Dynamic regulation and control method, device and equipment based on temperature monitoring points in heat supply system

Abstract

The invention provides a dynamic regulation and control method, device and equipment based on temperature monitoring points in a heat supply system, and the method comprises the steps: determining the length of a pipe network and the topographic features of an area where the pipe network is located, and determining a plurality of temperature monitoring points based on the length of the pipe network and the topographic features; temperature data, heat supply pipe network operation data and external environment data corresponding to each temperature monitoring point are obtained; based on the temperature data, the operation data of the heat supply pipe network and the external environment data, combined with dynamic thermodynamic balance, determining heat required by thermodynamic; based on real-time feedback data, historical data and heat demand heat of a heat supply system, heat supply parameters are dynamically adjusted step by step through self-adaptive control; real-time data visualization management and data monitoring management are carried out on the dynamically adjusted heat supply parameters, a data report is generated, and due to the fact that the determined temperature monitoring points are combined with the pipe network length and the topographic features, and through data fusion and self-adaptive control, the finally dynamically adjusted heat supply parameters can better improve the regulation and control efficiency of the heat supply system.

Description

Technical Field

[0001] The present invention relates to the technical field of heat supply management, and in particular to a dynamic control method, device and equipment based on temperature monitoring points in a heat supply system. Background Art

[0002] As the scale and complexity of urban heating systems continue to increase, how to improve the operating efficiency of the system while ensuring the quality of heating has become an important issue facing heating companies. As the main heat source, the thermal power plant transports hot water to the pressure isolation station, which then distributes the hot water to various heating stations in the urban area, and then transports it to users after passing through the heat exchange station. In order to achieve stable operation of the heating system, especially to cope with changes in external temperature and fluctuations in user demand, the heating company needs to monitor and dynamically control the temperature in the pipeline network in real time. At present, the existing control systems mostly monitor the temperature at a fixed point, and then perform temperature control through the Internet of Things, or PID control, or feedback control to ensure the stability of the heating system.

[0003] However, the above control method is relatively simple, resulting in relatively poor temperature control efficiency of the final heating system. Summary of the invention

[0004] The present invention provides a dynamic control method, device and equipment based on temperature monitoring points in a heating system, which are used to solve the defect of low temperature control efficiency of the heating system in the prior art.

[0005] In a first aspect, the present invention provides a dynamic control method based on temperature monitoring points in a heating system, comprising:

[0006] Determine the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determine a plurality of temperature monitoring points based on the length of the pipeline network and the terrain characteristics;

[0007] Obtaining temperature data, heating network operation data and external environment data corresponding to each of the temperature monitoring points;

[0008] Determine the heat demand based on the temperature data, the heat supply network operation data and the external environment data in combination with dynamic thermal balance;

[0009] Based on the real-time feedback data of the heating system, historical data and the heat demand, the heating parameters are dynamically adjusted in steps using adaptive control;

[0010] The dynamically adjusted heating parameters are managed by real-time data visualization and data monitoring, and a data report is generated.

[0011] According to a dynamic control method based on temperature monitoring points in a heating system provided by the present invention, the method of determining a plurality of temperature monitoring points based on the pipe network length and the terrain characteristics comprises:

[0012] Determine the total length, branch and segment lengths of the pipe network, and set temperature monitoring points at pump stations, valves and junctions of the pipe network;

[0013] Obtain a topographic map of the area where the pipe network is located, and annotate the elevation, slope, soil type, groundwater level, and vegetation cover;

[0014] Based on the elevation, slope, soil type, groundwater level and vegetation coverage, a point where the terrain environment temperature difference at the location of the pipeline network is greater than a preset value is determined as a temperature monitoring point.

[0015] According to a dynamic control method based on temperature monitoring points in a heating system provided by the present invention, the heat demand heat is determined based on the temperature data, the heating network operation data and the external environment data in combination with dynamic thermal balance, including:

[0016] Performing dynamic thermal balance fusion on the temperature data and the heating network operation data to obtain fused data;

[0017] Combining the fused data with the external environment data, using multivariate regression analysis and machine learning, to predict optimal heating parameters under different conditions;

[0018] Based on the optimal heating parameters, the heat demand of different heating stations is determined.

