AI-based intelligent control method and system for heat supply station

Abstract

The invention discloses an AI-based intelligent control method and system for a heat supply station, and the method comprises the steps: formulating a heat supply demand monitoring method according to regional analysis, obtaining a heat supply monitoring result of the heat supply station, finally obtaining a heat supply allocation method of the heat supply station, and controlling and executing the heat supply allocation method of the heat supply station through a heat supply tail end control terminal. A heat supply demand monitoring method is formulated according to regional analysis, a heat supply monitoring result of a heat supply station is obtained, a heat supply allocation method of the heat supply station is finally obtained, the heat supply allocation method is controlled and executed through a heat supply tail end control terminal, and the allocation result of the heat supply amount is controlled within a reasonable range. The heat supply tail end control terminal conducts monitoring, regulation and control through equipment such as a sensor, a valve and a control system, stable operation of a heat supply system is kept, heat energy is adjusted according to user requirements, safety and energy saving performance are ensured, the precision of the allocated heat supply amount is greatly improved, and the heat supply amount allocation system has the advantages of being high in heat supply amount allocation precision and high in heat supply prediction capacity.

Description

Technical Field

[0001] The present invention relates to the field of heating control technology, and specifically to a method and system for intelligent control of a heating station based on AI. Background Art

[0002] With the improvement of people's living standards and the increasing attention paid to energy conservation and environmental protection, urban centralized heating has developed rapidly in recent years. An analysis of the heating quality in my country's urban heating system shows that the improvement of heating quality is not obvious. The reason is that there are insufficient equipment control during the operation of the heating system, and the balance between the near and far ends and the high and low-level systems is poor, which makes the operation and management of the electric heating system more difficult.

[0003] In the prior art, the intelligent control system of the heating station monitors the historical heating data of the regional population, and controls and adjusts the heat supply when it detects a significant change in the heating data. However, the problem of imbalance in the electric heating area still exists. The main reason for this problem lies in the complexity of the internal structure of the city. The flow of population in the electric heating areas in different areas will affect the heating demand in the area, and the heating monitoring data has a lag, which makes it impossible to effectively predict the heating demand in the area, resulting in the heating station being unable to control the output of appropriate heat energy in the area, and the heating regulation of end users is difficult to achieve the expected effect. Therefore, it is very necessary to design an AI-based intelligent control method and system for heating stations with high accuracy in heat allocation and strong heating prediction capabilities. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for intelligent control of a heating station based on AI to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method and system for intelligent control of a heating station based on AI, comprising:

[0006] Develop a method for monitoring heating demand based on regional analysis;

[0007] Based on the heating demand monitoring method, the heating monitoring result of the heating station is obtained, and based on the heating monitoring result of the heating station, the heating allocation method of the heating station is obtained, and the heating allocation method of the heating station is executed through the heating terminal control terminal.

[0008] According to the above technical solution, the method for monitoring heating demand based on regional analysis includes:

[0009] According to the preset definition standard, the areas are divided into commercial areas, residential areas, industrial areas, scenic areas and other areas, and a key event is extracted from the commercial areas, residential areas, scenic areas, industrial areas and other areas respectively, marked as event A, event B, event C, event D and event E, among which other areas include the areas where the highways are located;

[0010] Monitor event A, event B, event C, event D and event E;

[0011] Retrieve and obtain the preset total heat consumption of commercial areas, residential areas, industrial areas, scenic areas and other areas, and divide them into a first effective time period and a second effective time period according to time. In the first effective time period, divide the preset total heat consumption of the commercial areas, residential areas, industrial areas, scenic areas and other areas into the heat consumption of the first effective time period and the heat consumption of the second effective time period;

[0012] According to the above technical solution, the areas are divided into commercial areas, residential areas, industrial areas, scenic areas and other areas according to the preset definition standards, including:

[0013] Extract heating history data, the heating history data includes the change curve of hourly heat consumption per unit area and daily heat consumption rate per unit area over time, based on the change curve of daily heat consumption rate per unit area over time, intercept the time nodes of the maximum change rate of daily heat consumption per unit area, the minimum change rate and the minimum absolute value of the change rate, subtract the absolute value of the minimum absolute value of the change rate from the time node of the maximum heat consumption time node to obtain the time difference S1, and obtain the heat consumption in the first effective time period The absolute value of the minimum time node of the absolute value of the change rate minus the minimum time node of the consumed calories is taken to obtain the time difference S2, and the consumed calories of the second effective time period are obtained. Where Q i is the heat consumption per unit area in the first effective time period, i is the time sequence value of the first effective time period, 1≤i≤S1, Q k is the heat consumption per unit area in the second effective time period, k is the time sequence value of the second effective time period, S1+1≤k≤S1+S2, i and k are both variable values;

[0014] Based on the heat consumption in the first effective time period and the heat consumption in the second effective time period in the unit area, adjacent unit areas are sequentially superimposed, the heat consumption in the first effective time period and the heat consumption in the second effective time period after the adjacent unit areas are superimposed are calculated, a virtual model composed of a plurality of unit areas in the area is retrieved and obtained, and the calculated adjacent unit areas are superimposed and matched in the virtual model;

[0015] Continue to superimpose adjacent unit area regions until at least one of the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in the virtual model are superimposed is monitored, and when the heat consumption difference rate of the corresponding effective time period between the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is lower than the preset minimum difference rate λ%, then confirm that the matching is successful, wherein the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is performed simultaneously with the step of sequentially superimposing adjacent unit area regions;

[0016] The area after the adjacent unit areas matched in the virtual model are superimposed is locked, and the locked area is matched with the heat consumption of the first effective time period and the heat consumption of the second effective time period preset in the commercial area, residential area, industrial area, scenic area and other areas in sequence, and the locked area is marked as the corresponding area name with the lowest difference between the heat consumption of the first effective time period and the heat consumption of the second effective time period, and the corresponding area name includes the commercial area, residential area, industrial area, scenic area and other areas.

