Heat supply management system

Abstract

The invention relates to the technical field of heat supply management, and discloses a heat supply management system, which is characterized in that a preliminary auditing module audits a network access application and executes a network access operation; the curve fitting module obtains real-time heat supply data of the current time node and determines a heat supply data fitting curve; the first calculation module extracts the maximum fitting slope and calculates a heat supply abnormal coefficient; a second calculation module collects heat supply flow data and heat supply temperature data within a preset duration range before the current time node and calculates a historical heat supply response coefficient; the data optimization module optimizes the heat supply abnormal coefficient based on the historical heat supply response coefficient to obtain a target heat supply abnormal coefficient; and the acceptance signing module judges whether abnormal operation exists or not according to the target heat supply abnormal coefficient, if not, acceptance work is carried out, a formal contract is signed with the user, the abnormal state of the heat supply system is predicted in advance, energy consumption and the fault occurrence probability are reduced, the intelligence of heat supply acceptance management is guaranteed, and the reliability of network access process management is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of heat supply management, and in particular to a heat supply management system. Background Art

[0002] The heating system consists of a heat source, a heat circulation system and a heat dissipation device. It heats low-temperature hot coal and transports it indoors, and then releases the heat through the heat dissipation device to keep the room warm. This system is particularly important in cold regions to ensure a comfortable living and working environment for residents.

[0003] Traditional heating acceptance management relies on manual monitoring and empirical judgment, lacks real-time and scientific nature, and leads to frequent heating failures and serious energy waste. This approach is difficult to handle large-scale, high-dimensional data and has obvious technical bottlenecks. In addition, existing heating monitoring and control technologies focus on optimizing a single link and lack comprehensive evaluation of overall performance and fault analysis. Traditional methods have limitations in data processing and analysis, making it difficult to effectively cope with complex and changing heating environments, and unable to guarantee efficient acceptance work or ensure that service quality meets standard requirements. Summary of the invention

[0004] The embodiment of the present invention provides a heat supply management system, which predicts the abnormal state of the heat supply system in advance through real-time monitoring, data analysis and intelligent diagnosis, ensures the intelligence of the heat supply acceptance management, ensures efficient acceptance work, and ensures that the service quality meets the standard requirements.

[0005] In order to achieve the above object, the present invention provides a heat supply management system, comprising: A preliminary review module is used to receive network access applications from different types of users, review the network access applications according to preset rules, and execute network access operations when the user passes the review; A curve fitting module is used to obtain the real-time heating data corresponding to the heating system at the current time node after executing the network access operation, determine the standard heating data corresponding to the real-time heating data, and determine the heating data fitting curve according to the real-time heating data and the standard heating data; a first calculation module, configured to analyze the heating data fitting curve, extract a maximum fitting slope from the heating data fitting curve, and calculate a heating abnormality coefficient of the heating system based on the maximum fitting slope; The second calculation module is used to collect the heating flow data and heating temperature data of the heating system within a preset time range before the current time node, and calculate the historical heating response coefficient of the heating system according to the heating flow data and heating temperature data; A data optimization module, configured to set an optimization coefficient based on the historical heating response coefficient, and optimize the heating abnormality coefficient based on the optimization coefficient to obtain a target heating abnormality coefficient of the heating system; The acceptance and signing module is used to determine whether the heating system has abnormal operation based on the target heating abnormality coefficient and the preset target heating abnormality coefficient. If not, acceptance work is carried out and a formal contract is signed with the user.

[0006] Furthermore, the curve fitting module is used for: The curve fitting module is used to calculate the heating data difference between the real-time heating data and the standard heating data, and construct a heating data difference sequence; The curve fitting module is used to determine an allowable heating data error range corresponding to the heating system, wherein the allowable heating data error range includes a first allowable heating data error and a second allowable heating data error; The curve fitting module is used for removing all heating data differences in the heating data difference sequence that are within the allowable heating data error range based on the allowable heating data error range, and obtaining a second heating data difference sequence; The curve fitting module is used to fit the heating data difference in the second heating data difference sequence to obtain the heating data fitting curve.

