Safety management method and device of heat pipe network, electronic equipment and storage medium

Abstract

The application provides a heat pipe network safety management method and device, electronic equipment and storage medium. The method comprises the following steps: evaluating first real-time monitoring data of a plurality of heat pipe network grids according to a preset safety standard to determine a safety level; analyzing spatial data of a plurality of first heat pipe network grids under a target safety level to determine a spatial position and a relative distance; selecting a plurality of second heat pipe network grids with a relative distance less than or equal to a preset relative distance, analyzing real-time and historical operation data of the plurality of second heat pipe network grids, and determining a first heat demand mode and a first heat supply capacity; determining a plurality of target heat pipe network grids with complementary heat energy, a target heat demand mode and a target heat supply capacity according to the first heat demand mode and the first heat supply capacity, generating a target heat pipe network grid group, and performing a safety management operation on the target heat pipe network grid group according to the target safety level, the target heat demand mode and the target heat supply capacity.

Description

Technical Field

[0001] This application relates to the field of heating network safety technology, and in particular to a method, device, electronic equipment and storage medium for the safety management of heating networks. Background Technology

[0002] With the acceleration of urbanization and the continuous growth of energy demand, the safe operation and efficient management of heating pipe networks, as an important part of urban heating, are receiving increasing attention.

[0003] In related technologies, monitoring equipment is typically used to periodically inspect the physical condition of the heating network, while sensors are used to monitor key parameters such as pressure, flow rate, and temperature in the network. These key parameters are then transmitted to the central control room for analysis. If any abnormalities are detected, staff are notified to conduct on-site inspections and take appropriate action.

[0004] However, the above-mentioned approach to the safety management of heating networks relies heavily on the periodic inspection of monitoring equipment. This management model, which depends on periodic inspections, suffers from timeliness issues and struggles to respond in real time to emergencies in the heating network. This limitation may prevent timely action in emergency situations, thereby affecting the overall safety operation efficiency of the heating network and resulting in low safety management efficiency of the heating network in related technologies. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for the safety management of heating pipe networks, which can improve the efficiency of safety management of heating pipe networks.

[0006] In a first aspect, this application provides a safety management method for a heating network, the method comprising: performing a safety assessment on first real-time monitoring data of multiple heating network grids in a heating network according to preset safety standards to determine the safety level of the multiple heating network grids; analyzing the spatial data of the multiple first heating network grids with a target safety level in the first real-time monitoring data to determine the spatial location of each of the multiple first heating network grids, wherein the safety level includes the target safety level, and the multiple heating network grids include multiple first heating network grids; determining the relative distance between every two first heating network grids in the multiple first heating network grids according to the spatial location; determining a multiple second heating network grids from the multiple first heating network grids whose relative distance is less than or equal to a preset relative distance, wherein the multiple first heating network grids include multiple second heating network grids; and performing a safety assessment on first real-time monitoring data of multiple heating network grids with a target safety level in the first real-time monitoring data to determine the spatial location of each of the multiple first heating network grids, wherein the safety level includes the target safety level, and the multiple ...; and performing a safety assessment on first real-time monitoring data of multiple heating network grids with a target safety level in the first real-time monitoring data to determine the spatial location of each of the multiple first heating network grids; and performing a The data analysis includes operational data and historical operational data of multiple secondary heating network grids to determine the primary heat demand pattern and primary heating capacity of each grid. A one-to-one correspondence exists between the primary heat demand pattern and primary heating capacity of each secondary heating network grid. Further analysis of these patterns and capacities identifies multiple target heating network grids with complementary heat energy relationships, along with their target heat demand patterns and target heating capacities. The primary heat demand pattern includes the target heat demand pattern, and the primary heating capacity includes the target heating capacity. These target heating network grids are then grouped into a target heating network grid group, and safety management operations are performed on this group based on the target safety level, target heat demand pattern, and target heating capacity.

[0007] By adopting the above technical solution, a safety assessment is performed on the first real-time monitoring data of multiple heating network grids according to preset safety standards. This enables real-time safety assessment of multiple heating network grids, allowing for timely identification of potential safety risks and enabling preventative maintenance or repair before anomalies escalate into serious failures. Analyzing the spatial data of the first heating network grids at specific safety levels (i.e., target safety levels) determines the spatial location of each grid, allowing for rapid and accurate location of abnormal areas, thus shortening response time and improving maintenance efficiency. Determining the relative distance between every two grids provides a more precise understanding of their spatial relationships, facilitating the assessment of heat transfer efficiency and heat loss risk, and enabling more precise thermal planning and optimization. Finally, multiple second heating network grids with relative distances less than or equal to preset relative distances are identified from the first grids for further analysis and optimization, thereby improving the management efficiency of the heating network. Analyzing real-time and historical operating data from multiple secondary heating network grids helps determine the primary heat demand pattern and primary heating capacity. This allows for the prediction of heat demand based on actual usage patterns, thereby optimizing heating planning, reducing energy waste, and improving energy efficiency. Furthermore, analyzing the primary heat demand pattern and primary heating capacity helps identify multiple target heating network grids with complementary heat energy relationships, along with their corresponding target heat demand patterns and target heating capacities. This enhances the flexibility and efficiency of heating network management by coordinating the heating capacities of different grids to balance the overall heat load of the heating network. Grouping the target heating network grids and performing safety management operations based on their safety levels, target heat demand patterns, and target heating capacities enables more refined safety management. This ensures that the heating network maintains a high level of safety performance while operating at its optimal level, thus solving the technical problem of low safety management efficiency in related technologies and achieving the technical effect of improving the safety management efficiency of heating networks.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the operational data and historical operational data of multiple second heating network grids in the first real-time monitoring data are analyzed to determine the first heat demand pattern and first heating capacity of the multiple second heating network grids. Specifically, this includes: analyzing the operational data and historical operational data of multiple second heating network grids in the first real-time monitoring data according to a preset time series to determine the target heat supply, target heating range, and target heat consumption of the multiple second heating network grids under the preset time series; determining the first heat demand pattern and first heating capacity of the multiple second heating network grids under the preset time series based on the target heat supply and target heat consumption, wherein the preset time series includes different time periods of any day in the target period, and the target period is the duration of any one of the four seasons of spring, summer, autumn, and winter.

[0009] By adopting the above technical solution and comprehensively analyzing real-time monitoring data and historical operating data, the target heat supply, target heating range, and target heat consumption of multiple secondary heating network grids under specific preset time series can be determined. This allows for accurate prediction of the heat demand and heating capacity of the heating network in different time periods and seasons, enabling the pre-adjustment and optimization of heating network operation strategies to meet changing energy demands while improving energy efficiency and reducing energy waste. After determining the target heat supply and target heat consumption of multiple secondary heating network grids, the primary heat demand pattern and primary heating capacity of each grid under the preset time series can be identified. This allows for the identification of heat demand fluctuations and heating response capabilities of each secondary heating network grid at different time points and seasons, thereby enabling better coordination and scheduling of heating resources and improving the response speed and adaptability of the heating network. This not only improves the heating quality and satisfaction of users but also enhances the energy utilization rate of the entire heating network by avoiding overheating or underheating.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, a first heat demand pattern and a first heating capacity of multiple second heating network grids under a preset time series are determined based on the target heat supply and target heat consumption. Specifically, this includes: determining the first heat supply, first heating range, and first heat consumption of each second heating network grid during the peak period of any day in the target period; and determining the second heat supply, second heating range, and second heat consumption of each second heating network grid during the off-peak period of any day in the target period. The peak period is defined as the time period in the preset time series where the heat consumption is greater than or equal to the preset heat consumption, and the second peak period is defined as the time period in the preset time series where the heat consumption is less than the preset heat consumption. The heat supply includes a first heat supply and a second heat supply, the target heating range includes a first heating range and a second heating range, and the target heat consumption includes a first heat consumption and a second heat consumption. Based on the first heat supply, the first heating range, and the first heat consumption, a second heat demand pattern and a second heating capacity are determined for each second heating network grid during the peak period of any day in the target cycle. Based on the second heat supply, the second heating range, and the second heat consumption, a third heat demand pattern and a third heating capacity are determined for each second heating network grid during the off-peak period of any day in the target cycle. The first heat demand pattern includes the second heat demand pattern and the third heat demand pattern, and the first heating capacity includes the second heating capacity and the third heating capacity.