[0017] According to the above technical solution, the monitoring of event A, event B, event C, event D and event E includes:

[0018] Retrieve a heat supply relationship distribution map in the area, the heat supply relationship distribution map includes at least n influencing data related to the amount of heat supply in the area and the influencing weight data of the at least n influencing data related to the amount of heat supply in the area on the heat supply relationship distribution map, and when it is monitored that the influencing data reaches a preset value and preset category information appears, mark it as heat supply change influencing data, and retrieve the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heat supply relationship distribution map in the heat supply relationship distribution map, wherein n is the minimum preset value of the number of influencing data related to the amount of heat supply in the area;

[0019] Based on the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map, the heating supply change impact data are divided into the commercial area, residential area, industrial area, scenic area and other areas in turn, and marked as event A, event B, event C, event D and event E in turn. The number of the heating supply change impact data contained in event A, event B, event C, event D and event E is not less than one. The heating supply change impact data contained in event A, event B, event C, event D and event E are multiplied by the impact weight data of the heating relationship distribution map corresponding to the heating supply change impact data, and the heating demand change values ​​of event A, event B, event C, event D and event E are obtained respectively.

[0020] According to the above technical solution, the method of obtaining the heating monitoring result of the heating station and obtaining the heating allocation method of the heating station based on the heating monitoring result of the heating station includes:

[0021] Mark the obtained heating demand change values ​​of event A, event B, event C, event D and event E as the heating monitoring result of the heating station;

[0022] The amount of heat allocated to the area corresponding to the area name Among them, X F is the reference value of the number of people in the corresponding area name, Y F The heat consumption of the area corresponding to the area name, when the heat consumption difference rate of the first effective time period is lower than the preset minimum difference rate λ%, the heat consumption of the first effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the second effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the second effective time period with a difference in heat consumption lower than the preset minimum difference λ% is selected; when the difference in heat consumption during the first effective time period and the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the corresponding effective time period with a larger difference between the heat consumption during the first effective time period and the heat consumption during the second effective time period is selected as Y F , and monitor the change of the difference rate of heat consumption between the first effective time period and the second effective time period at any time, and convert Y according to the above selection method F The specific calorie consumption value, Z F is the change value of the regional heating demand corresponding to the event, G is a preset level, and after the preset level G is multiplied by the difference rate λ, the multiplication result is controlled to be within 10 of the multiple of the reference difference rate λ0, λ0 is the reference difference rate, 0<λ0<70%.

[0023] According to the above technical solution, the method for controlling the heating station heat allocation by the heating terminal control terminal includes:

[0024] The heating terminal control terminal receives the heating adjustment instruction, transmits the heating adjustment instruction to the heating equipment, and the heating equipment receives the heating adjustment instruction and adjusts the opening and closing time of the valve; wherein the heating equipment includes: a meter and the valve, the meter and the valve are used to measure and adjust the heating amount, the valve receives the heating amount information allocated in the area corresponding to the area name, and controls the allocated heating amount after the built-in sensor detects that the opening and closing time has been adjusted;

[0025] The stored data on the available heat in the area, the control process, control method and control effect data of the heating terminal control terminal are extracted; when the heating terminal control terminal detects that the available heat in the area is lower than the heat supply allocated in the area with the corresponding area name, the heating station in the area is controlled to supplement power until it is detected that the available heat in the area is 20% higher than the heat supply allocated in the area with the corresponding area name, and the control is restarted through the control process, control method and control effect data of the heating terminal control terminal when it is detected next time.

[0026] According to the above technical solution, a system for intelligent control of a heating station based on AI is characterized in that: the system for intelligent control of the heating station includes a monitoring module and a control module;

[0027] The monitoring module is used to formulate a heating demand monitoring method based on regional analysis;

[0028] The control module is used to obtain the heating station heating monitoring results based on the heating demand monitoring method, obtain the heating station heating allocation method based on the heating station heating monitoring results, and execute the heating station heating allocation method through the heating terminal control terminal.

[0029] According to the above technical solution, the monitoring module includes a division module and a regional data acquisition module;

[0030] The division module is used to divide the area into commercial area, residential area, industrial area, scenic area and other areas according to the preset definition standard, extract a key event from the commercial area, residential area, scenic area, industrial area and other areas respectively, and mark them as event A, event B, event C, event D and event E, wherein the other area includes the area where the highway is located; monitor event A, event B, event C, event D and event E;

[0031] The regional data acquisition module is used to retrieve and obtain the preset total heat consumption of commercial areas, residential areas, industrial areas, scenic areas and other areas, which are divided into a first effective time period and a second effective time period according to time. During the first effective time period, the preset total heat consumption of the commercial areas, residential areas, industrial areas, scenic areas and other areas is divided into the heat consumption of the first effective time period and the heat consumption of the second effective time period.

[0032] According to the above technical solution, the division module includes a region definition submodule and an event monitoring submodule;