[0007] Furthermore, the first calculation module is used for: The first calculation module is used to construct a first data interval according to the first allowable heating data error and the standard data error; The first calculation module is used to construct a second data interval according to the second allowable heating data error and the standard data error; The first calculation module is used to analyze the removed heating data differences and count the number of first heating data differences falling within the first data interval; The first calculation module is used to count the number of second heating data difference values ​​of the heating data difference values ​​falling within the second data interval; The first calculation module is used to calculate the heating abnormality coefficient of the heating system according to the first heating data difference quantity and the second heating data difference quantity.

[0008] Furthermore, the first calculation module is used for: The first calculation module is used to calculate the heating abnormality coefficient of the heating system according to the following formula: ; Among them, a1 is the heating anomaly coefficient of the heating system, n is the number of heating data differences removed, and b iis the i-th removed heating data difference, e1 is the first allowable heating data error, e2 is the second allowable heating data error, f1=n1 / (n1+n2), n1 is the number of the first heating data differences, n2 is the number of the second heating data differences, f2=n2 / (n1+n2), g is the adjustment coefficient of the heating anomaly coefficient, and h is the maximum fitting slope.

[0009] Furthermore, the first calculation module is used for: The first calculation module is used to determine the adjustment coefficient g of the heating abnormality coefficient according to the following steps; The first calculation module is used to count a first number n3 of heating data differences on the heating data fitting curve; The first calculation module is used to pre-set a first preset adjustment coefficient, a second preset adjustment coefficient and a third preset adjustment coefficient; The first calculation module is used for selecting the first preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when n3 / (n1+n2)<1; The first calculation module is used for selecting the second preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when 1≤n3 / (n1+n2)<1.2; The first calculation module is used for selecting the third preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when 1.2≤n3 / (n1+n2).

[0010] Furthermore, the second calculation module is used for: The second calculation module is used to divide the preset time range into multiple time node intervals, and determine the first heating flow data and the second heating flow data of each time node interval, wherein the first heating flow data is the heating flow data corresponding to the end time of each time node interval, and the second heating flow data is the difference between the heating flow data corresponding to the start time and the end time of each time node interval; The second calculation module is used to determine a first historical heating response coefficient of the heating system according to the first heating flow data and the second heating flow data, wherein the first historical heating response coefficient is a product value of the first heating flow data and the second heating flow data; The second calculation module is used to determine the first heating temperature data and the second heating temperature data of each time node interval, wherein the first heating temperature data is the heating temperature data corresponding to the end time of each time node interval, and the second heating temperature data is the heating temperature data difference between the heating temperature data corresponding to the start time and the end time of each time node interval; The second calculation module is used to determine a second historical heating response coefficient of the heating system according to the first heating temperature data and the second heating temperature data, wherein the second historical heating response coefficient is a product value of the first heating temperature data and the second heating temperature data; The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to each time node interval according to the first historical heating response coefficient and the second historical heating response coefficient; The second calculation module is used to calculate the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients.

[0011] Furthermore, the second calculation module is used for: The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to the time node interval according to the following formula: ; Among them, k is the comprehensive historical heating response coefficient, p1 is the first calculation coefficient, q1 is the first historical heating response coefficient, q2 is the second historical heating response coefficient, p2 is the second calculation coefficient, p1<0, p2<0.