[0011] By adopting the above technical solution, the first heating capacity, first heating range, and first heating consumption of each second heating network grid during the peak period of any day in the target cycle are determined to assess the heating capacity during the period of maximum heat load demand. The second heating capacity, second heating range, and second heating consumption of each second heating network grid during the off-peak period of any day in the target cycle are also determined to assess the energy utilization efficiency during off-peak periods. This allows for the rational allocation of heating resources, ensuring sufficient heating during peak periods and energy savings during off-peak periods. Through precise control of peak and off-peak periods, overall energy consumption can be reduced. The first heating supply, first heating range, and first heating consumption during peak hours determine the second heating demand pattern and second heating capacity to reflect the heating status under maximum demand. Based on the second heating supply, second heating range, and second heating consumption during off-peak hours, a third heating demand pattern and third heating capacity are determined to adapt to the heating status during low-demand periods. This enhances the regulation capacity of the heating network, enabling it to flexibly adjust the heating status according to actual demand, ensuring that different user heating needs are met during both peak and off-peak periods. By adjusting the heating capacity, the stability and reliability of the system under different demand patterns are enhanced. Through dynamic management of the heating network, heating supply and consumption are adjusted at different times to achieve high efficiency and energy saving.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the first heat demand pattern and first heating capacity of multiple second heating network grids are analyzed to determine multiple target heating network grids with complementary heat energy relationships and the target heat demand pattern and target heating capacity of the multiple target heating network grids. Specifically, this includes: analyzing the second heat demand pattern and second heating capacity of each second heating network grid to determine multiple third heating network grids with first complementary heat energy relationships and the fourth heat demand pattern and fourth heating capacity of the multiple third heating network grids; and analyzing the third heat demand pattern and third heating capacity of each second heating network grid to determine multiple target heating network grids with complementary heat energy relationships. The target heat network grids include multiple fourth heat network grids and multiple fourth heat network grids with complementary relationships, and the fifth heat demand pattern and fifth heating capacity of the target heat network grids. The multiple target heat network grids include multiple third heat network grids and multiple fourth heat network grids. The target heat demand pattern includes the fourth heat demand pattern and the fifth heat demand pattern. The target heating capacity includes the fourth heating capacity and the fifth heating capacity. The heat energy complementarity relationship includes the first heat energy complementarity relationship and the second heat energy complementarity relationship. The first heat energy complementarity relationship indicates that there is a heat energy complementarity relationship between any two third heat network grids in the multiple second heat network grids during the peak period of any day in the target period. The second heat energy complementarity relationship indicates that there is a heat energy complementarity relationship between any two fourth heat network grids in the multiple second heat network grids during the off-peak period of any day in the target period.

[0013] By employing the aforementioned technical solutions, analyzing the second heat demand pattern and second heating capacity of each second heating network grid helps identify multiple third heating network grids with a first heat energy complementarity during peak periods. This allows for the identification of the fourth heat demand pattern and fourth heating capacity of these third heating network grids. By identifying and utilizing these complementarities, heat energy distribution can be optimized across grids during peak heat demand periods, improving the overall operating efficiency and reliability of the heating network, reducing energy waste, and ensuring the continuity and stability of heat supply. Similarly, analyzing the third heat demand pattern and third heating capacity of the second heating network grids helps identify fourth heating network grids with a second heat energy complementarity during off-peak periods. This allows for the identification of the fifth heat demand pattern and fifth heating capacity of these grids, enabling adjustments to heat energy distribution during off-peak periods. By transferring excess heat energy from one grid to another that requires it, the overall heat energy utilization rate of the heating network can be optimized, reducing heat loss due to uneven heating. Through this hierarchical and time-based analysis, the operation of the heating network can become more flexible, ensuring the safe operation of the heating network while ensuring the balance of heat supply and demand in different time periods.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, multiple target heating network grids are identified as a target heating network grid group, and safety management operations are performed on the target heating network grid group according to the target safety level, target heat demand pattern, and target heating capacity. Specifically, this includes: collecting second real-time monitoring data of the target heating network grid group according to the target safety level; and, if it is determined from the second real-time monitoring data that there is an abnormally operating fifth heating network grid in the target heating network grid group, sending a first message to multiple normally operating sixth heating network grids in the target heating network grid group to instruct the multiple sixth heating network grids to supply heat energy to the fifth heating network grid according to the sixth demand pattern and the sixth heating capacity, wherein the sixth demand pattern is the current heat demand pattern of the multiple sixth heating network grids, and the sixth heating capacity is the current heating capacity of the multiple sixth heating network grids.

[0015] By adopting the above technical solution, based on the target safety level, the second real-time monitoring data of the heating network grid group is collected, effectively ensuring the reliability of the second real-time monitoring data. This enables timely detection of anomalies, allowing for rapid response and further prevention of potential anomalies, thus reducing safety risks. When the second real-time monitoring data shows that there is an abnormally operating fifth heating network grid in the target heating network grid group, a first message is sent to multiple normally operating sixth heating network grids, instructing them to supply heat energy to the abnormal grid (i.e., the fifth heating network grid) according to their respective sixth demand patterns and sixth heating capacities. By assessing available heat energy resources and redistributing them from normal grids to where they are needed, the continuous operation of the heating network is ensured. This ensures that even if individual grids have problems, other grids can supplement the heating supply, protecting users from disruption. Through intelligent scheduling, efficient resource utilization is achieved, resource waste is avoided, and the overall anti-interference capability of the heating network is enhanced, enabling it to maintain stable operation even when some components fail. The emergency response and heat energy allocation process based on real-time monitoring data firstly ensures the safety of system operation through real-time monitoring, and secondly, immediately activates the emergency plan when an anomaly is detected, supplementing the heat energy demand of the affected grid through the normally operating grid, thereby improving the reliability, stability and safety of the heating network and ensuring the continuity of heating services for users.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after sending a first message to multiple sixth heating network grids operating normally in the target heating network grid group based on second real-time monitoring data, the above method further includes: upon receiving a first response message from multiple sixth heating network grids, determining, based on the first response message, that the current heating capacity of the sixth heating network grid is insufficient, wherein the first response message is feedback of the first message; sending a second message to multiple seventh heating network grids of a first safety level to instruct the multiple seventh heating network grids to supply heat energy to the fifth heating network grid according to a seventh demand mode and a seventh heating capacity, wherein the first safety level is greater than the target safety level, the seventh demand mode is the current heat demand mode of the multiple seventh heating network grids, and the seventh heating capacity is the current heating capacity of the multiple seventh heating network grids.

[0017] By adopting the above technical solution, after receiving the first response messages from multiple sixth-level heating network grids (which are feedback messages from multiple sixth-level heating network grids to the previously sent first messages), it is determined based on the first response messages that the current heating capacity of multiple sixth-level heating network grids is insufficient to meet the demand. Adjustments can be made based on real-time feedback to ensure that the heating capacity matches the demand. Timely identification of insufficient heating capacity can prevent a wider range of service interruptions. After confirming that multiple sixth-level heating network grids cannot meet the heating demand, a second message is sent to the seventh-level heating network grids with a higher safety level, instructing multiple seventh-level heating network grids to supply heat energy to the abnormal grid (i.e., the fifth-level heating network grid) according to their respective seventh demand mode and seventh heating capacity. By mobilizing the higher-level heating network grids, it is ensured that the fifth-level heating network grid can receive the necessary heat energy supplementation, thereby improving the response capability of the heating network to abnormal situations and ensuring that the stability of the entire heating network is not excessively affected by a single failure point. By distinguishing between heating network grids with different safety levels, more important or higher-risk heating problems can be addressed first. The emergency response process for detecting insufficient heating capacity in the sixth heating network grid involves assessing heating capacity by receiving feedback messages, and upgrading the safety level when insufficient capacity is confirmed. This mobilizes grids with higher safety levels to supplement heat energy, thereby ensuring the heat energy supply of the fifth heating network grid, improving the reliability of the heating system, optimizing resource allocation, and strengthening the response mechanism to emergencies.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, a safety assessment is performed on the first real-time monitoring data of multiple heating network grids in the heating network according to a preset safety standard to determine the safety level of the multiple heating network grids. Specifically, this includes: comparing the first real-time monitoring data with the preset safety standard to obtain a comparison result; and if it is determined from the comparison result that multiple heating network grids do not meet the preset safety standard, a safety assessment is performed on the multiple heating network grids to determine the safety level of the multiple heating network grids.