[0019] According to a dynamic control method based on temperature monitoring points in a heating system provided by the present invention, the external environment data includes weather forecast data after a preset time and historical data for the same period.

[0020] According to a dynamic control method based on temperature monitoring points in a heating system provided by the present invention, the method dynamically adjusts heating parameters in steps using adaptive control based on real-time feedback data, historical data and the thermal demand heat of the heating system, including:

[0021] Determine the data difference between the real-time feedback data, the historical data and the thermal demand heat;

[0022] Based on the data difference, the step amplitude is determined, and the heating parameters are progressively adjusted according to the step amplitude through adaptive control.

[0023] A dynamic control method based on temperature monitoring points in a heating system provided by the present invention also includes:

[0024] When a manual intervention instruction is received, the adaptive control process is stopped, and a manual confirmation instruction from the target person is received;

[0025] After the target person manually confirms, the heating system is regulated based on the manual intervention instruction.

[0026] According to a dynamic control method based on temperature monitoring points in a heating system provided by the present invention, real-time data visualization management of the dynamically adjusted heating parameters includes:

[0027] Simulate the pipe network and users of the heating system;

[0028] The simulation is used to display the data of each temperature monitoring point of the pipe network and the data of each user in real time.

[0029] According to a dynamic control method based on temperature monitoring points in a heating system provided by the present invention, generating a data report includes:

[0030] Periodically counting the changes in heating parameters and the data changes at each temperature monitoring point;

[0031] Based on the changes in the heating parameters and the data changes at the temperature monitoring points, a data report including heating efficiency and maintenance methods is generated.

[0032] In a second aspect, the present invention further provides a dynamic control device based on temperature monitoring points in a heating system, comprising:

[0033] A first determination module is used to determine the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determine multiple temperature monitoring points based on the length of the pipeline network and the terrain characteristics;

[0034] An acquisition module, used to acquire temperature data, heating network operation data and external environment data corresponding to each of the temperature monitoring points;

[0035] A second determination module is used to determine the heat demand based on the temperature data, the heat supply network operation data and the external environment data in combination with dynamic thermal balance;

[0036] An adaptive module, for dynamically adjusting heating parameters in steps using adaptive control based on real-time feedback data of the heating system, historical data and the thermal demand heat;

[0037] The visualization module is used to perform real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters and generate data reports.

[0038] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the dynamic control method based on temperature monitoring points in a heating system as described above is implemented.

[0039] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a dynamic control method based on temperature monitoring points in a heating system as described in any one of the above.

[0040] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements a dynamic control method based on temperature monitoring points in a heating system as described in any one of the above.

[0041] The present invention provides a dynamic control method, device and equipment based on temperature monitoring points in a heating system, and the method includes: determining the length of a pipeline network and the terrain characteristics of the area where the pipeline network is located, and determining multiple temperature monitoring points based on the pipeline network length and the terrain characteristics; obtaining temperature data, heating pipeline network operation data and external environment data corresponding to each temperature monitoring point; determining the thermal demand heat based on the temperature data, heating pipeline network operation data and external environment data, combined with dynamic thermal balance; based on the real-time feedback data, historical data and thermal demand heat of the heating system, dynamically adjusting the heating parameters in steps by using adaptive control; performing real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters, and generating a data report. Since the determined temperature monitoring points are combined with the pipeline network length and the terrain characteristics, the temperature monitoring results are more scientific, and through data fusion and adaptive control, combined with data report feedback, the final dynamically adjusted heating parameters can further improve the control efficiency of the heating system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 is a flow chart of a dynamic control method based on temperature monitoring points in a heating system provided in this embodiment;

[0044] Figure 2 is a structural schematic diagram of a dynamic control device based on temperature monitoring points in a heating system provided in this embodiment;

[0045] Figure 3 It is a schematic diagram of the structure of the electronic device provided in this embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Figure 1 It is a flow chart of the dynamic control method based on temperature monitoring points in the heating system provided in this embodiment.

[0048] like Figure 1 As shown, the dynamic control method based on temperature monitoring points in a heating system provided by an embodiment of the present invention mainly includes the following steps:

[0049] 101. Determine the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determine multiple temperature monitoring points based on the length of the pipeline network and the terrain characteristics.