[0033] The area definition submodule is used to extract heating history data, which includes the hourly heat consumption per unit area and the change curve of the daily heat consumption per unit area over time. Based on the change curve of the daily heat consumption per unit area over time, the time nodes of the maximum change rate, the minimum change rate and the minimum absolute value of the change rate are intercepted. The absolute value of the maximum heat consumption time node minus the minimum absolute value of the change rate time node is taken to obtain the time difference S1, and the heat consumption in the first valid time period is obtained. The absolute value of the minimum time node of the absolute value of the change rate minus the minimum time node of the consumed calories is taken to obtain the time difference S2, and the consumed calories of the second effective time period are obtained. Where Q i is the heat consumption per unit area in the first effective time period, i is the time sequence value of the first effective time period, 1≤i≤S1, Q kis the heat consumption in the unit area in the second effective time period, k is the time sequence value of the second effective time period, S1+1≤k≤S1+S2, and i and k are both variable values; based on the heat consumption in the first effective time period and the heat consumption in the second effective time period obtained in the unit area, adjacent unit areas are superimposed in sequence, the heat consumption in the first effective time period and the heat consumption in the second effective time period after the adjacent unit areas are superimposed are calculated, a virtual model consisting of a plurality of unit areas in the area is retrieved and obtained, and the calculated adjacent unit areas are superimposed and matched in the virtual model; adjacent unit areas are continued to be superimposed until at least one of the heat consumption in the first effective time period or the heat consumption in the second effective time period after the adjacent unit areas matched in the virtual model are monitored, and superimposed with the adjacent unit areas matched in other virtual models. When the heat consumption of the first effective time period or the heat consumption of the second effective time period after the corresponding effective time period is less than the preset minimum difference λ%, the match is confirmed to be successful, wherein the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is performed simultaneously with the step of superimposing the adjacent unit area areas in sequence; the area after the adjacent unit areas matched in the virtual model are superimposed is locked, and the locked area is matched with the heat consumption of the first effective time period and the heat consumption of the second effective time period preset in the commercial area, residential area, industrial area, scenic area and other areas in sequence, and the locked area is marked as the corresponding area name with the lowest difference between the heat consumption of the first effective time period and the heat consumption of the second effective time period, and the corresponding area name includes the commercial area, residential area, industrial area, scenic area and other areas.

[0034] The event monitoring submodule is used to retrieve a heating relationship distribution map in a region, wherein the heating relationship distribution map includes at least n influencing data related to the amount of heating in the region and weight data of the influence of the at least n influencing data related to the amount of heating in the region on the heating relationship distribution map. When it is monitored that the influencing data reaches a preset value and preset category information appears, it is marked as heating change influencing data, and the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map is retrieved from the heating relationship distribution map, wherein n is the minimum preset value of the number of influencing data related to the amount of heating in the region; based on the commercial area, residential area, industrial area, scenic area and other areas, the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map is retrieved from the heating relationship distribution map. The location information of the commercial area and other areas in the heating relationship distribution map is used to divide the heating demand change impact data into the commercial area, residential area, industrial area, scenic area and other areas in turn, and marked as event A, event B, event C, event D and event E in turn. The number of the heating demand change impact data contained in event A, event B, event C, event D and event E is not less than one, and the heating demand change impact data contained in event A, event B, event C, event D and event E is multiplied by the impact weight data of the heating relationship distribution map corresponding to the heating demand change impact data, so as to obtain the heating demand change values ​​of event A, event B, event C, event D and event E respectively.

[0035] According to the above technical solution, the control module includes a monitoring result acquisition module and a heating supply allocation module;

[0036] The monitoring result acquisition module is used to mark the obtained heating demand change values ​​of event A, event B, event C, event D and event E as the obtained heating monitoring result of the heating station;

[0037] The heat supply allocation module is used to allocate heat supply to the area corresponding to the area name. Among them, X F is the reference value of the number of people in the corresponding area name, Y F The heat consumption of the area corresponding to the area name, when the heat consumption difference rate of the first effective time period is lower than the preset minimum difference rate λ%, the heat consumption of the first effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the second effective time period is selected as Y FWhen the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the second effective time period with a difference in heat consumption lower than the preset minimum difference λ% is selected; when the difference in heat consumption during the first effective time period and the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the corresponding effective time period with a larger difference between the heat consumption during the first effective time period and the heat consumption during the second effective time period is selected as Y F , and monitor the change of the difference rate of heat consumption between the first effective time period and the second effective time period at any time, and convert Y according to the above selection method F The specific calorie consumption value, Z F is the change value of the regional heating demand corresponding to the event, G is a preset level, and after the preset level G is multiplied by the difference rate λ, the multiplication result is controlled to be within 10 of the multiple of the reference difference rate λ0, λ0 is the reference difference rate, 0<λ0<70%.

[0038] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by formulating a heating demand monitoring method based on regional analysis and obtaining the heating monitoring results of the heating station, can monitor the flow of population in the region, that is, the change in heating demand in the corresponding region, and realize early prediction of the heating demand, thereby avoiding the disadvantages caused by heating lag to the greatest extent, and finally obtaining the heating allocation method of the heating station, and controlling the execution of the heating allocation method through the heating terminal control terminal to control the allocation result of the heating amount within a reasonable range. The heating terminal control terminal monitors and controls through sensors, valves, control systems and other equipment to maintain the stable operation of the heating system, and adjusts the thermal energy according to user needs to ensure safety and energy saving, and greatly improve the accuracy of the allocated heating amount. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0040] Figure 1 It is a flow chart of a method for intelligent control of a heating station based on AI provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1, which is a flow chart of a method provided by an embodiment of the present invention, such as Figure 1 It can be seen that the method of intelligent control of a heating station based on AI includes:

[0043] Step S1: Develop a heating demand monitoring method based on regional analysis;

[0044] Step S2: Based on the heating demand monitoring method, a heating station heating monitoring result is obtained; based on the heating station heating monitoring result, a heating station heating allocation method is obtained; and the heating station heating allocation method is executed through the heating terminal control terminal.

[0045] The embodiments of the present invention formulate a heating demand monitoring method based on regional analysis and obtain heating monitoring results of the heating station. It is possible to monitor the flow of population in the region, that is, the change in heating demand in the corresponding region, and realize early prediction of the heating demand, thereby avoiding the disadvantages of heating lag to the greatest extent, and finally obtain the heating allocation method of the heating station. The heating allocation method is executed through the heating terminal control terminal to control the allocation result of the heating amount within a reasonable range. The heating terminal control terminal monitors and controls through sensors, valves, control systems and other equipment to maintain the stable operation of the heating system, and adjusts thermal energy according to user needs to ensure safety and energy saving, thereby greatly improving the accuracy of the allocated heating amount.