[0019] By adopting the above technical solution, the first real-time monitoring data is compared with the preset safety standards to determine whether the first real-time monitoring data is within the normal operating range. The comparison result indicates whether each heating network grid meets the preset safety standards. Heating network grids that do not meet the safety standards can be identified immediately, and timely measures can be taken to prevent accidents or failures that may be caused by operating conditions exceeding the safety standards. When the comparison results show that there are heating network grids that do not meet the preset safety standards, a safety assessment is conducted on these heating network grids. The safety assessment determines the safety level of each heating network grid, involving further analysis of potential risks and classification of risk levels. According to the determined safety level, corresponding risk management measures are implemented for the heating network grids. Establishing different safety levels for heating network grids helps to manage resources in a hierarchical manner, prioritize high-risk areas, and take corresponding intervention measures according to the safety level, making the intervention more precise and effective. The overall safety of the heating network is improved, and potential safety accidents are reduced through targeted assessment and intervention.

[0020] Secondly, embodiments of this application provide a safety management device for a heating network. The device includes: an evaluation module, configured to perform a safety evaluation on first real-time monitoring data of multiple heating network grids in a heating network according to preset safety standards, to determine the safety level of the multiple heating network grids; a first analysis module, configured to analyze the spatial data of the multiple first heating network grids with a target safety level in the first real-time monitoring data, to determine the spatial location of each of the multiple first heating network grids, wherein the safety level includes a target safety level, and the multiple heating network grids include multiple first heating network grids; a first determination module, configured to determine the relative distance between every two first heating network grids in the multiple first heating network grids based on their spatial locations; and a second determination module, configured to determine multiple second heating network grids from the multiple first heating network grids whose relative distance is less than or equal to a preset relative distance, wherein the multiple first heating network grids include multiple second heating network grids; The second analysis module analyzes the operational data and historical operational data of multiple second heating network grids in the first real-time monitoring data to determine the first heat demand pattern and first heating capacity of the multiple second heating network grids. Each second heating network grid has a one-to-one correspondence between its first heat demand pattern and first heating capacity. The third analysis module analyzes the first heat demand pattern and first heating capacity of the multiple second heating network grids and identifies multiple target heating network grids with complementary heat energy relationships, as well as their target heat demand patterns and target heating capacities. The first heat demand pattern includes the target heat demand pattern, and the first heating capacity includes the target heating capacity. The execution module identifies the multiple target heating network grids as a target heating network grid group and performs safety management operations on the target heating network grid group based on the target safety level, target heat demand pattern, and target heating capacity.

[0021] Thirdly, embodiments of this application provide an electronic device comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, and the one or more processors invoking the computer instructions to cause the electronic device to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on an electronic device, cause the electronic device to perform the method described in the first aspect and any possible implementation thereof.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. It solves the technical problem of low safety management efficiency of heating pipe networks in related technologies, and achieves the technical effect of improving the safety management efficiency of heating pipe networks.

[0024] 2. It can identify fluctuations in heat demand and heating response capabilities of each secondary heating network grid at different times and seasons, thereby enabling better coordination and scheduling of heating resources and improving the response speed and adaptability of the heating network. This not only improves the heating quality and satisfaction of users, but also enhances the energy utilization rate of the entire heating network by avoiding overheating or underheating.

[0025] 3. Based on the first heating capacity, first heating range, and first heating consumption during peak hours, determine the second heating demand pattern and second heating capacity to reflect the heating status under maximum demand. Based on the second heating capacity, second heating range, and second heating consumption during off-peak hours, determine the third heating demand pattern and third heating capacity to adapt to the heating status during low-demand periods. This enhances the regulation capacity of the heating network, enabling it to flexibly adjust the heating status according to actual needs. It ensures that different heating needs of users can be met during both peak and off-peak hours. By adjusting the heating capacity, the stability and reliability of the system under different demand patterns are enhanced. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating the safety management method for a heating network in an embodiment of this application. Figure 2 This is a structural block diagram of a safety management device for a thermal pipeline network provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. Detailed Implementation

[0027] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0028] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0029] This application provides a safety management method for heating pipe networks, see reference. Figure 1 , Figure 1 This is a flowchart illustrating the safety management method for a heating network in an embodiment of this application, including the following steps: Step S101: Conduct a safety assessment on the first real-time monitoring data of multiple heating network grids in the heating network according to preset safety standards, so as to determine the safety level of multiple heating network grids; In the above embodiments, the preset safety standards can be pre-set, and after being pre-set, they can be adjusted according to actual application needs. The methods for setting preset safety standards include, but are not limited to, industry safety standards, historical data analysis, and risk assessment. Industry standards refer to standards and guidelines issued by industry associations or regulatory agencies; historical data analysis involves analyzing historical accidents, failures, and operational data to determine the threshold for safety standards, using statistical methods to extract information from past performance and accident records; risk assessment involves identifying potential risk points and setting corresponding safety standards based on the risk level. It should be noted that the examples of setting preset safety standards described above are merely exemplary embodiments, and the methods for setting preset safety standards are not limited to the examples given above.

[0030] In the above embodiments, the first real-time monitoring data can be key operating parameters from various grid points, reflecting the real-time operating status of the pipeline network. The first real-time monitoring data includes, but is not limited to, the water or steam temperature in the pipeline network, ambient temperature, operating pressure within the pipeline network, pressure difference at various points in the pipeline network, flow rate or velocity of the heat transfer fluid (e.g., water or steam), flow rate at the pipeline network inlet and outlet, water quality parameters in the pipeline network (e.g., pH, hardness, oxygen content), energy consumption of the heating pipeline network (e.g., heat supply, electricity consumption), vibration level of the pipeline network and its components, noise level generated during operation, corrosion monitoring of the pipeline network and its components, detection of potential leaks in the pipeline network, operating status of key equipment such as pumps and valves, and environmental factors affecting the pipeline network (e.g., humidity, temperature difference, geological conditions). It should be noted that the above examples of the first real-time monitoring data are merely exemplary embodiments, and the first real-time monitoring data is not limited to the examples described above.

[0031] In the above embodiments, different safety levels can be set according to the degree of safety and risk, and corresponding countermeasures, during the monitoring and evaluation of the heating network. The classification of safety levels includes, but is not limited to, normal operation level (all monitoring parameters are within the preset safety range, the heating network is operating stably, and no special intervention is required), attention level (one or more monitoring parameters are approaching the boundary of the preset safety range, requiring continuous monitoring and possible preventative maintenance), warning level (one or more monitoring parameters exceed the preset safety range, but have not yet reached a critical level, requiring immediate measures to correct or reduce the risk), danger level (critical parameters show serious safety hazards, requiring immediate emergency measures to prevent accidents), and critical / emergency level (a serious failure occurs in the entire or part of the heating network, directly threatening the safety of personnel and equipment, requiring emergency shutdown or evacuation). The exact naming and number of safety levels may vary; the key is to ensure that each level has a clear parameter range and corresponding response measures. It should be noted that the above examples of the classification of preset safety levels are merely exemplary embodiments, and the classification of preset safety levels is not limited to the examples described above.

[0032] Step S102: Analyze the spatial data of multiple first heating network grids with target safety levels in the first real-time monitoring data to determine the spatial location of each first heating network grid in the multiple first heating network grids, wherein the safety level includes the target safety level, and the multiple heating network grids include multiple first heating network grids; In the above embodiments, spatial data in thermal pipeline network grid analysis mainly refers to information related to grid location and physical layout. This data helps determine the exact location of the grid in the thermal pipeline network and its relative relationship with other grids in the thermal pipeline network. Spatial data includes, but is not limited to, coordinate data (geographic coordinates (latitude and longitude) of the grid or coordinates in a specific reference system, used to describe the precise location of the grid), elevation data (used to determine the height of the grid relative to sea level), layout map (a plan view or 3D model of the pipeline network, showing the physical layout and connection between grids), distance and relative position (distance between grids, and their position relative to important reference points (e.g., heat sources, pumping stations, distribution nodes, etc.)), pipe diameter and pipe direction (the diameter and flow direction of each pipe segment in the pipeline network, affecting the transmission efficiency of hot water or steam), equipment location information (the location of key equipment such as valves, pumps, and heat exchangers in the pipeline network), geographic information system data (which can be used to analyze factors related to network layout such as geographic features, land use, and building distribution), building and structure information (the layout of buildings and structures within the grid coverage area, which may affect heat demand and distribution), topography and geomorphology data (topographic relief and geomorphological features, which may affect the laying and operation of the pipeline network), and field survey data (information such as grid location, soil type, and groundwater level obtained through field surveys). It should be noted that the above examples of spatial data are merely exemplary embodiments, and the spatial data is not limited to the examples described above.