[0050] In a specific implementation process, a full-coverage monitoring network is formed by setting up multiple temperature monitoring points from the thermal power plant to the pressure isolation station, and between the pressure isolation station and each thermal power station. Through this multi-point monitoring, the system can obtain the temperature data of each section of the pipeline in real time, ensure the thermal balance of the entire network, and respond to local temperature changes in a timely manner.

[0051] The pipe network is spread over a wide area. Therefore, the rationality of temperature monitoring can only be guaranteed by comprehensive consideration of the pipe network and the terrain. First, determine the total length, branch and segment length of the pipe network, and set temperature monitoring points at the pump stations, valves and intersections of the pipe network; obtain the topographic map of the area where the pipe network is located, and mark the elevation, slope, soil type, groundwater level and vegetation coverage; based on the elevation, slope, soil type, groundwater level and vegetation coverage, determine the points where the terrain environment temperature difference at the location of the pipe network is greater than the preset value as temperature monitoring points. This includes key node monitoring, terrain sensitive area monitoring and equidistant point distribution.

[0052] Key node monitoring: Set up monitoring points at key nodes of the pipeline network (such as pump station entrances and exits, before and after valves, intersections, etc.) to monitor temperature changes in these areas. Topography-sensitive area monitoring: Add monitoring points in areas with complex terrain (such as areas with large slope changes, river valleys, etc.) to capture temperature changes unique to these areas. Equidistant point distribution: In areas where the pipeline network is long and the terrain is relatively uniform, monitoring points can be set up in an equidistant manner to ensure that the temperature of the entire pipeline network is evenly monitored. The point spacing can be determined based on the specific conditions of the pipeline network and monitoring needs.

[0053] At different temperature monitoring points, high-precision temperature sensors are used to monitor the temperature of hot water in the pipeline in real time. The temperature data is transmitted to the central control system through advanced wireless transmission technologies such as LoRaWAN (Long-Range Wide Area Network) to ensure the stability and real-time performance of data transmission. LoRaWAN technology is used to build a low-power, long-distance data transmission network to achieve real-time transmission of temperature data. The data collected by the sensor is first analyzed by the data processing module and then transmitted to the central control system through the LoRaWAN gateway. The temperature monitoring points finally determined in combination with the length of the pipeline network and the terrain characteristics can better ensure the rationality of temperature monitoring, thereby ensuring the accuracy and efficiency of subsequent heating system management.

[0054] For example, three temperature monitoring points are set up in the 8.7-kilometer pipeline between the thermal power plant and the pressure isolation station, located 2 kilometers, 5 kilometers and 8 kilometers away from the thermal power plant. The system uses the temperature data of these measuring points to adjust the heating temperature and flow of the thermal power plant in real time to ensure stable heating at the pressure isolation station.

[0055] 102. Obtain the temperature data, heating network operation data and external environment data corresponding to each temperature monitoring point.

[0056] The operation data of the heating network includes hot water flow, pressure, external environment temperature and user heat load, etc. The external environment data includes weather forecast data after a preset time and historical data for the same period. The temperature data can be obtained by a temperature sensor, the operation data of the heating network can be obtained through the central control system, and the external environment can be obtained through weather forecast, as long as it can be obtained in a timely and accurate manner.

[0057] 103. Based on temperature data, heating network operation data and external environment data, combined with dynamic thermal balance, determine the heat demand.

[0058] The temperature data and the operation data of the heating network are dynamically integrated into the thermal balance to obtain the integrated data, which integrates the full-process operation data from the thermal power plant to the pressure isolation station and then to each thermal power station. These data include the supply and return water temperature, flow rate, pressure of hot water, and the actual heating situation of each community. The system collects these data in real time through the Internet of Things technology and integrates them in the central control system.

[0059] Combining fusion data and external environmental data, using multivariate regression analysis and machine learning, the optimal heating parameters under different conditions are predicted; based on the optimal heating parameters, the heat demand of different heating stations is determined. It can dynamically calculate the thermal balance state of the heating network, calculate the actual heat demand of each heating station in real time by analyzing temperature data, heat load and external ambient temperature, and adjust the output parameters of thermal power plants and pressure isolation stations accordingly. In this way, it can not only meet the heating needs of each community, but also optimize the overall heat distribution and reduce energy waste.

