Daily-discharging and night-charging type intelligent energy supply system based on soil coupling energy

Abstract

The invention discloses a daily-discharging and night-charging type intelligent energy supply system based on soil coupling energy, and relates to the technical field of energy supply management. The method comprises the following steps: collecting a geothermal parameter set around a user building through a soil heat exchanger loop, setting strategy adjustment points on an energy supply and discharge time axis, obtaining a matching degree value of each strategy adjustment point, judging whether each strategy adjustment point is executed according to the matching degree value, generating a dynamic energy supply and discharge strategy sequence according to a judgment result, and executing the dynamic energy supply and discharge strategy sequence. A three-dimensional thermophysical property distribution diagram is established according to spatial position distribution of a soil heat exchanger loop, a geothermal parameter set is mapped to the three-dimensional thermophysical property distribution diagram, then the geothermal parameter set is corrected, a thermal response model is established according to the three-dimensional thermophysical property distribution diagram, the thermal response model is divided into a plurality of energy supply and release areas, and the energy supply and release areas are subjected to thermal response. An energy supply and discharge time axis is established, time-of-use electricity price information is obtained, and then window periods and load prediction curves are set for all energy supply and discharge areas on the energy supply and discharge time axis.

Description

Technical Field

[0001] This invention relates to the field of energy management technology, specifically to a day-to-night intelligent energy supply system based on soil-coupled energy. Background Technology

[0002] In today's society, energy issues have increasingly become a global focus. With the rapid development of the construction industry, building energy consumption accounts for a growing proportion of total social energy consumption. Traditional energy supply systems largely rely on fossil fuels, causing not only serious environmental pollution but also facing the crisis of energy depletion. Therefore, developing and utilizing renewable energy sources to achieve efficient and green energy supply in buildings has become a current research hotspot.

[0003] Soil energy, as an abundant, stable, and renewable energy source, has enormous development potential. Soil-coupled energy systems are a novel energy utilization method that utilizes shallow underground geothermal resources for heating and cooling. They offer advantages such as energy saving, environmental protection, and high efficiency. However, existing soil-coupled energy supply systems have some shortcomings.

[0004] On the one hand, the lack of effective intelligent management and control mechanisms makes it difficult to make flexible adjustments based on the actual needs of users and the dynamic changes in soil energy, resulting in low energy utilization efficiency. For example, it is not possible to accurately arrange energy supply and release according to the energy demand and soil geothermal parameters at different times, which may lead to energy waste or insufficient supply.

[0005] On the other hand, the management of soil energy fields is not precise enough, making it difficult to accurately acquire and analyze geothermal parameters around soil heat exchangers, and hindering dynamic optimization of energy supply strategies based on these parameters. Furthermore, in terms of multi-source energy coupling, there is a lack of effective integration of different energy sources working together, failing to fully leverage the advantages of multi-source energy. In addition, the existing system's interaction with users is inadequate, unable to formulate reasonable energy supply strategies based on users' personalized needs and time-of-use pricing information. Therefore, this paper proposes a day-to-night intelligent energy supply system based on soil-coupled energy. Summary of the Invention

[0006] The purpose of this invention is to provide a daytime-discharge and nighttime-charge intelligent energy supply system based on soil-coupled energy, in order to solve the problems in the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A day-to-night intelligent energy supply system based on soil-coupled energy includes an intelligent cloud control platform, which is communicatively connected to a user interaction strategy management terminal and an energy station operation and maintenance terminal. The energy station operation and maintenance terminal is equipped with a soil energy field management module and a multi-source coupled energy supply module; The soil energy field management module is used to set up a soil heat exchanger loop, collect geothermal parameter sets around the user's building through the soil heat exchanger loop, set strategy adjustment points on the energy supply and release time axis from the user interaction strategy management terminal, obtain the matching degree value of each strategy adjustment point, and then determine whether each strategy adjustment point should be executed based on the matching degree value. Based on the judgment result, a dynamic energy supply and release strategy sequence is generated and executed. The multi-source coupled power supply module is used to establish a three-dimensional thermal property distribution map based on the spatial location distribution of the soil heat exchanger circuit, map the geothermal parameter set onto the three-dimensional thermal property distribution map, and then correct the geothermal parameter set. The user interaction strategy management terminal is used to establish a thermal response model based on the three-dimensional thermal property distribution map, divide the thermal response model into multiple energy supply and release regions, establish an energy supply and release time axis and obtain time-of-use electricity price information, and then set window periods and load forecast curves for each energy supply and release region on the energy supply and release time axis.