[0033] Step S103: Determine the relative distance between every two first heating pipe network grids in the multiple first heating pipe network grids based on their spatial location; In the above embodiments, after determining the relative distance between every two first thermal pipeline grids, the first thermal pipeline grids within a certain range can be divided into a group based on the relative distance, so as to facilitate subsequent safety management.

[0034] Step S104: Determine a plurality of second thermal pipeline grids from a plurality of first thermal pipeline grids whose relative distance is less than or equal to a preset relative distance, wherein the plurality of first thermal pipeline grids includes a plurality of second thermal pipeline grids; In the above embodiments, the preset relative distance can be set in advance, and after the preset relative distance is set in advance, it can be adjusted according to actual application needs, etc., which is not limited here.

[0035] Step S105: Analyze the operational data and historical operational data of multiple second heating network grids in the first real-time monitoring data to determine the first heat demand pattern and first heating capacity of multiple second heating network grids, wherein the first heat demand pattern and first heating capacity of each second heating network grid have a one-to-one correspondence. In the above embodiments, historical operating data is very important in analyzing the heat demand patterns and heating capacity of the second heating network grid. This data usually contains detailed records of the grid operation over a period of time, which can help analyze and predict future operating trends and demand patterns. Historical operational data includes, but is not limited to, temperature records (historical temperature data of fluids within the pipe network, including supply and return water temperatures), flow records (historical flow data, i.e., the flow rate of hot water or steam in the pipe network), pressure records (historical pressure data of each grid within the heating pipe network), energy consumption data (energy consumption data during the operation of the heating pipe network), fault and maintenance records (faults, maintenance activities, and repair history that occurred during the operation of the heating pipe network), operation logs (records of operations performed by operators on the heating pipe network, including valve switching, pump station start-up and shutdown, etc.), weather data (historical weather data affecting heat demand, such as air temperature, wind speed, and sunshine duration), heat load data (historical heat load data of the area served by the heating pipe network grid, reflecting changes in heat demand), user behavior (user behavior patterns, such as differences in heat usage between holidays and weekdays), and heating pipe network configuration change records (historical records of any changes to the configuration or layout of the heating pipe network, such as network expansion or renovation). Through comprehensive analysis of this historical operational data, the heat demand patterns and heating capacity of each secondary heating pipe network grid can be determined. For example, statistical analysis, machine learning models, or other data analysis methods can be used to identify periodic patterns, trends, and anomalies in heat demand, and accordingly optimize the heating system to improve efficiency and reliability. It should be noted that the examples of historical operating data described above are merely illustrative embodiments, and the historical operating data described is not limited to the examples given.

[0036] In the above embodiments, the first heat demand pattern refers to the heating demand characteristics of the heating network grid under different times and conditions. These patterns reflect the patterns of user demand for heat energy and may be affected by various factors such as season, climate, time, and user behavior. The first heat demand pattern includes, but is not limited to, seasonal patterns (significant differences in heat demand between winter and summer, with demand typically higher in winter); diurnal variation patterns (heat demand varies at different times of the day, such as wake-up time in the morning, working hours during the day, and rest time at night); weekly variation patterns (heat demand may differ significantly between weekdays and weekends); climate influence patterns (the impact of changes in climate conditions such as temperature, humidity, and wind speed on heat demand); user behavior patterns (the impact of user behavior such as residents' living habits and urban building work patterns on heat demand); holiday patterns (heat demand may differ due to changes in people's living habits during holidays); special event patterns (e.g., sporting events, large conferences, etc., may temporarily increase heat demand in a certain area); economic activity patterns (differences in heat demand between industrial areas, commercial areas, and residential areas); and long-term trend patterns (heat demand may show a long-term upward or downward trend due to urban development, population growth, or the implementation of energy-saving measures). By analyzing real-time monitoring data and historical operational data, these heat demand patterns can be identified, and the operation of the heating system can be optimized based on these patterns. For example, the heating capacity can be adjusted to match changes in heat demand, thereby improving energy efficiency and user satisfaction. It should be noted that the example of the first heat demand pattern described above is merely an exemplary embodiment, and the first heat demand pattern is not limited to the example given.

[0037] Step S106: Analyze the first heat demand pattern and first heating capacity of multiple second heat network grids to determine multiple target heat network grids with complementary heat energy relationships and the target heat demand pattern and target heating capacity of multiple target heat network grids. The first heat demand pattern includes the target heat demand pattern, and the first heating capacity includes the target heating capacity. In the above embodiments, when analyzing the operational data of the thermal network grid, in addition to considering the complementary relationship of thermal energy, redundancy, coordination, sequence, priority, exchange, maintenance, and upgrade relationships can also be considered. Redundancy refers to the availability of backup heating capacity in the thermal network. When the heating capacity of a certain part of the thermal network grid decreases or fails, other parts of the thermal network grid can provide the necessary thermal energy to maintain system operation. Coordination refers to the mutual support between different grids during operation. For example, when the heating demand of one grid is lower than its heating capacity, excess thermal energy can be transferred to a grid with higher demand. Sequential relationships refer to the possibility that certain grids may need to supply thermal energy in a specific order. For example, in a large thermal system... The start-up and shutdown of heating in certain grids may need to be sequenced based on their position and role within the overall thermal grid; priority relationships refer to the fact that in cases of insufficient heat supply, certain grids may be given higher priority based on the urgency or importance of heat demand, such as critical facilities like hospitals and schools; regulation relationships refer to the fact that different grids may have different regulation capabilities, i.e., the ability to adjust heating supply when demand fluctuates, and some grids may be more suitable as regulating heat sources to respond to instantaneous demand changes; exchange relationships refer to the fact that in some systems, there may be heat exchange mechanisms between grids, allowing grids to exchange heat energy under specific conditions, thereby improving overall efficiency; maintenance and upgrade relationships refer to the fact that the maintenance and upgrade plans of the pipeline grid may affect its heating capacity and demand patterns.

[0038] Step S107: Multiple target heating network grids are identified as target heating network grid groups, and safety management operations are performed on the target heating network grid groups according to the target safety level, target heat demand pattern, and target heating capacity.

[0039] In the above embodiments, the target safety level corresponding to the target thermal pipeline network group can be used as the index of the group, so that the corresponding group can be detected through the safety level in subsequent continuous monitoring.

[0040] Through the above steps, a safety assessment is performed on the first real-time monitoring data of multiple heating network grids according to preset safety standards. This enables real-time safety assessment of multiple heating network grids, allowing for timely identification of potential safety risks and enabling preventative maintenance or repair before anomalies escalate into serious failures. Analyzing the spatial data of the first heating network grids at a specific safety level (i.e., the target safety level) determines the spatial location of each grid, allowing for rapid and accurate location of abnormal areas, thus shortening response time and improving maintenance efficiency. Determining the relative distance between every two grids provides a more precise understanding of their spatial relationships, facilitating the assessment of heat transfer efficiency and heat loss risk, and enabling more precise thermal planning and optimization. Finally, multiple second heating network grids with relative distances less than or equal to preset relative distances are identified from the first grids for further analysis and optimization, thereby improving the management efficiency of the heating network. Real-time and historical operational data from multiple secondary heating network grids are used to determine the primary heat demand pattern and primary heating capacity. This enables the prediction of heat demand based on actual usage patterns, thereby optimizing heating planning, reducing energy waste, and improving energy efficiency. Analysis of the primary heat demand pattern and primary heating capacity identifies multiple target heating network grids with complementary heat energy relationships, along with their corresponding target heat demand patterns and target heating capacities. This enhances the flexibility and efficiency of heating network management by coordinating the heating capacities of different grids to balance the overall heat load of the heating network. Grouping the target heating network grids and performing safety management operations based on their safety levels, target heat demand patterns, and target heating capacities allows for more refined safety management. This ensures that the heating network maintains a high level of safety performance while operating at its optimal level, thus solving the technical problem of low safety management efficiency in related technologies and achieving the technical effect of improving the safety management efficiency of heating networks.

[0041] The entity performing the above steps can be a system, such as a heating network safety monitoring system, a heating network safety monitoring device, a processing device, a controller, or a processor, but is not limited to these.