[0060] Thanks to the use of multivariate regression analysis and machine learning, the optimal heating parameters under different conditions are predicted. The heating parameters can be adjusted in advance according to future weather forecasts and historical heat usage data to ensure that the heating system is well prepared before temperature fluctuations occur. The heating parameters can be adjusted in advance and preventive regulation can be carried out to avoid the impact of temperature fluctuations on the heating system.

[0061] By real-time monitoring of each temperature monitoring point and other data in the pipe network, abnormal conditions can be quickly detected, such as a sudden drop in temperature, an abnormal increase in pressure, etc. When the system detects an abnormal condition, it will immediately sound an alarm and mark the problem area on the management platform. Managers can respond quickly based on the early warning information, such as adjusting heating parameters or arranging on-site inspections to prevent the problem from further deteriorating.

[0062] 104. Based on the real-time feedback data, historical data and heat demand of the heating system, the heating parameters are dynamically adjusted in steps using adaptive control.

[0063] In order to prevent over-adjustment, adaptive control is used to adjust the heating parameters autonomously according to the real-time feedback and historical data of the system to ensure the stability of the regulation process. Specifically, the data difference between the real-time feedback data, historical data and the heat demand is determined; based on the data difference, the step amplitude is determined, and the heating parameters are gradually adjusted according to the step amplitude through adaptive control.

[0064] The system does not make large adjustments to heating parameters all at once, but makes small, gradual adjustments to ensure a steady temperature change. After each adjustment, the system immediately evaluates the temperature change and decides whether to continue or stop adjusting. This gradual adjustment method can effectively prevent over-regulation of temperature. Adaptive control has built-in multi-layer feedback loops that can monitor the actual effect of each adjustment in real time. If over-adjustment is detected, the system automatically corrects the next control strategy to avoid continuous over-adjustment. The feedback loop ensures that the system can quickly return to the optimal state after each adjustment, thereby improving the accuracy and safety of regulation.

[0065] Although the system has a high degree of automatic control capabilities, it still needs to cooperate with the manual adjustments of the operation and maintenance personnel in complex or emergency situations. Therefore, when it detects that a major adjustment is needed, the system will first notify the operation and maintenance personnel, allowing them to manually confirm or adjust the parameters recommended by the system. This can avoid the problem of over-adjustment during the automatic control process while ensuring the effectiveness of manual intervention. During the automatic control process, the system will require manual confirmation from the operation and maintenance personnel based on the preset conditions. For example, when the temperature change exceeds a certain range, the system will suspend automatic adjustment and prompt the operation and maintenance personnel to manually confirm or adjust. In this way, the system can maintain a high degree of automation while introducing manual judgment at critical moments to ensure system safety.

[0066] By introducing adaptive control, real-time feedback and step-by-step adjustment mechanisms, the stability and accuracy of the control process are ensured. The system can dynamically adjust the heating parameters according to actual needs to avoid over-adjustment, and can quickly respond to changes in the external environment and fluctuations in user demand. Through the manual priority mechanism and manual confirmation steps, manual judgment can be introduced in key control links. Combined with automatic control, it provides higher flexibility and security when dealing with emergencies or special situations, ensuring stable operation of the system.

[0067] Since multiple temperature monitoring points are set between the pressure isolation station and each heating station according to the pipeline length and heat load, the central control system dynamically adjusts the heating parameters of each heating station according to the temperature data of each heating station to ensure the temperature stability at the user end. Through multi-point monitoring, the system can detect temperature anomalies in time to avoid fluctuations in the entire network caused by temperature anomalies in a single area.

[0068] 105. Carry out real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters and generate data reports.

[0069] Specifically, the pipe network and users of the heating system are simulated, and the data of each temperature monitoring point in the pipe network and the data of each user are displayed in real time through simulation. Through simulation combined with visualization, managers can view the data of each temperature monitoring point in real time through the central control platform and understand the heating status of each pipe section and each heating station. This integrated visual management method enables managers to quickly identify problem areas and make corresponding decisions.