[0046] In certain preferred embodiments, the method for monitoring heating demand according to regional analysis comprises:

[0047] Step S11: Divide into commercial areas, residential areas, industrial areas, scenic areas and other areas according to preset definition standards, extract a key event from the commercial areas, residential areas, scenic areas, industrial areas and other areas respectively, and mark them as event A, event B, event C, event D and event E, wherein other areas include areas where highways are located;

[0048] Step S12: Monitor event A, event B, event C, event D and event E.

[0049] Commercial areas, residential areas, scenic areas, industrial areas and other areas in most cases include all areas where people are located. At the same time, there are also dimensional connections between the above five areas, such as:

[0050] In the following characteristic situation, the area where people are located during the day is E, and the area where people are located at night is B;

[0051] In the second characteristic case, the area where people are located during the day is B, and the area where people are located at night is C;

[0052] Step S13: retrieve and obtain the preset total heat consumption of commercial areas, residential areas, industrial areas, scenic areas and other areas, and divide them into a first effective time period and a second effective time period according to time. In the first effective time period, the preset total heat consumption of the commercial areas, residential areas, industrial areas, scenic areas and other areas is divided into the heat consumption of the first effective time period and the heat consumption of the second effective time period, wherein the effective time period is the time period that has an actual impact on the heating in the area compared with other time periods. In other time periods other than the first effective time period and the second effective time period, the heating cannot reflect the population's demand for heating, but is only the basic heating supply that needs to be achieved in the area. In the first effective time period, the heat consumption of the commercial area is a1, the heat consumption of the residential area is b1, the heat consumption of the scenic area is c1, the heat consumption of the industrial area is d1, and the heat consumption of other areas is e1; in the second effective time period, the heat consumption of the commercial area is a2, the heat consumption of the residential area is b2, the heat consumption of the scenic area is c2, the heat consumption of the industrial area is d2, and the heat consumption of other areas is e2.

[0053] By screening within the first effective time period and the second effective time period, the heating station can achieve real-time control of heating and improve the accuracy of heating allocation.

[0054] In some preferred embodiments, the division into commercial areas, residential areas, industrial areas, scenic areas and other areas according to preset definition criteria includes:

[0055] Step S111: extracting heating history data, the heating history data including the hourly heat consumption per unit area and the change curve of the daily heat consumption per unit area over time, intercepting the time nodes of the maximum change rate of the daily heat consumption per unit area, the minimum change rate and the minimum absolute value of the change rate based on the change curve of the daily heat consumption per unit area over time, subtracting the absolute value of the time node of the minimum absolute value of the change rate from the time node of the maximum heat consumption time node to obtain the time difference S1, and obtaining the heat consumption for the first effective time period The absolute value of the minimum time node of the absolute value of the change rate minus the minimum time node of the consumed calories is taken to obtain the time difference S2, and the consumed calories of the second effective time period are obtained. Where Q i is the heat consumption per unit area in the first effective time period, i is the time sequence value of the first effective time period, 1≤i≤S1, Q k is the heat consumption per unit area in the second effective time period, k is the time sequence value of the second effective time period, S1+1≤k≤S1+S2, i and k are both variable values;

[0056] Step S112: based on the obtained heat consumption in the first effective time period and the heat consumption in the second effective time period in the unit area, adjacent unit area areas are sequentially superimposed, the heat consumption in the first effective time period and the heat consumption in the second effective time period after the adjacent unit areas are superimposed are calculated, a virtual model consisting of a plurality of unit areas in the area is retrieved and obtained, and the calculated adjacent unit areas are superimposed and matched in the virtual model;

[0057] Step S113: Continue to superimpose adjacent unit area regions until at least one of the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in the virtual model are superimposed is monitored, and the heat consumption difference rate of the corresponding effective time period between the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is lower than the preset minimum difference rate λ%, then confirming that the matching is successful, wherein the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is performed simultaneously with the step of sequentially superimposing adjacent unit area regions;

[0058] Step S114: Lock the area after the adjacent unit areas matched in the virtual model are superimposed, and match the locked area with the heat consumption of the first effective time period and the heat consumption of the second effective time period preset in the commercial area, residential area, industrial area, scenic area and other areas in turn, and mark the locked area as the corresponding area name with the lowest difference between the heat consumption of the first effective time period and the heat consumption of the second effective time period, and the corresponding area name includes the commercial area, residential area, industrial area, scenic area and other areas.

[0059] This technical solution solves the problem of fuzzy division between different regions, mixed multiple regions, and difficulty in detecting the heating demand of the population. By retrieving and analyzing the heating impact data of different regions in the distribution map based on the division of different regional types, and obtaining the heating monitoring results of the heating station, it is possible to distinguish the unique heating demand changes in different regions when multiple regions are mixed, and monitor the flow of the population in the region, that is, the changes in the heating demand of the corresponding region, and realize the early prediction of the heating demand.

[0060] In certain preferred embodiments, the monitoring of event A, event B, event C, event D and event E comprises:

[0061] Step S121: Retrieve a heat supply relationship distribution map in the area, wherein the heat supply relationship distribution map includes at least n influencing data related to the amount of heat supply in the area and weight data of the influence of the at least n influencing data related to the amount of heat supply in the area on the heat supply relationship distribution map. When it is monitored that the influencing data reaches a preset value and preset category information appears, it is marked as heat supply change influencing data, and the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heat supply relationship distribution map is retrieved from the heat supply relationship distribution map, wherein n is the minimum preset value of the number of influencing data related to the amount of heat supply in the area;

[0062] Step S122: Based on the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map, the heating supply change impact data is divided into the commercial area, residential area, industrial area, scenic area and other areas in turn, and marked as event A, event B, event C, event D and event E in turn, and the number of the heating supply change impact data contained in the event A, event B, event C, event D and event E is not less than one, and the heating supply change impact data contained in the event A, event B, event C, event D and event E is multiplied by the impact weight data of the heating relationship distribution map corresponding to the heating supply change impact data, so as to obtain the heating demand change values ​​of the event A, event B, event C, event D and event E respectively.