[0042] In an optional embodiment, the operational data and historical operational data of multiple second heating network grids in the first real-time monitoring data are analyzed to determine the first heat demand pattern and first heating capacity of the multiple second heating network grids. Specifically, this includes: analyzing the operational data and historical operational data of multiple second heating network grids in the first real-time monitoring data according to a preset time series to determine the target heat supply, target heating range, and target heat consumption of the multiple second heating network grids under the preset time series; determining the first heat demand pattern and first heating capacity of the multiple second heating network grids under the preset time series based on the target heat supply and target heat consumption, wherein the preset time series includes different time periods of any day in the target period, and the target period is the duration of any one of the four seasons of spring, summer, autumn, and winter.

[0043] In the above embodiments, the preset time series refers to the pre-setting of time points or time periods during the data analysis process, so as to conduct orderly analysis of the operational data of the second heating network grid. There are various ways to set the preset time series, such as: fixed interval series, where data is collected at fixed time intervals, such as hourly, daily, weekly, etc.; working / non-working time series, where different time series are set according to different working days and non-working days (e.g., weekends and holidays) to reflect heat demand under different working conditions; seasonal time series, where different time series are set according to the temperature characteristics of the four seasons (spring, summer, autumn, and winter) to capture the impact of seasonal changes on heating demand; peak-valley time series, where different time series are set according to the peak and off-peak heating periods within a day or week to analyze and predict heating conditions during periods of high and low demand; and climate-driven series, based on... Time series can be set based on changes in climate conditions (e.g., temperature, humidity), such as starting data collection when the temperature drops to a certain threshold; event-driven sequences, which are time series triggered by specific events, such as data collection during equipment failure, maintenance, or other operational changes; random / non-fixed interval sequences, where data collection is not performed at fixed intervals but based on some random or condition-driven mechanism, which may be more suitable for analyzing irregular changes; demand-driven sequences, which set time series based on changes in heating demand, such as increasing the frequency of data collection when demand increases or decreases rapidly; and custom sequences, where the start point, end point, and interval of the time series are customized according to specific analytical needs or forecasting purposes. It should be noted that the above examples of preset time series are merely exemplary embodiments, and the preset time series are not limited to the examples described above.

[0044] In an optional embodiment, a first heat demand pattern and a first heating capacity of multiple second heating network grids under a preset time series are determined based on the target heat supply and target heat consumption. Specifically, this includes: determining the first heat supply, first heating range, and first heat consumption of each second heating network grid during the peak period of any day in the target period; and determining the second heat supply, second heating range, and second heat consumption of each second heating network grid during the off-peak period of any day in the target period. The peak period is defined as the time period in the preset time series where the heat consumption is greater than or equal to the preset heat consumption, and the target heat supply includes the first... The system comprises a first heating supply and a second heating supply, a target heating range including the first heating range and the second heating range, and a target heat consumption including the first heat consumption and the second heat consumption. Based on the first heating supply, the first heating range, and the first heat consumption, the system determines a second heat demand pattern and a second heating capacity for each second heating network grid during the peak period of any day in the target cycle. Furthermore, based on the second heating supply, the second heating range, and the second heat consumption, the system determines a third heat demand pattern and a third heating capacity for each second heating network grid during the off-peak period of any day in the target cycle. The first heat demand pattern includes both the second and third heat demand patterns, and the first heating capacity includes both the second and third heating capacities.

[0045] In the above embodiments, one example is provided to illustrate how to determine the heat demand pattern and heating capacity of the second heating network grid under a preset time series based on the target heat supply and target heat consumption: Step 1, collect real-time monitoring data and historical operation data of each second heating network grid, and set the preset time series as weekdays and non-weekdays, as well as the peak and off-peak periods of each day. For example, the peak period on weekdays is from 6:00 to 9:00 am (of course, it can also be from 5:00 to 8:00 am, 6:00 to 8:00 am, 5:00 to 9:00 am, etc., which will not be specified here). The hours are limited to 17:00 to 21:00 (but can also be 18:00 to 21:00, 17:00 to 22:00, 18:00 to 22:00, etc., which are not limited here), and off-peak hours are 9:00 to 17:00 (but can also be 8:00 to 17:00, 8:00 to 18:00, 9:00 to 18:00, etc., which are not limited here) and 21:00 to 6:00 the next day (but can also be 21:00 to 5:00 the next day, 22:00). (The timeframes are not limited to 5:00 AM to 6:00 AM the next day, etc.). Step 2: Determine the target heat supply and target heat consumption for each heating network grid. This may be based on past data analysis, weather forecasts, user behavior patterns, etc. Step 3: For each heating network grid, calculate the first heat supply, the first heating range, and the first heat consumption based on the peak time period in the preset time series. For each heating network grid, calculate the second heat supply, the second heating range, and the second heat consumption based on the low time period in the preset time series. The division of peak and low time periods... Step 4 is based on whether the heat consumption is greater than or equal to (for peak) or less than (for off-peak) a preset heat consumption threshold; Step 5 is to use the first heat supply, the first heating range and the first heat consumption during the peak period to determine the second heat demand pattern and the second heating capacity of each grid during the peak period, and to use the second heat supply, the second heating range and the second heat consumption during the off-peak period to determine the third heat demand pattern and the third heating capacity of each grid during the off-peak period. The first heat demand pattern includes the second heat demand pattern and the third heat demand pattern, and the first heating capacity includes the second heating capacity and the third heating capacity.

[0046] In the above embodiment, steps 1-4 are specifically implemented as follows: Assume there are three second thermal network grids A, B, and C. Grid A has a peak-hour first heating capacity of 100 GWh (which could also be 90 GWh, 95 GWh, 110 GWh, etc., without limitation here), a first heating range of 90-110 GWh (which could also be 90-100 GWh, 95-100 GWh, 95-110 GWh, etc., without limitation here), and a first heat consumption of 95 GWh (which could also be 90 GWh, 100 GWh, 105 GWh, etc., without limitation here). During off-peak hours, the second heating capacity is set to 50 GWh (which could also be 40 GWh, 45 GWh, 55 GWh, etc., without limitation here), and the second heating range is 45-55 GW. h (which could also be 40-50GWh, 45-50GWh, 40-55GWh, etc., not limited here), the second heat consumption is 48GWh (which could also be 43GWh, 50GWh, 52GWh, etc., not limited here); Grid B, the first heat supply during peak hours is set to 120GWh (which could also be 115GWh, 125GWh, 130GWh, etc., not limited here), the first heat supply range is 110-130GWh (which could also be 110-125GWh, 115-125GWh, 115-130GWh, etc., not limited here), the first heat consumption is 115GWh (which could also be... For grid C, the primary heating capacity during off-peak hours is set at 60 GWh (or 55 GWh, 65 GWh, 70 GWh, etc., without limitation), with a range of 55-65 GWh (or 50-55 GWh, 55-60 GWh, 50-65 GWh, etc., without limitation), and a secondary heating consumption of 58 GWh (or 54 GWh, 60 GWh, 63 GWh, etc., without limitation). (etc., not limited here) The first heating range is 70-90GWh (of course, it can also be 75-85GWh, 70-85GWh, 80-90GWh, etc., not limited here), the first heat consumption is 75GWh (of course, it can also be 70GWh, 80GWh, 85GWh, etc., not limited here), the second heating during off-peak hours is set at 40GWh (of course, it can also be 35GWh, 45GWh, 50GWh, etc., not limited here), the second heating range is 35-45GWh (of course, it can also be 35-40GWh, 30-45GWh, 40-45GWh, etc., not limited here), and the second heat consumption is 38GWh.The heating capacity and heat demand pattern of each grid are determined based on the heat supply and consumption during peak and off-peak periods. In practice, this data is used to optimize heating strategies, ensuring that users' heat needs are met at different times, while improving the system's energy efficiency and operational efficiency.

[0047] In an optional embodiment, the first heat demand pattern and first heating capacity of multiple second heating network grids are analyzed to determine multiple target heating network grids with complementary heat energy relationships and their target heat demand patterns and target heating capacities. Specifically, this includes: analyzing the second heat demand pattern and second heating capacity of each second heating network grid to determine multiple third heating network grids with first complementary heat energy relationships and their fourth heat demand pattern and fourth heating capacity; and analyzing the third heat demand pattern and third heating capacity of each second heating network grid to determine grids with second complementary heat energy relationships. The target heat network grids include multiple fourth heat network grids and multiple fourth heat network grids, with a fifth heat demand pattern and a fifth heating capacity. The multiple target heat network grids include multiple third heat network grids and multiple fourth heat network grids. The target heat demand patterns include fourth heat demand patterns and fifth heat demand patterns. The target heating capacity includes fourth heating capacity and fifth heating capacity. The heat energy complementarity relationship includes a first heat energy complementarity relationship and a second heat energy complementarity relationship. The first heat energy complementarity relationship indicates that any two third heat network grids in the multiple second heat network grids have a heat energy complementarity relationship during the peak period of any day in the target cycle. The second heat energy complementarity relationship indicates that any two fourth heat network grids in the multiple second heat network grids have a heat energy complementarity relationship during the off-peak period of any day in the target cycle.