[0070] By periodically counting the changes in heating parameters and the data changes at each temperature monitoring point, a data report containing heating efficiency and maintenance methods is generated based on the changes in heating parameters and the data changes at the temperature monitoring points. This includes the temperature change trend, equipment operating status, control records, etc. at each monitoring point. These reports help management make data-driven decisions and develop accurate maintenance plans. The system can also automatically recommend preventive maintenance measures based on abnormal fluctuations in monitoring data, thereby reducing the risk of equipment failure and system interruption.

[0071] It also supports multi-level user authority settings, and different operators can access different levels of data and control functions according to their responsibilities. For example, senior managers can view the overall operating status of the system and make strategic decisions, while front-line operation and maintenance personnel can monitor and adjust the heating parameters of specific areas in real time. Through clear authority classification and responsibility division, the management efficiency of the system has been greatly improved, while also ensuring data security and traceability of operations, and ensuring the efficiency of heating system management and regulation.

[0072] Based on the same general inventive concept, the present invention also protects a dynamic control device based on temperature monitoring points in a heating system. The dynamic control device based on temperature monitoring points in the heating system provided by the present invention is described below. The dynamic control device based on temperature monitoring points in the heating system described below and the dynamic control method based on temperature monitoring points in the heating system described above can be referenced to each other.

[0073] Figure 2 It is a structural schematic diagram of a dynamic control device based on temperature monitoring points in a heating system provided in this embodiment.

[0074] like Figure 2 As shown, this embodiment provides a dynamic control device based on temperature monitoring points in a heating system, including:

[0075] The first determination module 201 is used to determine the length of the pipe network and the terrain characteristics of the area where the pipe network is located, and determine multiple temperature monitoring points based on the length of the pipe network and the terrain characteristics;

[0076] The acquisition module 202 is used to acquire the temperature data, heating network operation data and external environment data corresponding to each temperature monitoring point;

[0077] The second determination module 203 is used to determine the heat demand based on the temperature data, the heat supply network operation data and the external environment data in combination with the dynamic thermal balance;

[0078] An adaptive module 204 is used to dynamically adjust heating parameters in steps using adaptive control based on real-time feedback data, historical data and thermal demand of the heating system;

[0079] The visualization module 205 is used to perform real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters and generate data reports.

[0080] Figure 3 It is a schematic diagram of the structure of the electronic device provided in this embodiment.

[0081] like Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute a dynamic control method based on temperature monitoring points in a heating system, the method comprising: determining the length of the pipe network and the terrain characteristics of the area where the pipe network is located, and determining a plurality of temperature monitoring points based on the pipe network length and the terrain characteristics; obtaining temperature data, heating pipe network operation data and external environment data corresponding to each of the temperature monitoring points; determining the heat demand based on the temperature data, the heating pipe network operation data and the external environment data in combination with dynamic thermodynamic balance; dynamically adjusting the heating parameters in steps using adaptive control based on the real-time feedback data, historical data and the heat demand of the heating system; performing real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters, and generating a data report.

[0082] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0083] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the dynamic control method based on temperature monitoring points in the heating system provided by the above-mentioned methods, the method including: determining the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determining multiple temperature monitoring points based on the length of the pipeline network and the terrain characteristics; obtaining temperature data, heating pipeline network operation data and external environment data corresponding to each of the temperature monitoring points; determining the thermal demand heat based on the temperature data, the heating pipeline network operation data and the external environment data in combination with dynamic thermal balance; based on the real-time feedback data, historical data and the thermal demand heat of the heating system, using adaptive control to dynamically adjust the heating parameters in steps; performing real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters, and generating a data report.

[0084] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the dynamic control method based on temperature monitoring points in the heating system provided by the above-mentioned methods, the method comprising: determining the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determining multiple temperature monitoring points based on the length of the pipeline network and the terrain characteristics; obtaining temperature data, heating pipeline network operation data and external environment data corresponding to each of the temperature monitoring points; determining the thermal demand heat based on the temperature data, the heating pipeline network operation data and the external environment data in combination with dynamic thermal balance; dynamically adjusting the heating parameters in steps using adaptive control based on the real-time feedback data, historical data and the thermal demand heat of the heating system; performing real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters, and generating a data report.