[0008] Furthermore, users upload energy preference information and building information to the user interaction strategy management terminal and the energy station operation and maintenance terminal. The building information includes building envelope characteristics, pipeline distribution information, geographical coordinates and energy supply area. The energy preference signal includes desired temperature range, work and rest time and cost-sensitive interval.

[0009] Furthermore, the process of acquiring the geothermal parameter set includes: The location of the user's building is determined by the geographic coordinates of the building information, and n parallel soil heat exchanger loops are set up around the user's building. Each soil heat exchanger loop is equipped with a temperature sensor and a flow sensor, and forms an independent energy harvesting unit, where n is a natural number greater than or equal to 4. Then, each soil heat exchanger loop works in concert to collect the initial temperature distribution and thermal property parameters of the soil energy field as a geothermal parameter set; Once the geothermal parameter set acquisition is completed, the soil energy field management module collects the geothermal parameter sets acquired from each soil heat exchanger loop.

[0010] Furthermore, the process of establishing the three-dimensional thermal property distribution map includes: A three-dimensional thermal property distribution map of the soil energy field is established. The geothermal parameter sets collected by each soil heat exchanger loop are mapped onto the three-dimensional thermal property distribution map according to the location of each soil heat exchanger loop. All temperature data are standardized and temperature difference thresholds are set. The three-dimensional thermal property distribution map sets n data display points according to the spatial location distribution of the soil heat exchanger circuit. Then, based on the geothermal parameter set collected by the soil heat exchanger circuit and the data collection range, the initial temperature distribution of the geothermal parameter set is distributed in the form of thermal ripples on the three-dimensional thermal property distribution map, so that the spatial location associated with the same thermal ripple in the three-dimensional thermal property distribution map corresponds to the same temperature value. Determine the relationship between the temperature difference and the temperature difference threshold between adjacent data display points in the three-dimensional thermal property distribution map. Based on the determination result, mark the scene area associated with the data perception range of the corresponding data display point as a thermal property anomaly area, and treat the data display point as measurement noise for smoothing and filtering. After all data display points have been judged, a short-term enhanced heat transfer test is conducted on the soil heat exchanger loops around the scene area marked as an abnormal thermal property zone.

[0011] Furthermore, the short-time enhanced heat transfer test includes: Retrieve the soil heat exchanger circuit associated with the scene area marked as a thermal property anomaly area, and according to the distribution location of the thermal property anomaly area in the three-dimensional thermal property distribution map, retrieve the three-dimensional thermal property distribution map area that is not in the thermal property anomaly area within the data sensing range of the soil heat exchanger circuit associated with the thermal property anomaly area and record it as the control area. Obtain the average temperature of the area based on the thermal pattern distribution in the control area, that is, accumulate the temperature values ​​corresponding to each thermal pattern and take the average value. Then, circulating liquid with temperatures lower and higher than the regional average temperature was injected into the soil heat exchanger circuit, and a heat exchange test cycle was set. Then, the temperature response curve of the soil heat exchanger circuit was collected under m heat exchange test cycles, where m is a natural number greater than 50. Simultaneously, the control temperature change curves of the control area under each heat exchange test cycle are obtained. The control temperature change curves and temperature response curves under each heat exchange test cycle are mapped onto the same two-dimensional coordinate system. Correction parameters are set for the temperature response curve and iterated so that the temperature values ​​on the temperature response curve are iterated with the correction parameters until the temperature response curve overlaps with the control temperature change curve to the greatest extent. The average value of the correction parameters under each heat exchange test cycle is recorded as the temperature correction parameter for the corresponding thermal property anomaly zone. Then, in the subsequent update of the three-dimensional thermal property distribution map, the temperature data collected by the soil heat exchanger loop is automatically corrected by the temperature correction parameter.