[0048] The above embodiments involve the complementary analysis and optimization process between heating network grids. The aim is to improve the overall thermal efficiency of the heating network by identifying and utilizing the complementary capabilities of different grids during peak and off-peak periods. Assuming the need to manage a city's heating network, which consists of multiple heating network grids, the goal is to optimize the operation of these grids to ensure efficient fulfillment of heat demand at different times. The specific implementation steps are as follows: First, determine the data for each second heating network grid, including but not limited to the heat demand data (i.e., the second and third heat demand patterns) and the heating data (i.e., the second and third heating capacities) of each grid. Analyze this data to determine which grids have a first thermal energy complementarity relationship during peak periods (e.g., morning and evening), and identify multiple third heating network grids and their corresponding grids. The corresponding fourth heat demand pattern and fourth heating capacity are identified. The same analysis also applies to off-peak periods (e.g., nighttime), where grids support each other when demand is low. This identifies the fourth heating network grid with a second complementary heat energy relationship and its corresponding fifth heat demand pattern and fifth heating capacity. Once complementary grids are identified, optimization strategies can be implemented for these grids. This involves adjusting the heat supply of different grids according to the heat demand pattern and heating capacity. By optimizing the heat energy distribution between grids, overheating or underheating can be reduced, thereby better matching supply and demand and improving the safe operation efficiency of the entire heating network.

[0049] In an optional embodiment, multiple target heating network grids are identified as a target heating network grid group, and safety management operations are performed on the target heating network grid group according to the target safety level, target heat demand pattern, and target heating capacity. Specifically, this includes: collecting second real-time monitoring data of the target heating network grid group according to the target safety level; and, if it is determined from the second real-time monitoring data that there is an abnormally operating fifth heating network grid in the target heating network grid group, sending a first message to multiple normally operating sixth heating network grids in the target heating network grid group to instruct the multiple sixth heating network grids to supply heat energy to the fifth heating network grid according to the sixth demand pattern and the sixth heating capacity, wherein the sixth demand pattern is the current heat demand pattern of the multiple sixth heating network grids, and the sixth heating capacity is the current heating capacity of the multiple sixth heating network grids.

[0050] In the above embodiment, assuming a city heating system composed of multiple heating network grids, to ensure the safe operation of the system and effectively respond to sudden failures, the heating network monitoring system collects data according to a predetermined safety level and responds quickly when an anomaly is detected. The specific implementation steps are as follows: First, according to the set target safety level, second real-time monitoring data is collected from each heating network grid group. This data may include temperature, flow rate, pressure, and other important parameters that may affect the safe operation of the network. Second, the collected data is analyzed in real time to determine if any grid is experiencing abnormal operation. Anomalies may be caused by equipment failure, leakage, unexpected increased demand, or other factors. Third, if an abnormal operation is detected in a fifth heating network grid, an emergency response is automatically triggered. Fourth, the system sends signals to the normally operating grids. Multiple sixth-level heating network grids send a first message (alarm or notification) instructing them to supply heat to the malfunctioning fifth-level heating network grid according to their respective sixth-level demand patterns and sixth-level heating capacities. Upon receiving the first message, the sixth-level heating network grids adjust their operating status based on their current heating capacity and demand patterns to provide the necessary heat to the fifth-level heating network grid, potentially reducing heat supply to other or less urgent needs to ensure energy is redistributed where needed. After the fifth-level heating network grid receives the additional heat and begins to resume normal operation, its performance is continuously monitored to ensure the recovery meets safety standards. Once the fifth-level heating network grid is determined to be stable, all participating sixth-level heating network grids are notified to gradually return to normal heating patterns. This embodiment demonstrates how real-time monitoring and data analysis, along with automated emergency response, can maintain the safety and stability of a heating network, reducing heating interruptions due to faults and ensuring the continuity and reliability of heat supply.

[0051] In an optional embodiment, after sending a first message to multiple sixth heating network grids operating normally in the target heating network grid group based on the second real-time monitoring data, the method further includes: upon receiving a first response message from the multiple sixth heating network grids, determining that the current heating capacity of the sixth heating network grid is insufficient based on the first response message, wherein the first response message is a feedback of the first message; sending a second message to multiple seventh heating network grids of a first safety level to instruct the multiple seventh heating network grids to supply heat energy to the fifth heating network grid according to a seventh demand mode and a seventh heating capacity, wherein the first safety level is greater than the target safety level, the seventh demand mode is the current heat demand mode of the multiple seventh heating network grids, and the seventh heating capacity is the current heating capacity of the multiple seventh heating network grids.

[0052] In the above embodiments, assuming a hierarchical and responsive heating network monitoring system designed to optimize heating supply and provide support in case of anomalies, the specific implementation steps are as follows: A first message is sent to all sixth heating network grids (or possibly a single sixth heating network grid or a subset thereof, etc., not limited here), instructing the sixth heating network grids to provide available heating capacity to support the fifth heating network grid; upon receiving the request, the sixth heating network grid sends a first response message based on its current operating status and capacity, indicating its available heating capacity; all first response messages are aggregated to determine whether the total heating capacity provided by the sixth heating network grids is sufficient to meet the needs of the fifth heating network grid. The system addresses the following scenario: If the heating capacity of the sixth heating grid is determined to be insufficient, a second message is sent to the seventh heating grid, which has a higher safety level and typically more redundancy and greater heating capacity. Upon receiving the second message, the seventh heating grid assesses its current heat demand pattern and heating capacity, adjusting its operation to provide additional heat energy to the fifth heating grid. After the fifth heating grid begins receiving heat energy from the sixth and seventh grid groups, its performance and recovery progress are continuously monitored. Based on the recovery status of the fifth heating grid and the heating capacity of other grid groups, the emergency heating strategy is further adjusted to ensure balanced operation of all grids. This embodiment demonstrates a hierarchical and dynamic emergency response mechanism that ensures the heating network can quickly mobilize resources from different levels of safety grid groups when facing abnormal situations, guaranteeing the stability and security of heat supply.

[0053] In an optional embodiment, a safety assessment is performed on the first real-time monitoring data of multiple heating network grids in the heating network according to a preset safety standard to determine the safety level of the multiple heating network grids. Specifically, this includes: comparing the first real-time monitoring data with the preset safety standard to obtain a comparison result; and if it is determined from the comparison result that multiple heating network grids do not meet the preset safety standard, a safety assessment is performed on the multiple heating network grids to determine the safety level of the multiple heating network grids.

[0054] In the above embodiments, when comparing the first real-time monitoring data with the preset safety standards, the comparison results mainly reflect the degree of compliance between the current operating status of the heating network grid and the safety standards. These results can be multi-dimensional. For example, the comparison results are completely consistent, meaning that the monitoring data of the heating network grid meets or exceeds the preset safety standards at all detection points; the comparison results show a slight deviation, meaning that the monitoring data shows that the heating network grid slightly exceeds the safety limits at some detection points, but the deviation is within an acceptable range and does not affect the overall safety of the heating network; the comparison results show a moderate deviation, meaning that the monitoring data indicates that the performance of the heating network grid deviates from the safety standards at multiple detection points. Further evaluation and monitoring may be needed to determine if the deviation will gradually worsen; severe deviation in comparison results, where monitoring data shows one or more key performance indicators of the heating network grid significantly exceed safety standards, potentially posing immediate and direct risks to the operation of the heating network, requiring immediate emergency measures; inconsistent comparison results, where monitored data cannot be effectively compared with preset standards, possibly due to sensor failure, data loss, or communication errors; and safety margin, where monitoring data shows the heating network grid's performance not only meets safety standards but also has additional safety margins, indicating robust system operation and the ability to cope with sudden load increases or other unforeseen circumstances. In addition to the current degree of deviation, comparison results may also include performance trend information over time, such as stable performance, gradual improvement, or deterioration. After obtaining these comparison results, detailed safety assessments can be conducted on multiple heating network grids based on the different results to determine their safety levels. This assessment will help identify which grids may require maintenance, upgrades, or additional control measures in emergency situations.

[0055] In this embodiment of the application, the target heating network grid is grouped and safety management operations are performed according to its safety level, target heat demand pattern and target heating capacity to achieve more refined safety management and ensure that the heating network maintains a high level of safety performance while operating at its optimal level.

