improving overall heat exchange efficiency.

[0129] After its implementation, the project provided stable heating, cooling and domestic hot water services for 294,600 square meters of buildings, providing an effective large-scale application practice model for alleviating the shortage of gas supply in the city during winter and solving the problem of insufficient clean heating heat sources.

[0130] Example 4: Medium-deep geothermal heating, single heating The total construction area of ​​a certain heating service project is approximately 457,800 square meters, of which the first phase has a total construction area of ​​265,600 square meters and a heating area of ​​201,500 square meters. All residential buildings are high-rise, while the supporting public buildings are multi-story. The project utilizes medium-deep geothermal non-intrusive clean heating technology. The clean heating system consists of four parts: a heat source system, a heating machine room, a heating pipeline network, and an intelligent management and control platform. The heat source system is designed with 12 deep heat exchange holes and is equipped with 12 heat exchange systems. The heating machine room is equipped with 5 medium-deep geothermal units, 3 in the low-zone and 2 in the high-zone, with a machine room area of ​​approximately 240 square meters.

[0131] The method of this invention is used for heating regulation. In step S1, numerical weather prediction data from the meteorological bureau is accessed to obtain outdoor dry-bulb temperature and solar radiation data for the next 24–72 hours. Building heat load prediction uses a weighted approach of a physical model and a data-driven model, with the physical model weight α ranging from 0.6 to 0.7. Since this project involves a large heating area and consists of high-rise buildings, the load prediction model is established in separate low-rise and high-rise zones to predict the hourly heat load for each zone.

[0132] Step S2 establishes an unsteady-state heat transfer model for a group of 12 heat exchange wells. The geothermal gradient in this area is approximately 3.0℃ / 100m, the well depth is approximately 2000~2100m, and the initial geothermal temperature at the well bottom is approximately 75℃. Due to the large number of wells and their relatively concentrated layout, the radial calculation radius of the model is taken as 60m, and all 12 wells are included in the same computational domain, considering inter-well thermal interference. According to the model calculation, the total geothermal extraction capacity of the 12 wells is approximately 5000~6000kW.

[0133] Step S3 determines the sustainable geothermal heat extraction threshold P_geo,allow to be 1900kW (with a safety factor of 1.3). Since the total heat load of the project is approximately 8000kW, the sustainable geothermal heat extraction power is far lower than the peak heat load. The compensation heat load is mainly borne by the heat pump unit extracting heat from the geothermal working fluid. The geothermal circulating working fluid enters the evaporator of the heat pump unit, where the heat pump unit enhances the low-grade heat in the working fluid before supplying it to the heating system. Therefore, the actual heating capacity can reach 8000kW.

[0134] In step S4, the optimization scheduling aims to minimize operating electricity costs, taking into account time-of-use pricing, and optimizes the start-up and shutdown combinations and load allocation of each heat pump unit. Three units are configured in the low-load zone, and two units are configured in the high-load zone. The optimal combination of units is used to match different load rates. During low-load periods, the number of operating units is reduced, and the load rate of each unit is increased to ensure the units operate in their high-efficiency zones; during peak load periods, all units are put into operation.

[0135] In step S5, the feedforward-feedback composite control adjusts the number of operating units and the geothermal circulation flow rate in advance based on climate forecasts. When a cold wave is forecast, one additional unit is started 6 hours in advance, and the frequency of the geothermal circulation pump is increased, increasing the geothermal working fluid flow rate by 20% to ensure sufficient heating capacity. Feedback control performs PI regulation based on the return water temperature deviation in high and low zones to maintain heating balance in each zone.

[0136] In step S6, the 12 heat exchange holes are divided into an operating zone (8 holes) and a recovery zone (4 holes), rotating every two weeks. The heat exchange holes in the recovery zone rely on natural ground recovery and heat diffusion from the surrounding operating holes to restore their temperature. The energy management platform analyzes key data in real time through a data acquisition and analysis system, adjusts operating strategies based on load trends, and achieves unattended operation and remote management.