[0012] Furthermore, the second calculation module is used for: The second calculation module is used to extract the same comprehensive historical heating response coefficient from all comprehensive historical heating response coefficients, and obtain multiple comprehensive historical heating response coefficient sequences; The second calculation module is used to count the number of the first comprehensive historical heating response coefficient sequence of the comprehensive historical heating response coefficient sequence; The second calculation module is used to extract a comprehensive historical heating response coefficient from all comprehensive historical heating response coefficient sequences, and calculate the first comprehensive historical heating response coefficient and value; The second calculation module is used to obtain a preset preset comprehensive historical heating response coefficient, eliminate all comprehensive historical heating response coefficient sequences that are less than the preset comprehensive historical heating response coefficient, and count the number of second comprehensive historical heating response coefficient sequences of the remaining comprehensive historical heating response coefficient sequences; The second calculation module is used to extract a comprehensive historical heating response coefficient from the remaining comprehensive historical heating response coefficient sequence, and calculate the second comprehensive historical heating response coefficient and value; The second calculation module is used to calculate the historical heating response coefficient of the heating system according to the first comprehensive historical heating response coefficient sequence number, the second comprehensive historical heating response coefficient sequence number, the first comprehensive historical heating response coefficient sum value and the second comprehensive historical heating response coefficient sum value.

[0013] Furthermore, the data optimization module is used to: Presetting a first preset historical heating response coefficient and a second preset historical heating response coefficient; Presetting a first preset optimization coefficient, a second preset optimization coefficient, and a third preset optimization coefficient; When the historical heating response coefficient is less than the first preset historical heating response coefficient, the product value of the first preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system; When the historical heating response coefficient is greater than or equal to the first preset historical heating response coefficient and less than the second preset historical heating response coefficient, the product value of the second preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system; When the historical heating response coefficient is greater than or equal to the second preset historical heating response coefficient, the product value of the third preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system.

[0014] Furthermore, the acceptance signing module is used to: The acceptance signing module is used to determine that there is no abnormal operation of the heating system when the target heating abnormality coefficient is less than the preset target heating abnormality coefficient; The acceptance signing module is used to determine that the heating system is operating abnormally when the target heating abnormality coefficient is greater than or equal to the preset target heating abnormality coefficient.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a heat supply management system, wherein a preliminary review module reviews a network access application and executes a network access operation; a curve fitting module obtains real-time heat supply data at a current time node and determines a heat supply data fitting curve; a first calculation module extracts a maximum fitting slope and calculates a heat supply anomaly coefficient; a second calculation module collects heat supply flow data and heat supply temperature data within a preset time range before the current time node and calculates a historical heat supply response coefficient; a data optimization module optimizes the heat supply anomaly coefficient based on the historical heat supply response coefficient and obtains a target heat supply anomaly coefficient; an acceptance signing module determines whether there is an abnormal operation according to the target heat supply anomaly coefficient, and if not, an acceptance work is carried out, a formal contract is signed with the user, and the abnormal state of the heat supply system is predicted in advance, energy consumption and the probability of failure are reduced, the intelligence of the heat supply acceptance management is ensured, and the reliability of the network access process management is ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A schematic structural diagram of a heat supply management system in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0017] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0018] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0019] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0020] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0021] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0022] like Figure 1 As shown, an embodiment of the present invention discloses a heat management system, comprising: A preliminary review module is used to receive network access applications from different types of users, review the network access applications according to preset rules, and execute network access operations when the user passes the review; A curve fitting module is used to obtain the real-time heating data corresponding to the heating system at the current time node after executing the network access operation, determine the standard heating data corresponding to the real-time heating data, and determine the heating data fitting curve according to the real-time heating data and the standard heating data; a first calculation module, configured to analyze the heating data fitting curve, extract a maximum fitting slope from the heating data fitting curve, and calculate a heating abnormality coefficient of the heating system based on the maximum fitting slope; The second calculation module is used to collect the heating flow data and heating temperature data of the heating system within a preset time range before the current time node, and calculate the historical heating response coefficient of the heating system according to the heating flow data and heating temperature data; A data optimization module, configured to set an optimization coefficient based on the historical heating response coefficient, and optimize the heating abnormality coefficient based on the optimization coefficient to obtain a target heating abnormality coefficient of the heating system; The acceptance and signing module is used to determine whether the heating system has abnormal operation based on the target heating abnormality coefficient and the preset target heating abnormality coefficient. If not, acceptance work is carried out and a formal contract is signed with the user.