[0012] Furthermore, the process of establishing the thermal response model includes: The user interaction strategy management terminal establishes a thermal response model based on the three-dimensional thermal property distribution map and building information. The thermal response model includes a building image model established based on the characteristics of the building envelope, pipeline distribution information and energy supply area. The building image model is divided into multiple energy supply and release areas according to energy preference information, and the three-dimensional thermal property distribution map is covered on the model display area according to the spatial distribution. A time axis for energy supply and release is set for each energy supply and release area. Based on the expected temperature range, work and rest time and cost-sensitive interval in the energy consumption preference information, the expected load of the energy supply and release area is marked and marked on the energy supply and release time axis in chronological order. The expected load of each time node on each energy supply and release time axis is statistically analyzed to obtain the load prediction curve. By obtaining time-of-use electricity price information via the internet, multiple economic charging and releasing windows are marked on the energy supply and release timeline. At the same time, based on the cost-sensitive range set by the user, corresponding strategy priorities are set for each window.

[0013] Furthermore, the process of obtaining the matching degree value of the strategy adjustment point includes: Based on the load forecast curve, several strategy adjustment points are set on the power supply and release time axis, and each strategy adjustment point contains a power supply and release strategy. And based on the strategy priority associated with each strategy adjustment point, a strategy weight is set for each strategy adjustment point. According to the priority of the window period from high to low, the strategy weight of the corresponding strategy adjustment point decreases sequentially. Starting from the first strategy adjustment point in chronological order, obtain the matching degree value γ between each strategy adjustment point and the current building state.

[0014] Furthermore, the generation process of the dynamic energy supply and release strategy sequence includes: Set a policy switching threshold and check in real time whether the matching degree value γ is greater than or equal to the policy switching threshold. If it is greater than or equal to the threshold, the policy switching is triggered; otherwise, no action is taken. If a conflict is predicted between the power supply and release strategies at different strategy adjustment points, the matching degree value γ of the conflicting strategies is compared. The strategy adjustment point with a smaller γ value will temporarily suspend the strategy switching or select the suboptimal strategy option. The strategy adjustment point with a larger γ value is recorded as a valid strategy adjustment point until the strategy conflict is resolved. Based on each effective strategy adjustment point, a corresponding dynamic energy supply and release strategy sequence is generated, and then the energy station operation and maintenance terminal sends the dynamic energy supply and release strategy sequence to each energy supply and release device for execution. During the operation of the dynamic energy supply strategy sequence, the thermal response model is continuously updated. Then, after each heat exchange test cycle, the load forecast curve and the window period on the energy supply and release time axis are updated in a rolling manner based on the thermal response model and real-time electricity price, and the dynamic energy supply and release strategy sequence is updated synchronously.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention generates a dynamic energy supply and release strategy sequence by setting strategy adjustment points on the energy supply and release time axis and determining whether to execute based on the matching degree value. This enables flexible adjustment of energy supply and release strategies according to real-time changes in soil energy and actual user needs, thereby improving energy utilization efficiency and effectively avoiding energy waste.

[0016] 2. This invention establishes a thermal response model based on a three-dimensional thermal property distribution map, divides it into multiple energy supply and release zones, and combines time-of-use electricity price information to set window periods and load forecast curves for each energy supply and release zone on the energy supply and release time axis. Thus, while taking into account the user's personalized needs and the impact of time-of-use electricity prices, it can formulate a more economical and reasonable energy supply strategy for users. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a system framework diagram of a day-to-night intelligent energy supply system based on soil-coupled energy, as described in this invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 As shown, a day-to-night intelligent energy supply system based on soil-coupled energy includes an intelligent cloud control platform, which is communicatively connected to a user interaction strategy management terminal and an energy station operation and maintenance terminal. The energy station operation and maintenance terminal is equipped with a soil energy field management module and a multi-source coupled energy supply module; The soil energy field management module is used to set up a soil heat exchanger loop, collect geothermal parameter sets around the user's building through the soil heat exchanger loop, set strategy adjustment points on the energy supply and release time axis from the user interaction strategy management terminal, obtain the matching degree value of each strategy adjustment point, and then determine whether each strategy adjustment point should be executed based on the matching degree value. Based on the judgment result, a dynamic energy supply and release strategy sequence is generated and executed. The multi-source coupled power supply module is used to establish a three-dimensional thermal property distribution map based on the spatial location distribution of the soil heat exchanger circuit, map the geothermal parameter set onto the three-dimensional thermal property distribution map, and then correct the geothermal parameter set. The user interaction strategy management terminal is used to establish a thermal response model based on the three-dimensional thermal property distribution map, divide the thermal response model into multiple energy supply and release regions, establish an energy supply and release time axis and obtain time-of-use electricity price information, and then set window periods and load forecast curves for each energy supply and release region on the energy supply and release time axis.