[0137] After the project's implementation, the coefficient of performance (COP) of the medium-deep geothermal units will reach over 7.0, and the system's energy efficiency will be more than 50% higher than that of shallow buried pipe heat pumps. The operating cost for heating units will not exceed 3 yuan / ㎡ / month, significantly lower than the 5.8 yuan / ㎡ / month operating cost of traditional coal-fired boilers. Over a four-month heating season, the overall annual heating operating cost will be approximately 3 million yuan lower than that of traditional coal-fired boilers. This project does not use primary energy sources such as coal or natural gas, consuming only a small amount of electricity, thus achieving clean and low-carbon heating.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A climate-adaptive, mid-deep, closed-loop geothermal heating compensation and regulation method, characterized in that, Includes the following steps: S1. Obtain climate forecast data and building heat load forecast data for the target heating area during the future forecast period, as well as the geological parameters and operating parameters of the medium-deep closed heat exchange hole group. S2. Establish an unsteady heat transfer model for a group of medium-deep closed heat extraction and heat exchange holes, and calculate the soil and rock temperature field, hole wall temperature and circulating working fluid outlet temperature under different heat extraction power and intermittent operation conditions. S3. Determine the sustainable geothermal heat extraction threshold based on geological parameters and geothermal recovery characteristics, and determine the compensation heat load for each time period within the forecast period based on climate forecast data; wherein, the sustainable geothermal heat extraction threshold is determined according to the following formula: In the formula, Let be the thermal conductivity of the soil and rock in the i-th geological layer, in units of . ; ,i is the original geothermal temperature of the i-th layer, in °C; T_min,i is the minimum allowable borehole wall temperature of the i-th layer, in °C; The equivalent thermal resistance of the i-th layer is defined as the radial thermal resistance per unit length of the i-th geological layer, with units of m·K / W, and is calculated based on the radial heat transfer equation and the thermal resistance of the borehole tube for that layer; SF is the safety factor, with a value ranging from 1.2 to 1.

5. S4. With the goal of minimizing the total system operating cost during the predicted period, and using geothermal heat extraction power, compensation heat source power, and thermal storage device power as optimization variables, the day-ahead scheduling plan is obtained by satisfying the constraints of heat load balance, geothermal heat extraction capacity, ground temperature recovery, and compensation heat source capacity. The total system operating cost includes electricity cost, fuel cost, and carbon emission cost under time-of-use pricing. S5. Real-time acquisition of outdoor temperature, circulating working fluid return water temperature, user-side supply and return water temperature and temperature of each hole in the geothermal heat exchange hole group, and feedforward-feedback composite control of circulating pump frequency, geothermal side electric regulating valve, compensation heat source and heat storage device. S6. Divide the heat exchange pore group into an operating zone, a recovery zone, and a standby zone. Rotate zones according to the temperature recovery rate of each pore wall. During low-load periods, use a compensating heat source or renewable energy to reinject heat into the formation to accelerate ground temperature recovery. The recovery rate γ is defined as: In the formula, To restore the borehole wall temperature, T_min is the lowest borehole wall temperature during operation. This represents the original borehole wall temperature. The conditions for the zone rotation are as follows: when the temperature recovery degree γ of the hole wall in the recovery zone reaches 0.9, it is transferred to the standby zone; when the hole wall temperature in the operating zone is lower than the minimum allowable hole wall temperature for that layer. When i, it is switched out to the recovery zone; the standby zone is put into operation when the heat extraction capacity of the operating zone is insufficient. The heat reinjection medium is a circulating working fluid heated by solar energy collection, air source heat pump, or industrial waste heat, with a replenishment temperature of 35-60℃. S7. Update the parameters of the unsteady heat transfer model and load prediction model online using historical operating data and real-time monitoring data; The compensating heat source is an auxiliary heat source coupled to the geothermal system, selected from at least one of a gas boiler, an electric boiler, an air source heat pump, a solar collector, or an industrial waste heat exchanger.

2. The climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S1, the climate forecast data includes outdoor dry-bulb temperature, relative humidity, solar radiation, wind speed, and cloud cover; the building heat load forecast data is obtained by weighting a physical model and a data-driven model, wherein the physical model adopts the equivalent full load hours method, and the data-driven model adopts a multiple regression or neural network model based on historical meteorological data and heat load data, and the weighting coefficients are dynamically adjusted according to the forecast lead time and the historical forecast error of the model.

3. The climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S2, the unsteady heat transfer model uses the finite difference method to discretize the coaxial tube heat exchanger, dividing the formation radially into a near-hole zone, a transition zone, and a far-hole zone, and discretizing the axial direction according to geological stratification, taking into account groundwater seepage and changes in formation thermal properties with temperature; the circulating working fluid in the inner and outer tubes and annular cavity of the coaxial tube heat exchanger is described by a one-dimensional convective heat transfer equation, which is solved by coupling the thermal resistance of the tube with the formation heat transfer equation; The formation thermal properties change with temperature using the following linear correction relationship: In the formula, ,ref and ,ref represents the reference temperature of the i-th layer. Thermal conductivity and volumetric heat capacity at i; This is the temperature correction factor for thermal conductivity, with a value ranging from -0.002 to 0.003 / ℃. This is the volumetric heat capacity temperature correction factor, with a value range of -0.001 to 0.002 / ℃.