[0023] In this embodiment, network access applications are received from different types of users (including communities, hospitals, factories and small users).

[0024] In this embodiment, the contact application service can be provided to small users through a mini-program or a web page.

[0025] In this embodiment, it is determined whether the heating system is operating abnormally based on the target heating abnormality coefficient and the preset target heating abnormality coefficient, and acceptance work can be performed to ensure that the service quality meets the standard requirements.

[0026] In this embodiment, a formal contract is signed with the user to clarify the rights and obligations of both parties.

[0027] In this embodiment, during the entire process, the system can track the progress of each node in real time and send reminder notifications to relevant personnel; the platform will store all user information and historical data that have participated in the network access process for a long time as a record material for future contact or inquiry. In this embodiment, the real-time heating data includes water supply temperature, return water temperature, heating pressure and heating flow.

[0028] In this embodiment, the standard heating data corresponds to the real-time heating data one by one, and is specifically determined according to actual conditions.

[0029] The beneficial effect of the above technical solution is that the present invention predicts the abnormal state of the heating system in advance, thereby improving the operating efficiency and stability of the heating system, reducing energy consumption and the probability of failure.

[0030] In some embodiments of the present application, the curve fitting module is used to: The curve fitting module is used to calculate the heating data difference between the real-time heating data and the standard heating data, and construct a heating data difference sequence; The curve fitting module is used to determine an allowable heating data error range corresponding to the heating system, wherein the allowable heating data error range includes a first allowable heating data error and a second allowable heating data error; The curve fitting module is used for removing all heating data differences in the heating data difference sequence that are within the allowable heating data error range based on the allowable heating data error range, and obtaining a second heating data difference sequence; The curve fitting module is used to fit the heating data difference in the second heating data difference sequence to obtain the heating data fitting curve.

[0031] In this embodiment, the heating data difference is the absolute value of the difference between the real-time heating data and the standard heating data.

[0032] In this embodiment, the allowable error range is set by the staff. During actual heating, a certain error is allowed. For example, if the allowable heating data error range is temperature, the first allowable heating data error is -1°C, and the second allowable heating data error is 2°C.

[0033] The beneficial effect of the above technical solution is: the present invention fits the heating data difference in the second heating data difference sequence to obtain a heating data fitting curve. By obtaining the heating data fitting curve, the present invention can lay a foundation for subsequent analysis.

[0034] In some embodiments of the present application, the first computing module is used to: The first calculation module is used to construct a first data interval according to the first allowable heating data error and the standard data error; The first calculation module is used to construct a second data interval according to the second allowable heating data error and the standard data error; The first calculation module is used to analyze the removed heating data differences and count the number of first heating data differences falling within the first data interval; The first calculation module is used to count the number of second heating data difference values ​​of the heating data difference values ​​falling within the second data interval; The first calculation module is used to calculate the heating abnormality coefficient of the heating system according to the first heating data difference quantity and the second heating data difference quantity.

[0035] In this embodiment, the method for determining the slope will not be repeated here, and the maximum slope can be taken.

[0036] In this embodiment, the standard data error is 0. As mentioned above, the first data interval is constructed based on -1°C and 0, and the second data interval is constructed based on 0 and 2°C.

[0037] In this embodiment, the removed heating data differences fall into one of the two intervals, so the number of first heating data differences and the number of second heating data differences can be counted.

[0038] The beneficial effect of the above technical solution is that the present invention calculates the heating anomaly coefficient of the heating system according to the first heating data difference number and the second heating data difference number, thereby ensuring the calculation accuracy of the heating anomaly coefficient and avoiding errors.

[0039] In some embodiments of the present application, the first computing module is used to: The first calculation module is used to calculate the heating abnormality coefficient of the heating system according to the following formula: ; Among them, a1 is the heating anomaly coefficient of the heating system, n is the number of heating data differences removed, and b i is the i-th removed heating data difference, e1 is the first allowable heating data error, e2 is the second allowable heating data error, f1=n1 / (n1+n2), n1 is the number of the first heating data differences, n2 is the number of the second heating data differences, f2=n2 / (n1+n2), g is the adjustment coefficient of the heating anomaly coefficient, and h is the maximum fitting slope.