[0021] Furthermore, the working principle of the present invention will be illustrated below through embodiments: Users upload energy consumption preference information and building information to the user interaction strategy management terminal and the energy station operation and maintenance terminal. The building information includes building envelope characteristics, pipeline distribution information, geographical coordinates and energy supply area. The energy consumption preference signal includes the desired temperature range, working and rest time and cost sensitive interval (indicating the range of electricity cost values ​​that the user is willing to accept). It should be noted that the building envelope characteristics refer to the physical properties of the building shell, such as heat transfer coefficient, thermal inertia index, light transmission characteristics, etc. It should be noted that after users upload their energy preference information, they can set the energy supply priority for different building areas (such as bedrooms, living rooms, and office workstations) in the user interaction strategy management. That is, when formulating energy supply strategies, more stable energy supply will be allocated to areas with higher priority. The soil energy field management module in the energy station operation and maintenance terminal locates the user's building location based on the geographical coordinates of the building information, and sets up n parallel-operating soil heat exchanger loops around the user's building. Each soil heat exchanger loop is equipped with a temperature sensor and a flow sensor, and constitutes an independent energy acquisition unit, where n is a natural number greater than or equal to 4. Then, each soil heat exchanger loop works in concert to collect the initial temperature distribution and thermal property parameters (thermal conductivity, volumetric specific heat capacity, etc.) of the soil energy field as a geothermal parameter set; Once the geothermal parameter set acquisition is completed, the soil energy field management module collects the geothermal parameter sets collected from each soil heat exchanger loop and sends them to the multi-source coupled energy supply module. Because of the spatial heterogeneity of the soil energy field, that is, the soil quality varies at different spatial locations, the first geothermal parameters collected by the soil heat exchanger loops at adjacent locations will have some differences. Then, the multi-source coupled energy supply module establishes a three-dimensional thermal property distribution map of the soil energy field, maps the geothermal parameter set collected by each soil heat exchanger loop onto the three-dimensional thermal property distribution map according to the location of each soil heat exchanger loop, standardizes all temperature data, and sets temperature difference thresholds. The three-dimensional thermal property distribution map sets n data display points according to the spatial location distribution of the soil heat exchanger circuit. Then, based on the geothermal parameter set collected by the soil heat exchanger circuit and the data collection range, the initial temperature distribution of the geothermal parameter set is distributed in the form of thermal ripples on the three-dimensional thermal property distribution map, so that the spatial location associated with the same thermal ripple in the three-dimensional thermal property distribution map corresponds to the same temperature value. Determine the relationship between the temperature difference and the temperature difference threshold between adjacent data display points in a three-dimensional thermal property distribution map. If the temperature difference is less than or equal to the threshold, no action is taken; If the temperature difference is greater than the threshold, it is determined whether the adjacent data display points of the corresponding data display point have the same size relationship. If so, the scene area associated with the data perception range of the corresponding data display point is marked as a thermal property anomaly area, and the data display point is regarded as measurement noise and smoothed and filtered. After all data display points have been judged, a short-term enhanced heat transfer test is conducted on the soil heat exchanger loops around the scene area marked as an abnormal thermal property zone. The short-time enhanced heat transfer test includes: Retrieve the soil heat exchanger circuit associated with the scene area marked as a thermal property anomaly area, and according to the distribution location of the thermal property anomaly area in the three-dimensional thermal property distribution map, retrieve the three-dimensional thermal property distribution map area that is not in the thermal property anomaly area within the data sensing range of the soil heat exchanger circuit associated with the thermal property anomaly area and record it as the control area. Obtain the average temperature of the area based on the thermal pattern distribution in the control area, that is, accumulate the temperature values ​​corresponding to each thermal pattern and take the average value. Then, circulating liquid with temperatures lower and higher than the regional average temperature is injected into the soil heat exchanger circuit, and a heat exchange test cycle (usually tens of minutes to several hours) is set. Then, the temperature response curve of the soil heat exchanger circuit under m heat exchange test cycles is collected, where m is a natural number greater than 50. Simultaneously, the control temperature change curves of the control area under each heat exchange test cycle are obtained. The control temperature change curves and temperature response curves under each heat exchange test cycle are mapped onto the same two-dimensional coordinate system. Correction parameters are set for the temperature response curve and iterated so that the temperature values ​​on the temperature response curve are iterated with the correction parameters until the temperature response curve overlaps with the control temperature change curve to the greatest extent. The average value of the correction parameters under each heat exchange test cycle is recorded as the temperature correction parameter for the corresponding thermal property anomaly zone. Then, in the subsequent process of updating the three-dimensional thermal property distribution map, the temperature data collected by the soil heat exchanger loop is automatically corrected by the temperature correction parameter. By setting the temperature correction parameters as described above, the impact of the spatial heterogeneity of the soil energy field is eliminated to some extent, laying a data foundation for the subsequent establishment of energy supply strategies.