[0085] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0086] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dynamic control method based on temperature monitoring points in a heating system, characterized in that: include: Determine the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determine a plurality of temperature monitoring points based on the length of the pipeline network and the terrain characteristics; Obtaining temperature data, heating network operation data and external environment data corresponding to each of the temperature monitoring points; Determine the heat demand based on the temperature data, the heat supply network operation data and the external environment data in combination with dynamic thermal balance; Based on the real-time feedback data of the heating system, historical data and the heat demand, the heating parameters are dynamically adjusted in steps using adaptive control; The dynamically adjusted heating parameters are managed by real-time data visualization and data monitoring, and a data report is generated.

2. The dynamic control method based on temperature monitoring points in a heating system according to claim 1 is characterized in that: The step of determining a plurality of temperature monitoring points based on the pipe network length and the terrain features includes: Determine the total length, branch and segment lengths of the pipe network, and set temperature monitoring points at pump stations, valves and junctions of the pipe network; Obtain a topographic map of the area where the pipe network is located, and annotate the elevation, slope, soil type, groundwater level, and vegetation cover; Based on the elevation, slope, soil type, groundwater level and vegetation coverage, a point where the terrain environment temperature difference at the location of the pipeline network is greater than a preset value is determined as a temperature monitoring point.

3. The dynamic control method based on temperature monitoring points in a heating system according to claim 1 is characterized in that: The determining of the heat demand based on the temperature data, the heat supply network operation data and the external environment data in combination with dynamic thermal balance includes: Performing dynamic thermal balance fusion on the temperature data and the heating network operation data to obtain fused data; Combining the fused data with the external environment data, using multivariate regression analysis and machine learning, to predict optimal heating parameters under different conditions; Based on the optimal heating parameters, the heat demand of different heating stations is determined.

4. The dynamic control method based on temperature monitoring points in a heating system according to claim 3 is characterized in that: The external environment data includes weather forecast data after a preset time and historical data for the same period.

5. The dynamic control method based on temperature monitoring points in a heating system according to claim 1, characterized in that: The method of dynamically adjusting heating parameters in steps by using adaptive control based on the real-time feedback data of the heating system, historical data and the heat demand, includes: Determine the data difference between the real-time feedback data, the historical data and the thermal demand heat; Based on the data difference, the step amplitude is determined, and the heating parameters are progressively adjusted according to the step amplitude through adaptive control.

6. The dynamic control method based on temperature monitoring points in a heating system according to claim 5, characterized in that: Also includes: When a manual intervention instruction is received, the adaptive control process is stopped, and a manual confirmation instruction from the target person is received; After the target person manually confirms, the heating system is regulated based on the manual intervention instruction.

7. The dynamic control method based on temperature monitoring points in a heating system according to claim 1, characterized in that: The real-time data visualization management of the dynamically adjusted heating parameters includes: Simulate the pipe network and users of the heating system; The simulation is used to display the data of each temperature monitoring point of the pipe network and the data of each user in real time.

8. The dynamic control method based on temperature monitoring points in a heating system according to claim 7, characterized in that: The generating of data report comprises: Periodically counting the changes in heating parameters and the data changes at each temperature monitoring point; Based on the changes in the heating parameters and the data changes at the temperature monitoring points, a data report including heating efficiency and maintenance methods is generated.

9. A dynamic control device based on temperature monitoring points in a heating system, characterized in that: include: A first determination module is used to determine the length of the pipeline network and the terrain characteristics of the area where the pipeline network is located, and determine multiple temperature monitoring points based on the length of the pipeline network and the terrain characteristics; An acquisition module, used to acquire temperature data, heating network operation data and external environment data corresponding to each of the temperature monitoring points; A second determination module is used to determine the heat demand based on the temperature data, the heat supply network operation data and the external environment data in combination with dynamic thermal balance; An adaptive module, for dynamically adjusting heating parameters in steps using adaptive control based on real-time feedback data of the heating system, historical data and the thermal demand heat; The visualization module is used to perform real-time data visualization management and data monitoring management on the dynamically adjusted heating parameters and generate data reports.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the dynamic control method based on temperature monitoring points in the heating system as described in any one of claims 1 to 8 is implemented.

Images