[0040] In some embodiments of the present application, the first computing module is used to: The first calculation module is used to determine the adjustment coefficient g of the heating abnormality coefficient according to the following steps; The first calculation module is used to count a first number n3 of heating data differences on the heating data fitting curve; The first calculation module is used to pre-set a first preset adjustment coefficient, a second preset adjustment coefficient and a third preset adjustment coefficient; The first calculation module is used for selecting the first preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when n3 / (n1+n2)<1; The first calculation module is used for selecting the second preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when 1≤n3 / (n1+n2)<1.2; The first calculation module is used for selecting the third preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when 1.2≤n3 / (n1+n2).

[0041] In this embodiment, the first preset adjustment coefficient is preferably 0.85, the second preset adjustment coefficient is preferably 1.15, and the third preset adjustment coefficient is preferably 1.25.

[0042] The beneficial effect of the above technical solution is: the present invention selects different adjustment coefficients according to the first number of heating data differences on the heating data fitting curve, thereby realizing dynamic adjustment of the heating abnormality coefficient and further ensuring calculation accuracy.

[0043] In some embodiments of the present application, the second computing module is used to: The second calculation module is used to divide the preset time range into multiple time node intervals, and determine the first heating flow data and the second heating flow data of each time node interval, wherein the first heating flow data is the heating flow data corresponding to the end time of each time node interval, and the second heating flow data is the difference between the heating flow data corresponding to the start time and the end time of each time node interval; The second calculation module is used to determine a first historical heating response coefficient of the heating system according to the first heating flow data and the second heating flow data, wherein the first historical heating response coefficient is a product value of the first heating flow data and the second heating flow data; The second calculation module is used to determine the first heating temperature data and the second heating temperature data of each time node interval, wherein the first heating temperature data is the heating temperature data corresponding to the end time of each time node interval, and the second heating temperature data is the heating temperature data difference between the heating temperature data corresponding to the start time and the end time of each time node interval; The second calculation module is used to determine a second historical heating response coefficient of the heating system according to the first heating temperature data and the second heating temperature data, wherein the second historical heating response coefficient is a product value of the first heating temperature data and the second heating temperature data; The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to each time node interval according to the first historical heating response coefficient and the second historical heating response coefficient; The second calculation module is used to calculate the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients.

[0044] In this embodiment, the preset duration range can be set to 10 minutes, and the multiple time node intervals are {0,2}, {2,4}, {4,6}, {6,8}, {8,10}, in minutes, and can also be set according to actual conditions.

[0045] In this embodiment, the first heating data is the heating flow data corresponding to the 2nd minute, the 4th minute, the 6th minute, the 8th minute and the 10th minute.

[0046] In this embodiment, the second heating flow rate data is the difference between the heating flow rate data at the 4th minute and the heating flow rate data at the 2nd minute. The rest are not shown one by one.

[0047] In this embodiment, the first heating temperature data and the second heating temperature data are determined in the same manner as described above and will not be described again here.

[0048] In this embodiment, the comprehensive historical heating response coefficient corresponding to each time node interval can be obtained.

[0049] The beneficial effect of the above technical solution is that the present invention calculates the historical heating response coefficient of the heating system based on all the comprehensive historical heating response coefficients, avoids the calculation errors existing in manual calculation, and provides a prerequisite basis for the optimization of the heating abnormality coefficient.

[0050] In some embodiments of the present application, the second computing module is used to: The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to the time node interval according to the following formula: ; Among them, k is the comprehensive historical heating response coefficient, p1 is the first calculation coefficient, q1 is the first historical heating response coefficient, q2 is the second historical heating response coefficient, p2 is the second calculation coefficient, p1<0, p2<0.