[0022] Furthermore, once the three-dimensional thermal property distribution map is corrected, the energy station operation and maintenance terminal will send the three-dimensional thermal property distribution map to the user interaction strategy management terminal. The user interaction strategy management terminal establishes a thermal response model based on the three-dimensional thermal property distribution map and building information. The thermal response model includes a building image model established based on the characteristics of the building envelope, pipeline distribution information and energy supply area. The building image model is divided into multiple energy supply and release areas according to energy preference information, and the three-dimensional thermal property distribution map is covered on the model display area according to the spatial distribution. A time axis for energy supply and release is set for each energy supply and release area. Based on the expected temperature range, work and rest time and cost-sensitive interval in the energy consumption preference information, the expected load of the energy supply and release area is marked and marked on the energy supply and release time axis in chronological order. The expected load of each time node on each energy supply and release time axis is statistically analyzed to obtain the load prediction curve. Time-of-use electricity price information (such as off-peak electricity at night and peak electricity during the day) is obtained through the Internet. Multiple economic charging windows (such as off-peak electricity price periods at night) and economic releasing windows (such as peak electricity price periods during the day) are marked on the energy supply and release time axis. At the same time, according to the cost-sensitive interval set by the user, corresponding strategy priorities are set for each window period, and the load forecast curve and energy supply and release time axis are sent to the energy station operation and maintenance terminal. The strategy priorities are divided into high-priority window periods, medium-priority window periods, and low-priority window periods, from high to low. For example, the priority window period is the period when the electricity price is at its highest. During this window period, the priority of implementing the economic energy release strategy is set to the highest, because the economic benefits are maximized for every kilowatt-hour saved at this time. The limit requirements for soil temperature are also appropriately relaxed to ensure that the energy release target is achieved.

[0023] Furthermore, the soil energy field management module in the energy station operation and maintenance terminal sets several strategy adjustment points on the energy supply and release time axis according to the load prediction curve. Each strategy adjustment point contains an energy supply and release strategy, such as soil charging, regional energy supply, etc. Based on the strategy priority associated with each strategy adjustment point, a strategy weight is set for each strategy adjustment point. According to the priority of the window period from high to low, the strategy weight of the corresponding strategy adjustment point decreases sequentially. For example, the strategy weight of the starting point of the highest priority economic charging window period is 100, and the strategy weight of the lowest priority window period is 10. Starting from the first strategy adjustment point in chronological order, obtain the matching degree values ​​between each strategy adjustment point and the current building status (such as average soil temperature, real-time building load, and outdoor temperature). The formula for calculating the matching degree value γ is: ; in and w represent the temperature correction parameter and the policy weight, respectively. These represent the ideal soil temperature and the actual soil temperature, respectively. These represent the current electricity price and the preset maximum electricity price, respectively. These represent the predicted load and the maximum functional capacity, respectively. Set a policy switching threshold and check in real time whether the matching degree value γ is greater than or equal to the policy switching threshold. If it is greater than or equal to the threshold, the policy switching is triggered; otherwise, no action is taken. For example, when γ exceeds the strategy switching threshold, the current soil source-only energy supply mode will be switched to soil source + air source combined energy supply or the phase change energy storage unit will be activated to release energy. If it is predicted that there will be a conflict between the energy supply and release strategies at different strategy adjustment points (such as requiring soil energy charging and releasing at the same time), the matching degree value γ of the conflicting strategies will be compared. The strategy adjustment point with the smaller γ value will postpone the strategy switching or select the suboptimal strategy option. The strategy adjustment point with the larger γ value will be recorded as the effective strategy adjustment point until the strategy conflict is resolved. Based on each effective strategy adjustment point, a corresponding dynamic energy supply and release strategy sequence is generated. Then, the energy station operation and maintenance terminal sends the dynamic energy supply and release strategy sequence to each energy supply and release device for execution (such as heat pump host, valve, water pump, etc.). During the operation of the dynamic energy supply strategy sequence, the thermal response model is continuously updated. Then, after each heat exchange test cycle, the load forecast curve and the window period on the energy supply and release time axis are updated in a rolling manner based on the thermal response model and real-time electricity price, and the dynamic energy supply and release strategy sequence is updated synchronously.