[0063] Changes in the heat supply in the commercial area affect data such as: when the time and date reaches a holiday, it reaches the preset value;

[0064] The data affected by the change of heat supply in the residential area, for example: the time reaches the working time node or the time reaches the off-get off work time node, which means the preset value is reached;

[0065] Data on the impact of changes in heat supply in industrial areas, for example: announcements of changes in regional facilities, are preset category information;

[0066] The data affected by the change of heat supply in the scenic area, for example: when the time and date reaches the holiday, it reaches the preset value;

[0067] Other data on the impact of changes in heat supply within the area, such as announcements of regional facility construction, are preset category information;

[0068] 5. According to the method of intelligent control of a heating station based on AI in claim 4, it is characterized in that: the obtaining of the heating monitoring result of the heating station and the obtaining of the heating allocation method of the heating station based on the heating monitoring result of the heating station include:

[0069] Step S21: marking the obtained heating demand change values ​​of the event A, event B, event C, event D and event E as the heating monitoring result of the heating station;

[0070] Step S22: The heat supply allocated to the area corresponding to the area name Among them, X F is the reference value of the number of people in the corresponding area name, Y F The heat consumption of the area corresponding to the area name, when the heat consumption difference rate of the first effective time period is lower than the preset minimum difference rate λ%, the heat consumption of the first effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the second effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the second effective time period with a difference in heat consumption lower than the preset minimum difference λ% is selected; when the difference in heat consumption during the first effective time period and the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the corresponding effective time period with a larger difference between the heat consumption during the first effective time period and the heat consumption during the second effective time period is selected as Y F , and monitor the change of the difference rate of heat consumption between the first effective time period and the second effective time period at any time, and convert Y according to the above selection method F The specific calorie consumption value, Z F is the change value of the regional heating demand corresponding to the event, G is a preset level, and after the preset level G is multiplied by the difference rate λ, the difference between the multiplication result and the reference difference rate λ0 is controlled to be within 10, λ0 is the reference difference rate, 0<λ0<70%, and the preset level G and the reference difference rate λ0 can ensure that the result of λ0%+Gλ% is controlled within a reasonable range, thereby greatly improving the accuracy of the allocated heating supply.

[0071] Specifically, during the first effective period, the commercial area: Y F =a1, residential area: Y F =b1, Scenic spot: Y F =c1, Industrial Zone: Y F =d1, other areas: Y F = e1; During the second effective time period, commercial area: Y F =a2, residential area: Y F =b2, Scenic spot: Y F =c2, Industrial Zone: Y F =d2, other areas: Y F =e2.

[0072] 6. The method of intelligent control of a heating station based on AI according to claim 5 is characterized in that: the heating station heat allocation method is executed by controlling the heating terminal control terminal, comprising:

[0073] The heating terminal control terminal receives the heating adjustment instruction, transmits the heating adjustment instruction to the heating equipment, and the heating equipment receives the heating adjustment instruction and adjusts the opening and closing time of the valve; wherein the heating equipment includes: a meter and the valve, the meter and the valve are used to measure and adjust the heating amount, the valve receives the heating amount information allocated in the area corresponding to the area name, and controls the allocated heating amount after the built-in sensor detects that the opening and closing time has been adjusted;

[0074] The stored data on the available heat in the area, the control process, control method and control effect data of the heating terminal control terminal are extracted; when the heating terminal control terminal detects that the available heat in the area is lower than the heat supply allocated in the area with the corresponding area name, the heating station in the area is controlled to supplement power until it is detected that the available heat in the area is 20% higher than the heat supply allocated in the area with the corresponding area name, and the control is restarted through the control process, control method and control effect data of the heating terminal control terminal when it is detected next time.

[0075] The heating terminal control terminal monitors and controls through sensors, valves, control systems and other equipment to maintain the stable operation of the heating system and adjust heat energy according to user needs to ensure safety and energy saving.

[0076] Based on the same concept as the above embodiment, an embodiment of the present invention further provides an AI-based intelligent control system for a heating station, comprising:

[0077] A monitoring module, the monitoring module is used to formulate a heating demand monitoring method based on regional analysis;

[0078] A control module is used to obtain a heating station heating monitoring result based on the heating demand monitoring method, obtain a heating station heating allocation method based on the heating station heating monitoring result, and execute the heating station heating allocation method through a heating terminal control terminal.

[0079] In this embodiment, the monitoring module includes:

[0080] A division module, wherein the division module is used to divide the area into commercial area, residential area, industrial area, scenic area and other areas according to a preset definition standard, extract a key event from the commercial area, residential area, scenic area, industrial area and other areas respectively, and mark them as event A, event B, event C, event D and event E, wherein the other area includes the area where the highway is located; and monitor event A, event B, event C, event D and event E;

[0081] A regional data collection module is used to retrieve and obtain the preset total heat consumption of commercial areas, residential areas, industrial areas, scenic areas and other areas, which is divided into a first effective time period and a second effective time period according to time. Within the first effective time period, the preset total heat consumption of the commercial areas, residential areas, industrial areas, scenic areas and other areas is divided into the heat consumption of the first effective time period and the heat consumption of the second effective time period.

[0082] In this embodiment, the division module includes:

[0083] A region definition submodule is used to extract heating history data, wherein the heating history data includes a curve of the hourly heat consumption per unit area and the daily heat consumption rate per unit area over time. Based on the curve of the daily heat consumption rate per unit area over time, the time nodes of the maximum change rate, the minimum change rate and the minimum absolute value of the change rate are intercepted. The absolute value of the maximum heat consumption time node minus the minimum absolute value of the change rate time node is taken to obtain the time difference S1, and the heat consumption in the first effective time period is obtained. The absolute value of the minimum time node of the absolute value of the change rate minus the minimum time node of the consumed calories is taken to obtain the time difference S2, and the consumed calories of the second effective time period are obtained. Where Q i is the heat consumption per unit area in the first effective time period, i is the time sequence value of the first effective time period, 1≤i≤S1, Q kis the heat consumption in the unit area in the second effective time period, k is the time sequence value of the second effective time period, S1+1≤k≤S1+S2, and i and k are both variable values; based on the heat consumption in the first effective time period and the heat consumption in the second effective time period obtained in the unit area, adjacent unit areas are superimposed in sequence, the heat consumption in the first effective time period and the heat consumption in the second effective time period after the adjacent unit areas are superimposed are calculated, a virtual model consisting of a plurality of unit areas in the area is retrieved and obtained, and the calculated adjacent unit areas are superimposed and matched in the virtual model; adjacent unit areas are continued to be superimposed until at least one of the heat consumption in the first effective time period or the heat consumption in the second effective time period after the adjacent unit areas matched in the virtual model are monitored, and superimposed with the adjacent unit areas matched in other virtual models. When the heat consumption of the first effective time period or the heat consumption of the second effective time period after the corresponding effective time period is less than the preset minimum difference λ%, the match is confirmed to be successful, wherein the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is performed simultaneously with the step of superimposing the adjacent unit area areas in sequence; the area after the adjacent unit areas matched in the virtual model are superimposed is locked, and the locked area is matched with the heat consumption of the first effective time period and the heat consumption of the second effective time period preset in the commercial area, residential area, industrial area, scenic area and other areas in sequence, and the locked area is marked as the corresponding area name with the lowest difference between the heat consumption of the first effective time period and the heat consumption of the second effective time period, and the corresponding area name includes the commercial area, residential area, industrial area, scenic area and other areas.

[0084] An event monitoring submodule, the event monitoring submodule is used to retrieve a heating relationship distribution map in a region, the heating relationship distribution map includes at least n influencing data related to the amount of heating in the region and weight data of the influence of the at least n influencing data related to the amount of heating in the region on the heating relationship distribution map, when it is monitored that the influencing data reaches a preset value and preset category information appears, it is marked as heating change influencing data, and the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map is retrieved in the heating relationship distribution map, wherein n is the minimum preset value of the number of influencing data related to the amount of heating in the region; based on the commercial area, residential area, industrial area, scenic area and other areas, the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map is retrieved ... the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map are retrieved, wherein the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map are retrieved, wherein the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map are retrieved, wherein the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map are retrieved, wherein the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map are retrieved, wherein the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution The location information of business areas, scenic areas and other areas in the heating relationship distribution map is used to divide the heating demand change impact data into the commercial areas, residential areas, industrial areas, scenic areas and other areas in turn, and mark them as event A, event B, event C, event D and event E in turn. The number of the heating demand change impact data contained in event A, event B, event C, event D and event E is not less than one. The heating demand change impact data contained in event A, event B, event C, event D and event E are multiplied by the impact weight data of the heating relationship distribution map corresponding to the heating demand change impact data, and the heating demand change values ​​of event A, event B, event C, event D and event E are obtained respectively.

[0085] In this embodiment, the control module includes:

[0086] A monitoring result acquisition module, the monitoring result acquisition module is used to mark the obtained heating demand change values ​​of the event A, event B, event C, event D and event E as the obtained heating monitoring result of the heating station;

[0087] A heat supply allocation module, the heat supply allocation module is used to allocate heat supply to the area corresponding to the area name Among them, X F is the reference value of the number of people in the corresponding area name, Y F The heat consumption of the area corresponding to the area name, when the heat consumption difference rate of the first effective time period is lower than the preset minimum difference rate λ%, the heat consumption of the first effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the second effective time period is selected as Y FWhen the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the second effective time period with a difference in heat consumption lower than the preset minimum difference λ% is selected; when the difference in heat consumption during the first effective time period and the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the corresponding effective time period with a larger difference between the heat consumption during the first effective time period and the heat consumption during the second effective time period is selected as Y F , and monitor the change of the difference rate of heat consumption between the first effective time period and the second effective time period at any time, and convert Y according to the above selection method F The specific calorie consumption value, Z F is the change value of the regional heating demand corresponding to the event, G is a preset level, and after the preset level G is multiplied by the difference rate λ, the multiplication result is controlled to be within 10 of the multiple of the reference difference rate λ0, λ0 is the reference difference rate, 0<λ0<70%.

[0088] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from other entities or operations, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0089] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for intelligent control of a heating station based on AI, characterized in that: include: Develop a method for monitoring heating demand based on regional analysis; Based on the heating demand monitoring method, the heating monitoring result of the heating station is obtained, and based on the heating monitoring result of the heating station, the heating allocation method of the heating station is obtained, and the heating allocation method of the heating station is executed through the heating terminal control terminal.

2. The method for intelligent control of a heating station based on AI according to claim 1, characterized in that: The method for monitoring heating demand according to regional analysis comprises: According to the preset definition standard, the areas are divided into commercial areas, residential areas, industrial areas, scenic areas and other areas, and a key event is extracted from the commercial areas, residential areas, scenic areas, industrial areas and other areas respectively, marked as event A, event B, event C, event D and event E, among which other areas include the areas where the highways are located; Monitor event A, event B, event C, event D and event E; The daily preset total calorie consumption of commercial areas, residential areas, industrial areas, scenic areas and other areas is retrieved and divided into a first effective time period and a second effective time period according to time. Within the first effective time period, the daily preset total calorie consumption of the commercial areas, residential areas, industrial areas, scenic areas and other areas is divided into the calorie consumption of the first effective time period and the calorie consumption of the second effective time period.