[0051] In some embodiments of the present application, the second computing module is used to: The second calculation module is used to extract the same comprehensive historical heating response coefficient from all comprehensive historical heating response coefficients, and obtain multiple comprehensive historical heating response coefficient sequences; The second calculation module is used to count the number of the first comprehensive historical heating response coefficient sequence of the comprehensive historical heating response coefficient sequence; The second calculation module is used to extract a comprehensive historical heating response coefficient from all comprehensive historical heating response coefficient sequences, and calculate the first comprehensive historical heating response coefficient and value; The second calculation module is used to obtain a preset preset comprehensive historical heating response coefficient, eliminate all comprehensive historical heating response coefficient sequences that are less than the preset comprehensive historical heating response coefficient, and count the number of second comprehensive historical heating response coefficient sequences of the remaining comprehensive historical heating response coefficient sequences; The second calculation module is used to extract a comprehensive historical heating response coefficient from the remaining comprehensive historical heating response coefficient sequence, and calculate the second comprehensive historical heating response coefficient and value; The second calculation module is used to calculate the historical heating response coefficient of the heating system according to the first comprehensive historical heating response coefficient sequence number, the second comprehensive historical heating response coefficient sequence number, the first comprehensive historical heating response coefficient sum value and the second comprehensive historical heating response coefficient sum value.

[0052] In this embodiment, if multiple comprehensive historical heating response coefficient sequences are obtained, {2,2}, {4,4,4}, {6,6}, {8,8,8}. The number of the first comprehensive historical heating response coefficient sequences is 4, and one comprehensive historical heating response coefficient is extracted from all the comprehensive historical heating response coefficient sequences, that is, 2,4,6,8. The preset comprehensive historical heating response coefficient is 3, and the remaining comprehensive historical heating response coefficient sequences are {4,4,4}, {6,6}, {8,8,8}. One comprehensive historical heating response coefficient is extracted from the remaining comprehensive historical heating response coefficient sequences, that is, 4,6,8.

[0053] In this embodiment, the historical heating response coefficient of the heating system is calculated according to the following formula: ; Among them, u is the historical heating response coefficient of the heating system, w1 is the number of the first comprehensive historical heating response coefficient sequence, w2 is the number of the second comprehensive historical heating response coefficient sequence, w3 is the sum of the first comprehensive historical heating response coefficient, and w4 is the sum of the second comprehensive historical heating response coefficient.

[0054] The beneficial effect of the above technical solution is that the present invention calculates the historical heating response coefficient of the heating system according to the number of first comprehensive historical heating response coefficient sequences, the number of second comprehensive historical heating response coefficient sequences, the sum of the first comprehensive historical heating response coefficient and the sum of the second comprehensive historical heating response coefficient, thereby ensuring the calculation accuracy of the historical heating response coefficient.

[0055] In some embodiments of the present application, the data optimization module is used to: Presetting a first preset historical heating response coefficient and a second preset historical heating response coefficient; Presetting a first preset optimization coefficient, a second preset optimization coefficient, and a third preset optimization coefficient; When the historical heating response coefficient is less than the first preset historical heating response coefficient, the product value of the first preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system; When the historical heating response coefficient is greater than or equal to the first preset historical heating response coefficient and less than the second preset historical heating response coefficient, the product value of the second preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system; When the historical heating response coefficient is greater than or equal to the second preset historical heating response coefficient, the product value of the third preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system.

[0056] In this embodiment, the first preset historical heating response coefficient is preferably 6, and the second preset historical heating response coefficient is preferably 9.

[0057] In this embodiment, the first preset optimization coefficient is preferably 0.95, the second preset optimization coefficient is preferably 1.05, and the third preset optimization coefficient is preferably 1.1.

[0058] The beneficial effect of the above technical solution is that the present invention sets the optimization coefficient according to the historical heating response coefficient, the first preset historical heating response coefficient and the second preset historical heating response coefficient, thereby achieving fine-tuning of the heating abnormality coefficient and ensuring the comprehensiveness of the calculation.