[0024] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations 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. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A daytime-to-night intelligent energy supply system based on soil-coupled energy, comprising an intelligent cloud control platform, characterized in that, The intelligent cloud control platform has communication connections with a user interaction strategy management terminal and an energy station operation and maintenance terminal. The energy station operation and maintenance terminal is equipped with a soil energy field management module and a multi-source coupled energy supply module; The soil energy field management module is used to set up a soil heat exchanger loop, collect geothermal parameter sets around the user's building through the soil heat exchanger loop, set strategy adjustment points on the energy supply and release time axis from the user interaction strategy management terminal, obtain the matching degree value of each strategy adjustment point, and then determine whether each strategy adjustment point should be executed based on the matching degree value. Based on the judgment result, a dynamic energy supply and release strategy sequence is generated and executed. The multi-source coupled power supply module is used to establish a three-dimensional thermal property distribution map based on the spatial location distribution of the soil heat exchanger circuit, map the geothermal parameter set onto the three-dimensional thermal property distribution map, and then correct the geothermal parameter set. The user interaction strategy management terminal is used to establish a thermal response model based on the three-dimensional thermal property distribution map, divide the thermal response model into multiple energy supply and release regions, establish an energy supply and release time axis and obtain time-of-use electricity price information, and then set window periods and load forecast curves for each energy supply and release region on the energy supply and release time axis.

2. The intelligent energy supply system based on soil-coupled energy, characterized in that, Users upload energy consumption preference information and building information to the user interaction strategy management terminal and the energy station operation and maintenance terminal. The building information includes building envelope characteristics, pipeline distribution information, geographical coordinates and energy supply area. The energy consumption preference signal includes desired temperature range, work and rest time and cost-sensitive interval.

3. The intelligent energy supply system based on soil-coupled energy, characterized in that, The process of acquiring the geothermal parameter set includes: The location of the user's building is determined by the geographic coordinates of the building information, and n parallel soil heat exchanger loops are set up around the user's building. Each soil heat exchanger loop is equipped with a temperature sensor and a flow sensor, where n is a natural number greater than or equal to 4. Then, each soil heat exchanger loop works in concert to collect the initial temperature distribution and thermal property parameters of the soil energy field as a geothermal parameter set.

4. The intelligent energy supply system based on soil-coupled energy, characterized in that, The process of establishing the three-dimensional thermal property distribution map includes: A three-dimensional thermal property distribution map of the soil energy field is established. The geothermal parameter sets collected by each soil heat exchanger loop are mapped onto the three-dimensional thermal property distribution map. All temperature data are standardized and temperature difference thresholds are set. The three-dimensional thermal property distribution map sets n data display points according to the spatial location distribution of the soil heat exchanger circuit. Then, based on the geothermal parameter set collected by the soil heat exchanger circuit and the data collection range, the initial temperature distribution of the geothermal parameter set is distributed in the form of thermal ripples on the three-dimensional thermal property distribution map, so that the spatial location associated with the same thermal ripple in the three-dimensional thermal property distribution map corresponds to the same temperature value. Determine the relationship between the temperature difference and the temperature difference threshold between adjacent data display points in the three-dimensional thermal property distribution map. Based on the determination result, mark the scene area associated with the data perception range of the corresponding data display point as a thermal property anomaly area, and treat the data display point as measurement noise for smoothing and filtering. After all data display points have been judged, a short-term enhanced heat transfer test is conducted on the soil heat exchanger loops around the scene area marked as an abnormal thermal property zone.