[0056] The safety management method for the heating network in the embodiments of this application has been described above. The safety management device for the heating network in the embodiments of this application will be described in detail below, in conjunction with the above-described safety management method for the heating network. (See reference...) Figure 2 , Figure 2 This is a structural block diagram of a safety management device for a heating network provided in an embodiment of this application. The device includes: Evaluation module 201 is used to perform a safety assessment on the first real-time monitoring data of multiple heating network grids in the heating network according to preset safety standards, so as to determine the safety level of the multiple heating network grids; The first analysis module 202 is used to analyze the spatial data of multiple first thermal pipeline grids with a target safety level in the first real-time monitoring data to determine the spatial location of each first thermal pipeline grid in the multiple first thermal pipeline grids, wherein the safety level includes the target safety level, and the multiple thermal pipeline grids include the multiple first thermal pipeline grids; The first determining module 203 is used to determine the relative distance between every two first thermal pipeline grids in the plurality of first thermal pipeline grids according to the spatial location; The second determining module 204 is used to determine from the plurality of first thermal network grids a plurality of second thermal network grids whose relative distance is less than or equal to a preset relative distance, wherein the plurality of first thermal network grids includes the plurality of second thermal network grids; The second analysis module 205 is used to analyze the operation data of the plurality of second heating network grids and the historical operation data of the plurality of second heating network grids in the first real-time monitoring data, so as to determine the first heat demand mode and the first heating capacity of the plurality of second heating network grids, wherein the first heat demand mode and the first heating capacity of each second heating network grid have a one-to-one correspondence. The third analysis module 206 is used to analyze the first heat demand pattern and the first heating capacity of the plurality of second heat pipe network grids, so as to determine a plurality of target heat pipe network grids with complementary heat energy relationships and the target heat demand pattern and target heating capacity of the plurality of target heat pipe network grids from the plurality of second heat pipe network grids, wherein the first heat demand pattern includes the target heat demand pattern and the first heating capacity includes the target heating capacity; The execution module 207 is used to determine the plurality of target heating network grids as a target heating network grid group, and to perform safety management operations on the target heating network grid group according to the target safety level, the target heat demand pattern and the target heating capacity.

[0057] In an optional embodiment, the second analysis module 205 includes: a first analysis unit, configured to analyze the operational data of the plurality of second heating network grids and the historical operational data of the plurality of second heating network grids in the first real-time monitoring data according to a preset time series, so as to determine the target heat supply, target heat supply range, and target heat consumption of the plurality of second heating network grids under the preset time series; and a first determination unit, configured to determine the first heat demand pattern and the first heat supply capacity of the plurality of second heating network grids under the preset time series based on the target heat supply and the target heat consumption, wherein the preset time series includes different time periods of any day in the target period, and the target period is the duration of any one of the four seasons of spring, summer, autumn, and winter.

[0058] In an optional embodiment, the first determining unit includes: a first determining subunit, configured to determine the first heating capacity, the first heating range, and the first heating consumption of each second heating network grid during the peak time period of any day in the target cycle; and to determine the second heating capacity, the second heating range, and the second heating consumption of each second heating network grid during the low-peak time period of any day in the target cycle, wherein the peak time period is a time period in the preset time series where the heating consumption is greater than or equal to a preset heating consumption, the target heating capacity includes the first heating capacity and the second heating capacity, and the target heating range includes the first heating range and the second heating capacity. The heat range, wherein the target heat consumption includes the first heat consumption and the second heat consumption; the second determining subunit, configured to determine, based on the first heat supply, the first heat supply range, and the first heat consumption, a second heat demand pattern and a second heat supply capacity for each second heat network grid during the peak period of any day in the target cycle, and, based on the second heat supply, the second heat supply range, and the second heat consumption, a third heat demand pattern and a third heat supply capacity for each second heat network grid during the off-peak period of any day in the target cycle, wherein the first heat demand pattern includes the second heat demand pattern and the third heat demand pattern, and the first heat supply capacity includes the second heat supply capacity and the third heat supply capacity.

[0059] In an optional embodiment, the third analysis module 206 includes: a second analysis unit, configured to analyze the second heat demand pattern and the second heating capacity of each second thermal network grid to determine a plurality of third thermal network grids having a first heat energy complementarity relationship and a fourth heat demand pattern and a fourth heating capacity of the plurality of third thermal network grids from the plurality of second thermal network grids; and to analyze the third heat demand pattern and the third heating capacity of each second thermal network grid to determine a plurality of fourth thermal network grids having a second heat energy complementarity relationship and a fifth heat demand pattern and a fifth heating capacity of the plurality of fourth thermal network grids from the plurality of second thermal network grids, wherein the plurality of target thermal networks The grid includes the plurality of third heating network grids and the plurality of fourth heating network grids. The target heat demand pattern includes the fourth heat demand pattern and the fifth heat demand pattern. The target heating capacity includes the fourth heating capacity and the fifth heating capacity. The thermal energy complementarity relationship includes the first thermal energy complementarity relationship and the second thermal energy complementarity relationship. The first thermal energy complementarity relationship indicates that there is a thermal energy complementarity relationship between any two of the third heating network grids in the plurality of second heating network grids during the peak period of any day in the target cycle. The second thermal energy complementarity relationship indicates that there is a thermal energy complementarity relationship between any two of the fourth heating network grids in the plurality of second heating network grids during the off-peak period of any day in the target cycle.

[0060] In an optional embodiment, the execution module 207 includes: a data acquisition unit, configured to acquire second real-time monitoring data of the target thermal network grid group according to the target safety level; and a first supply unit, configured to, when it is determined from the second real-time monitoring data that there is an abnormally operating fifth thermal network grid in the target thermal network grid group, send a first message to a plurality of normally operating sixth thermal network grids in the target thermal network grid group, to instruct the plurality of sixth thermal network grids to supply heat energy to the fifth thermal network grid according to a sixth demand mode and a sixth heating capacity, wherein the sixth demand mode is the current heat demand mode of the plurality of sixth thermal network grids, and the sixth heating capacity is the current heating capacity of the plurality of sixth thermal network grids.

[0061] In an optional embodiment, the execution module 207 further includes: a second determining unit, configured to, after sending a first message to multiple sixth heating network grids operating normally in the target heating network grid group based on the second real-time monitoring data, determine, based on the first response message received from the multiple sixth heating network grids, that the current heating capacity of the sixth heating network grid is insufficient, wherein the first response message is feedback of the first message; and a second supply unit, configured to send a second message to multiple seventh heating network grids of a first safety level to instruct the multiple seventh heating network grids to supply heat energy to the fifth heating network grid according to a seventh demand mode and a seventh heating capacity, wherein the first safety level is greater than the target safety level, the seventh demand mode is the current heat demand mode of the multiple seventh heating network grids, and the seventh heating capacity is the current heating capacity of the multiple seventh heating network grids.

[0062] In an optional embodiment, the evaluation module 201 includes: a comparison unit, configured to compare the first real-time monitoring data with a preset safety standard to obtain a comparison result; and an evaluation unit, configured to perform a safety evaluation on the plurality of thermal pipeline grids to determine the safety level of the plurality of thermal pipeline grids if it is determined from the comparison result that the plurality of thermal pipeline grids do not meet the preset safety standard.

[0063] This application also provides a computer-readable storage medium storing instructions that, when executed, perform the steps of any of the methods described above.

[0064] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0065] This application also discloses an electronic device, see reference. Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0066] The communication bus 302 is used to enable communication between these components.

[0067] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0068] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0069] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the electronic device (such as a server) using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0070] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a safety management method of a thermal pipeline network.