3. The method for intelligent control of a heating station based on AI according to claim 2 is characterized in that: The areas are divided into commercial areas, residential areas, industrial areas, scenic areas and other areas according to the preset definition standards, including: Extract heating history data, the heating history data includes the change curve of hourly heat consumption per unit area and daily heat consumption rate per unit area over time, based on the change curve of daily heat consumption rate per unit area over time, intercept the time nodes of the maximum change rate of daily heat consumption per unit area, the minimum change rate and the minimum absolute value of the change rate, subtract the absolute value of the minimum absolute value of the change rate from the time node of the maximum heat consumption time node to obtain the time difference S1, and obtain the heat consumption in the first effective time period The absolute value of the minimum time node of the absolute value of the change rate minus the minimum time node of the consumed calories is taken to obtain the time difference S2, and the consumed calories of the second effective time period are obtained. Where Q i is the heat consumption per unit area in the first effective time period, i is the time sequence value of the first effective time period, 1≤i≤S1, Q k is the heat consumption per unit area in the second effective time period, k is the time sequence value of the second effective time period, S1+1≤k≤S1+S2, i and k are both variable values; Based on the heat consumption in the first effective time period and the heat consumption in the second effective time period in the unit area, adjacent unit areas are sequentially superimposed, the heat consumption in the first effective time period and the heat consumption in the second effective time period after the adjacent unit areas are superimposed are calculated, a virtual model composed of a plurality of unit areas in the area is retrieved and obtained, and the calculated adjacent unit areas are superimposed and matched in the virtual model; Continue to superimpose adjacent unit area regions until at least one of the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in the virtual model are superimposed is monitored, and when the heat consumption difference rate of the corresponding effective time period between the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is lower than the preset minimum difference rate λ%, then confirm that the matching is successful, wherein the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is performed simultaneously with the step of sequentially superimposing adjacent unit area regions; The area after the adjacent unit areas matched in the virtual model are superimposed is locked, and the locked area is matched with the heat consumption of the first effective time period and the heat consumption of the second effective time period preset in the commercial area, residential area, industrial area, scenic area and other areas in sequence, and the locked area is marked as the corresponding area name with the lowest difference between the heat consumption of the first effective time period and the heat consumption of the second effective time period, and the corresponding area name includes the commercial area, residential area, industrial area, scenic area and other areas.

4. The method for intelligent control of a heating station based on AI according to claim 3 is characterized in that: The monitoring of event A, event B, event C, event D and event E includes: Retrieve a heat supply relationship distribution map in the area, the heat supply relationship distribution map includes at least n influencing data related to the amount of heat supply in the area and the influencing weight data of the at least n influencing data related to the amount of heat supply in the area on the heat supply relationship distribution map, and when it is monitored that the influencing data reaches a preset value and preset category information appears, mark it as heat supply change influencing data, and retrieve the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heat supply relationship distribution map in the heat supply relationship distribution map, wherein n is the minimum preset value of the number of influencing data related to the amount of heat supply in the area; Based on the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map, the heating supply change impact data are divided into the commercial area, residential area, industrial area, scenic area and other areas in turn, and marked as event A, event B, event C, event D and event E in turn. The number of the heating supply change impact data contained in event A, event B, event C, event D and event E is not less than one. The heating supply change impact data contained in event A, event B, event C, event D and event E are multiplied by the impact weight data of the heating relationship distribution map corresponding to the heating supply change impact data, and the heating demand change values ​​of event A, event B, event C, event D and event E are obtained respectively.

5. The method for intelligent control of a heating station based on AI according to claim 4 is characterized in that: The method of obtaining the heating monitoring result of the heating station and obtaining the heating allocation method of the heating station based on the heating monitoring result of the heating station includes: Mark the obtained heating demand change values ​​of event A, event B, event C, event D and event E as the heating monitoring result of the heating station; The amount of heat allocated to the area corresponding to the area name Among them, X F is the reference value of the number of people in the corresponding area name, Y F The heat consumption of the area corresponding to the area name, when the heat consumption difference rate of the first effective time period is lower than the preset minimum difference rate λ%, the heat consumption of the first effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the second effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the second effective time period with a difference in heat consumption lower than the preset minimum difference λ% is selected; when the difference in heat consumption during the first effective time period and the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the corresponding effective time period with a larger difference between the heat consumption during the first effective time period and the heat consumption during the second effective time period is selected as Y F , and monitor the change of the difference rate of heat consumption between the first effective time period and the second effective time period at any time, and convert Y according to the above selection method F The specific calorie consumption value, Z F is the change value of the regional heating demand corresponding to the event, G is a preset level, and after the preset level G is multiplied by the difference rate λ, the multiplication result is controlled to be within 10 of the multiple of the reference difference rate λ0, λ0 is the reference difference rate, 0<λ0<70%.

6. The method for intelligent control of a heating station based on AI according to claim 5 is characterized in that: The method of controlling and executing the heat supply allocation method of the heat supply station by the heat supply terminal control terminal includes: The heating terminal control terminal receives the heating adjustment instruction, transmits the heating adjustment instruction to the heating equipment, and the heating equipment receives the heating adjustment instruction and adjusts the opening and closing time of the valve; wherein the heating equipment includes: a meter and the valve, the meter and the valve are used to measure and adjust the heating amount, the valve receives the heating amount information allocated in the area corresponding to the area name, and controls the allocated heating amount after the built-in sensor detects that the opening and closing time has been adjusted; The stored data on the available heat in the area, the control process, control method and control effect data of the heating terminal control terminal are extracted; when the heating terminal control terminal detects that the available heat in the area is lower than the heat supply allocated in the area with the corresponding area name, the heating station in the area is controlled to supplement power until it is detected that the available heat in the area is 20% higher than the heat supply allocated in the area with the corresponding area name, and the control is restarted through the control process, control method and control effect data of the heating terminal control terminal when it is detected next time.

7. An AI-based intelligent control system for a heating station, characterized in that: The intelligent control system of the heating station includes a monitoring module and a control module; The monitoring module is used to formulate a heating demand monitoring method based on regional analysis; The control module is used to obtain the heating station heating monitoring results based on the heating demand monitoring method, obtain the heating station heating allocation method based on the heating station heating monitoring results, and execute the heating station heating allocation method through the heating terminal control terminal.