4. The climate-adaptive, mid-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S3, the compensated heat load is the difference between the building heat load and the sustainable geothermal heat extraction power during the predicted period: In the formula, , Predict the building heat load at time t. This refers to the system's thermal efficiency.

5. The climate-adaptive, mid-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S4, the ground temperature recovery constraint is: within one recovery cycle, the average temperature recovery rate of the heat exchange orifice wall is not less than 85%; the mapping relationship between the total power consumption and fuel consumption of the system and the optimization variables in the optimization objective is: In the formula, The power consumption of the circulating pump is proportional to the cube of the geothermal circulation flow rate. The power consumption of an air source heat pump is equal to the heat pump's heating capacity divided by its coefficient of performance (COP). ; Electricity consumption of an electric boiler is equal to the boiler's heating capacity divided by its efficiency. ; Powering the gas-fired boiler LHV represents the lower heating value of the gas-fired boiler.

6. The climate-adaptive, mid-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S5, the feedforward-feedback composite control specifically involves: generating a feedforward control curve based on the 24-hour climate forecast and load prediction; and adjusting the real-time return water temperature deviation... PI feedback correction is performed; when the outdoor temperature prediction deviation exceeds the set threshold, the model predictive control rolling optimization is triggered. The rolling optimization time domain is 4 to 8 hours, and the control step size is 10 to 30 minutes.

7. The climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S6, the heat power of the heat reinjection does not exceed 50% to 80% of the normal heat extraction power of the hole.

8. The climate-adaptive, medium-deep, closed-loop geothermal heating compensation and regulation method according to claim 1, characterized in that, In step S7, the online parameter update adopts extended Kalman filtering or particle filtering, and uses the circulating working fluid outlet temperature error as the observed value to update the formation equivalent thermal conductivity, volumetric heat capacity and orifice thermal resistance. The update cycle is 24 hours or is triggered when the prediction error continuously exceeds twice the threshold. In the extended Kalman filter, the process noise covariance Take 1% to 5% of the initial parameter values ​​to construct a diagonal matrix; measure the noise covariance. Take the square of the standard deviation of the circulating working fluid outlet temperature measurement; initial error covariance matrix. The squares of the initial standard deviations of the parameters are used to construct a diagonal matrix.

9. A climate-adaptive, mid-deep, closed-loop geothermal heating compensation and control system, used to implement the method described in any one of claims 1 to 8, characterized in that, include: The meteorological data acquisition module is used to acquire climate forecast data for the target heating area during the future prediction period; The load forecasting module is used to generate building heat load forecasting data based on climate forecast data, building thermal parameters, and historical heat consumption data; The geothermal heat transfer model module is used to establish an unsteady heat transfer model of a group of medium-deep closed heat extraction and exchange holes, and to calculate the temperature field of the soil and rock, the hole wall temperature and the outlet temperature of the circulating working fluid. The optimization scheduling module is used to solve the day-ahead scheduling plan for geothermal heat extraction power, compensation heat source power, and thermal storage device power with the goal of minimizing the total system operating cost within the predicted period; the total system operating cost includes electricity cost, fuel cost, and carbon emission cost under time-of-use pricing. The real-time control module is used to collect outdoor temperature, circulating working fluid return water temperature, user-side supply and return water temperature and temperature of each hole in the geothermal heat exchange hole group in real time, and to perform feedforward-feedback composite regulation of circulating pump frequency, geothermal side electric regulating valve, compensation heat source and heat storage device. The zone rotation management module is used to divide the heat exchanger orifice group into an operating zone, a recovery zone, and a standby zone, and to perform zone rotation based on the temperature recovery degree of each orifice wall, and control the heat reinjection during low-load periods; the recovery degree γ is defined as... ,in To restore the temperature of the borehole wall, This represents the lowest borehole wall temperature during operation. The original borehole wall temperature is used for the zone rotation. When the borehole wall temperature recovery rate γ in the recovery zone reaches 0.9, the zone is switched to the standby zone. When the borehole wall temperature in the operating zone is lower than the minimum allowable borehole wall temperature, the zone is switched to the recovery zone. The standby zone is put into operation when the heat extraction capacity of the operating zone is insufficient. The heat reinjection medium is a circulating working fluid heated by solar collectors, air source heat pumps, or industrial waste heat, with a supplementary temperature of 35-60℃. The data storage and model update module is used to store historical operating data and real-time monitoring data, and to update the parameters of the unsteady heat transfer model and load prediction model online.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the climate-adaptive, medium-deep, closed-loop geothermal heating compensation and control method according to any one of claims 1 to 8.

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