[0071] exist Figure 3 In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and to acquire user input data; while the processor 301 can be used to call an application program of a safety management method for a thermal pipeline network stored in the memory 305. When executed by one or more processors 301, the electronic device 300 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0072] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0073] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0074] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0075] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A safety management method for a heat distribution pipe network, characterized by, include: A safety assessment is performed on the first real-time monitoring data of multiple heating network grids in the heating network according to preset safety standards, so as to determine the safety level of the multiple heating network grids; The spatial data of multiple first heating network grids with a target safety level in the first real-time monitoring data are analyzed to determine the spatial location of each first heating network grid in the multiple first heating network grids, wherein the safety level includes the target safety level, and the multiple heating network grids include the multiple first heating network grids; The relative distance between any two first thermal pipeline grids in the plurality of first thermal pipeline grids is determined based on the spatial location; From the plurality of first thermal network grids, a plurality of second thermal network grids with a relative distance less than or equal to a preset relative distance are determined, wherein the plurality of first thermal network grids include the plurality of second thermal network grids; The operational data and historical operational data of the plurality of second heating network grids in the first real-time monitoring data are analyzed to determine the first heat demand pattern and the first heating capacity of the plurality of second heating network grids, wherein the first heat demand pattern and the first heating capacity of each second heating network grid have a one-to-one correspondence. The first heat demand pattern and the first heating capacity of the plurality of second heat pipe network grids are analyzed to determine a plurality of target heat pipe network grids with complementary heat energy relationships and the target heat demand pattern and target heating capacity of the plurality of target heat pipe network grids, wherein the first heat demand pattern includes the target heat demand pattern and the first heating capacity includes the target heating capacity. The multiple target heating network grids are identified as a target heating network grid group, and safety management operations are performed on the target heating network grid group according to the target safety level, the target heat demand pattern, and the target heating capacity.

2. The method of claim 1, wherein, The analysis of the operational data and historical operational data of the plurality of second heating network grids in the first real-time monitoring data to determine the first heat demand pattern and first heating capacity of the plurality of second heating network grids specifically includes: The operation data of the multiple second heating network grids in the first real-time monitoring data and the historical operation data of the multiple second heating network grids are analyzed according to a preset time series to determine the target heat supply, target heat supply range and target heat consumption of the multiple second heating network grids under the preset time series. The first heat demand pattern and the first heating capacity of the plurality of second heating network grids under the preset time series are determined based on the target heat supply and the target heat consumption, wherein the preset time series includes different time periods of any day in the target period, and the target period is the duration of any one of the four seasons of spring, summer, autumn and winter.

3. The method of claim 2, wherein, The step of determining the first heat demand pattern and the first heating capacity of the plurality of second heating network grids under the preset time series based on the target heat supply and the target heat consumption specifically includes: The method involves determining the first heat supply, the first heating range, and the first heat consumption for each second heating network grid during the peak period of any day in the target cycle, and determining the second heat supply, the second heating range, and the second heat consumption for each second heating network grid during the off-peak period of any day in the target cycle. The peak period is defined as the time period in the preset time series where the heat consumption is greater than or equal to a preset heat consumption, and the target heat consumption is defined as the time period in the preset time series where the heat consumption is less than a preset heat consumption. The target heat supply includes the first heat supply and the second heat supply, the target heating range includes the first heating range and the second heating range, and the target heat consumption includes the first heat consumption and the second heat consumption. Based on the first heat supply, the first heating range, and the first heat consumption, a second heat demand pattern and a second heating capacity are determined for each second heating network grid during the peak period of any day in the target cycle. Furthermore, based on the second heat supply, the second heating range, and the second heat consumption, a third heat demand pattern and a third heating capacity are determined for each second heating network grid during the off-peak period of any day in the target cycle. The first heat demand pattern includes the second heat demand pattern and the third heat demand pattern, and the first heating capacity includes the second heating capacity and the third heating capacity.

4. The method of claim 3, wherein, The analysis of the first heat demand pattern and the first heating capacity of the plurality of second heating network grids to determine a plurality of target heating network grids with complementary heat energy relationships and the target heat demand pattern and target heating capacity of the plurality of target heating network grids specifically includes: The second heat demand pattern and second heating capacity of each second heating network grid are analyzed to determine a plurality of third heating network grids with a first heat energy complementarity relationship and a fourth heat demand pattern and a fourth heating capacity of the plurality of third heating network grids. Furthermore, the third heat demand pattern and third heating capacity of each second heating network grid are analyzed to determine a plurality of fourth heating network grids with a second heat energy complementarity relationship and a fifth heat demand pattern and a fifth heating capacity of the plurality of fourth heating network grids. The plurality of target heating network grids include the plurality of third heating network grids and... The plurality of fourth heating network grids, the target heat demand pattern includes the fourth heat demand pattern and the fifth heat demand pattern, the target heating capacity includes the fourth heating capacity and the fifth heating capacity, the heat energy complementarity relationship includes the first heat energy complementarity relationship and the second heat energy complementarity relationship, the first heat energy complementarity relationship indicates that there is a heat energy complementarity relationship between any two third heating network grids in the plurality of second heating network grids during the peak period of any day in the target cycle, and the second heat energy complementarity relationship indicates that there is a heat energy complementarity relationship between any two fourth heating network grids in the plurality of second heating network grids during the off-peak period of any day in the target cycle.

5. The method of claim 1, wherein, The step of identifying the plurality of target heating network grids as a target heating network grid group, and performing safety management operations on the target heating network grid group according to the target safety level, the target heat demand pattern, and the target heating capacity, specifically includes: The second real-time monitoring data of the target thermal pipeline network group is collected according to the target safety level; If, based on the second real-time monitoring data, it is determined that there is an abnormally operating fifth heating network grid in the target heating network grid group, a first message is sent to multiple normally operating sixth heating network grids in the target heating network grid group to instruct the multiple sixth heating network grids to supply heat energy to the fifth heating network grid according to a sixth demand mode and a sixth heating capacity, wherein the sixth demand mode is the current heat demand mode of the multiple sixth heating network grids, and the sixth heating capacity is the current heating capacity of the multiple sixth heating network grids.

6. The method of claim 5, wherein, After sending the first message to the multiple sixth heating network grids operating normally in the target heating network grid group based on the second real-time monitoring data, the method further includes: Upon receiving a first response message from the plurality of sixth heating network grids, it is determined, based on the first response message, that the current heating capacity of the sixth heating network grid is insufficient, wherein the first response message is feedback of the first message; A second message is sent to multiple seventh-level heating network grids at the first safety level to instruct the multiple seventh-level heating network grids to supply heat energy to the fifth-level heating network grid according to a seventh demand pattern and a seventh heating capacity, wherein the first safety level is greater than the target safety level, the seventh demand pattern is the current heat demand pattern of the multiple seventh-level heating network grids, and the seventh heating capacity is the current heating capacity of the multiple seventh-level heating network grids.

7. The method of claim 1, wherein, The step of conducting a safety assessment of the first real-time monitoring data of multiple heating network grids in the heating network according to preset safety standards, in order to determine the safety level of the multiple heating network grids, specifically includes: The first real-time monitoring data is compared with the preset safety standard to obtain the comparison result; If, based on the comparison results, it is determined that any of the plurality of heating network grids does not meet the preset safety standards, the safety assessment is performed on the plurality of heating network grids to determine the safety level of the plurality of heating network grids.

8. A safety management device for a heat distribution pipe network, characterized by include: The assessment module is used to perform a safety assessment on the first real-time monitoring data of multiple heating network grids in the heating network according to preset safety standards, so as to determine the safety level of the multiple heating network grids; The first analysis module is used to analyze the spatial data of multiple first thermal pipeline grids with a target safety level in the first real-time monitoring data, so as to determine the spatial location of each first thermal pipeline grid in the multiple first thermal pipeline grids, wherein the safety level includes the target safety level, and the multiple thermal pipeline grids include the multiple first thermal pipeline grids; The first determining module is used to determine the relative distance between every two first thermal pipeline grids in the plurality of first thermal pipeline grids based on the spatial location; The second determining module is used to determine from the plurality of first thermal network grids a plurality of second thermal network grids whose relative distance is less than or equal to a preset relative distance, wherein the plurality of first thermal network grids includes the plurality of second thermal network grids; The second analysis module is used to analyze the operation data of the plurality of second heating network grids and the historical operation data of the plurality of second heating network grids in the first real-time monitoring data, so as to determine the first heat demand pattern and the first heating capacity of the plurality of second heating network grids, wherein the first heat demand pattern and the first heating capacity of each second heating network grid have a one-to-one correspondence. The third analysis module is used to analyze the first heat demand pattern and the first heating capacity of the plurality of second heat pipe network grids, so as to determine a plurality of target heat pipe network grids with complementary heat energy relationships and the target heat demand pattern and target heating capacity of the plurality of target heat pipe network grids from the plurality of second heat pipe network grids, wherein the first heat demand pattern includes the target heat demand pattern and the first heating capacity includes the target heating capacity. The execution module is used to determine the plurality of target heating network grids as a target heating network grid group, and to perform safety management operations on the target heating network grid group according to the target safety level, the target heat demand pattern and the target heating capacity.

9. An electronic device, comprising: include: One or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the electronic device to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-7.

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