8. The AI-based intelligent control system for heating stations according to claim 7 is characterized in that: The monitoring module includes a division module and a regional data acquisition module; The division module is used to divide the area into commercial area, residential area, industrial area, scenic area and other areas according to the preset definition standard, and extract a key event from the commercial area, residential area, scenic area, industrial area and other areas respectively, marked as event A, event B, event C, event D and event E, wherein the other area includes the area where the highway is located, and monitors event A, event B, event C, event D and event E; The regional data acquisition module is used to retrieve and obtain the preset total heat consumption of commercial areas, residential areas, industrial areas, scenic areas and other areas, which are divided into a first effective time period and a second effective time period according to time. During the first effective time period, the preset total heat consumption of the commercial areas, residential areas, industrial areas, scenic areas and other areas is divided into the heat consumption of the first effective time period and the heat consumption of the second effective time period.

9. The AI-based intelligent control system for heating stations according to claim 8 is characterized in that: The division module includes a region definition submodule and an event monitoring submodule; The area definition submodule is used to extract heating history data, which includes the hourly heat consumption per unit area and the change curve of the daily heat consumption per unit area over time. Based on the change curve of the daily heat consumption per unit area over time, the time nodes of the maximum change rate, the minimum change rate and the minimum absolute value of the change rate are intercepted. The absolute value of the maximum heat consumption time node minus the minimum absolute value of the change rate time node is taken to obtain the time difference S1, and the heat consumption in the first valid time period is obtained. The absolute value of the minimum time node of the absolute value of the change rate minus the minimum time node of the consumed calories is taken to obtain the time difference S2, and the consumed calories of the second effective time period are obtained. Where Q i is the heat consumption per unit area in the first effective time period, i is the time sequence value of the first effective time period, 1≤i≤S1, Q k is the heat consumption in the unit area in the second effective time period, k is the time sequence value of the second effective time period, S1+1≤k≤S1+S2, and i and k are both variable values; based on the heat consumption in the first effective time period and the heat consumption in the second effective time period obtained in the unit area, adjacent unit areas are superimposed in sequence, the heat consumption in the first effective time period and the heat consumption in the second effective time period after the adjacent unit areas are superimposed are calculated, a virtual model consisting of a plurality of unit areas in the area is retrieved and obtained, and the calculated adjacent unit areas are superimposed and matched in the virtual model; adjacent unit areas are continued to be superimposed until at least one of the heat consumption in the first effective time period or the heat consumption in the second effective time period after the adjacent unit areas matched in the virtual model are monitored, and superimposed with the adjacent unit areas matched in other virtual models. When the heat consumption of the first effective time period or the heat consumption of the second effective time period after the corresponding effective time period is less than the preset minimum difference rate λ%, the match is confirmed to be successful, wherein the heat consumption of the first effective time period or the heat consumption of the second effective time period after the adjacent unit areas matched in other virtual models are superimposed is performed simultaneously with the step of sequentially superimposing the adjacent unit area areas; the area after the adjacent unit areas matched in the virtual model are superimposed is locked, and the locked area is sequentially matched with the heat consumption of the first effective time period and the heat consumption of the second effective time period preset in the commercial area, residential area, industrial area, scenic area and other areas, and the locked area is marked as the corresponding area name with the lowest difference rate between the heat consumption of the first effective time period and the heat consumption of the second effective time period, and the corresponding area name includes the commercial area, residential area, industrial area, scenic area and other areas; The event monitoring submodule is used to retrieve a heating relationship distribution map in a region, wherein the heating relationship distribution map includes at least n influencing data related to the amount of heating in the region and weight data of the influence of the at least n influencing data related to the amount of heating in the region on the heating relationship distribution map. When it is monitored that the influencing data reaches a preset value and preset category information appears, it is marked as heating change influencing data, and the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map is retrieved from the heating relationship distribution map, wherein n is the minimum preset value of the number of influencing data related to the amount of heating in the region; based on the commercial area, residential area, industrial area, scenic area and other areas, the location information of the commercial area, residential area, industrial area, scenic area and other areas in the heating relationship distribution map is retrieved from the heating relationship distribution map. The location information of the commercial area and other areas in the heating relationship distribution map is used to divide the heating demand change impact data into the commercial area, residential area, industrial area, scenic area and other areas in turn, and marked as event A, event B, event C, event D and event E in turn. The number of the heating demand change impact data contained in event A, event B, event C, event D and event E is not less than one, and the heating demand change impact data contained in event A, event B, event C, event D and event E is multiplied by the impact weight data of the heating relationship distribution map corresponding to the heating demand change impact data, so as to obtain the heating demand change values ​​of event A, event B, event C, event D and event E respectively.

10. The AI-based intelligent control system for heating stations according to claim 9 is characterized in that: The control module includes a monitoring result acquisition module and a heat supply allocation module; The monitoring result acquisition module is used to mark the obtained heating demand change values ​​of event A, event B, event C, event D and event E as the obtained heating monitoring result of the heating station; The heat supply allocation module is used to allocate heat supply to the area corresponding to the area name. Among them, X F is the reference value of the number of people in the corresponding area name, Y F The heat consumption of the area corresponding to the area name, when the heat consumption difference rate of the first effective time period is lower than the preset minimum difference rate λ%, the heat consumption of the first effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the second effective time period is selected as Y F When the difference in heat consumption during the second effective time period is lower than the preset minimum difference λ%, the second effective time period with a difference in heat consumption lower than the preset minimum difference λ% is selected; when the difference in heat consumption during the first effective time period and the second effective time period is lower than the preset minimum difference λ%, the heat consumption during the corresponding effective time period with a larger difference between the heat consumption during the first effective time period and the heat consumption during the second effective time period is selected as Y F , and monitor the change of the difference rate of heat consumption between the first effective time period and the second effective time period at any time, and convert Y according to the above selection method F The specific calorie consumption value, Z F is the change value of the regional heating demand corresponding to the event, G is a preset level, and after the preset level G is multiplied by the difference rate λ, the multiplication result is controlled to be within 10 of the multiple of the reference difference rate λ0, λ0 is the reference difference rate, 0<λ0<70%.

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