5. The intelligent energy supply system based on soil-coupled energy, characterized in that, The short-time enhanced heat transfer test includes: Retrieve the soil heat exchanger loop associated with the scene area marked as a thermal property anomaly area. Based on the distribution location of the thermal property anomaly area in the three-dimensional thermal property distribution map, retrieve the three-dimensional thermal property distribution map area that is not in the thermal property anomaly area within the data sensing range of the soil heat exchanger loop associated with the thermal property anomaly area and record it as the control area. Obtain the average temperature of the area based on the thermal pattern distribution in the control area. Set the heat exchange test cycle, and then collect the temperature response curve of the soil heat exchanger loop under m heat exchange test cycles, where m is a natural number greater than 50. Simultaneously, the control temperature change curves of the control area under each heat exchange test cycle are obtained. The control temperature change curves and temperature response curves under each heat exchange test cycle are mapped onto the same two-dimensional coordinate system. Correction parameters are set for the temperature response curve and iterated so that the temperature values ​​on the temperature response curve are iterated with the correction parameters until the temperature response curve overlaps with the control temperature change curve to the greatest extent. The average value of the correction parameters under each heat exchange test cycle is recorded as the temperature correction parameter. The temperature correction parameter is used to correct the abnormal thermal properties.

6. The intelligent energy supply system based on soil-coupled energy, characterized in that, The process of establishing the thermal response model includes: A thermal response model is established based on the three-dimensional thermal property distribution map and building information. The thermal response model includes a building image model established based on the characteristics of the building envelope, pipeline distribution information and energy supply area. The building image model is divided into multiple energy supply and release areas according to energy preference information, and the three-dimensional thermal property distribution map is covered on the model display area according to the spatial distribution. A time axis for energy supply and release is set for each energy supply and release area. Based on the expected temperature range, work and rest time and cost-sensitive interval in the energy consumption preference information, the expected load of the energy supply and release area is marked and marked on the energy supply and release time axis in chronological order. The expected load of each time node on each energy supply and release time axis is statistically analyzed to obtain the load prediction curve. By obtaining time-of-use electricity price information through the Internet, multiple economic charging and releasing windows are marked on the energy supply and release timeline. At the same time, according to the cost-sensitive range set by the user, corresponding strategy priorities are set for each window.

7. The intelligent energy supply system based on soil-coupled energy, characterized in that, according to claim 6, The process of obtaining the matching degree value of the strategy adjustment point includes: Based on the load forecast curve, several strategy adjustment points are set on the power supply and release time axis, and each strategy adjustment point contains a power supply and release strategy. Based on the strategy priority associated with each strategy adjustment point, a strategy weight is set for each strategy adjustment point. According to the priority of the window period from high to low, the strategy weight of the corresponding strategy adjustment point decreases sequentially. Starting from the first strategy adjustment point in chronological order, the matching degree value γ between each strategy adjustment point and the current building state is obtained.

8. A daytime-to-night intelligent energy supply system based on soil-coupled energy, as described in claim 7, is characterized in that... The generation process of the dynamic energy supply and release strategy sequence includes: Set a policy switching threshold and check in real time whether the matching degree value γ is greater than or equal to the policy switching threshold. If it is greater than or equal to the threshold, the policy switching is triggered; otherwise, no action is taken. If a conflict is predicted between the power supply and release strategies at different strategy adjustment points, the matching degree value γ of the conflicting strategies is compared. The strategy adjustment point with a smaller γ value will temporarily postpone the strategy switching or select the suboptimal strategy option. The strategy adjustment point with a larger γ value is recorded as a valid strategy adjustment point until the strategy conflict is resolved. Based on each effective strategy adjustment point, a corresponding dynamic energy supply and release strategy sequence is generated, and then the energy station operation and maintenance terminal sends the dynamic energy supply and release strategy sequence to each energy supply and release device for execution. During the operation of the dynamic energy supply strategy sequence, the thermal response model is continuously updated. Then, after each heat exchange test cycle, the load forecast curve and the window period on the energy supply and release time axis are updated in a rolling manner based on the thermal response model and real-time electricity price, and the dynamic energy supply and release strategy sequence is updated synchronously.

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