[0059] In some embodiments of the present application, the acceptance signing module is used to: The acceptance signing module is used to determine that there is no abnormal operation of the heating system when the target heating abnormality coefficient is less than the preset target heating abnormality coefficient; The acceptance signing module is used to determine that the heating system is operating abnormally when the target heating abnormality coefficient is greater than or equal to the preset target heating abnormality coefficient.

[0060] In this embodiment, the preset target heating abnormality coefficient is 8.

[0061] The beneficial effect of the above technical solution is: the present invention determines whether there is abnormal operation according to the target heating abnormality coefficient and the preset target heating abnormality coefficient, and predicts the abnormal state of the heating system in advance, thereby improving the operating efficiency and stability of the heating system, and reducing energy consumption and the probability of failure.

[0062] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0063] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed by the present invention may be used in combination with each other in any manner, and the fact that these combinations are not fully described in this specification is only for the sake of omitting space and saving resources.

[0064] Those skilled in the art can understand that the above are only preferred embodiments of the present invention and are 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 recorded 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 heat supply management system, characterized in that: include: A preliminary review module is used to receive network access applications from different types of users, review the network access applications according to preset rules, and execute network access operations when the user passes the review; A curve fitting module is used to obtain the real-time heating data corresponding to the heating system at the current time node after executing the network access operation, determine the standard heating data corresponding to the real-time heating data, and determine the heating data fitting curve according to the real-time heating data and the standard heating data; a first calculation module, configured to analyze the heating data fitting curve, extract a maximum fitting slope from the heating data fitting curve, and calculate a heating abnormality coefficient of the heating system based on the maximum fitting slope; The second calculation module is used to collect the heating flow data and heating temperature data of the heating system within a preset time range before the current time node, and calculate the historical heating response coefficient of the heating system according to the heating flow data and heating temperature data; A data optimization module, configured to set an optimization coefficient based on the historical heating response coefficient, and optimize the heating abnormality coefficient based on the optimization coefficient to obtain a target heating abnormality coefficient of the heating system; The acceptance and signing module is used to determine whether the heating system has abnormal operation based on the target heating abnormality coefficient and the preset target heating abnormality coefficient. If not, acceptance work is carried out and a formal contract is signed with the user.

2. The heat management system according to claim 1, characterized in that: The curve fitting module is used for: The curve fitting module is used to calculate the heating data difference between the real-time heating data and the standard heating data, and construct a heating data difference sequence; The curve fitting module is used to determine an allowable heating data error range corresponding to the heating system, wherein the allowable heating data error range includes a first allowable heating data error and a second allowable heating data error; The curve fitting module is used for removing all heating data differences in the heating data difference sequence that are within the allowable heating data error range based on the allowable heating data error range, and obtaining a second heating data difference sequence; The curve fitting module is used to fit the heating data difference in the second heating data difference sequence to obtain the heating data fitting curve.

3. The heat management system according to claim 2, characterized in that: The first calculation module is used for: The first calculation module is used to construct a first data interval according to the first allowable heating data error and the standard data error; The first calculation module is used to construct a second data interval according to the second allowable heating data error and the standard data error; The first calculation module is used to analyze the removed heating data differences and count the number of first heating data differences falling within the first data interval; The first calculation module is used to count the number of second heating data difference values ​​of the heating data difference values ​​falling within the second data interval; The first calculation module is used to calculate the heating abnormality coefficient of the heating system according to the first heating data difference quantity and the second heating data difference quantity.

4. The heat management system according to claim 3, characterized in that: The first calculation module is used for: The first calculation module is used to calculate the heating abnormality coefficient of the heating system according to the following formula: ； Among them, a1 is the heating anomaly coefficient of the heating system, n is the number of heating data differences removed, and b i is the i-th removed heating data difference, e1 is the first allowable heating data error, e2 is the second allowable heating data error, f1=n1 / (n1+n2), n1 is the number of the first heating data differences, n2 is the number of the second heating data differences, f2=n2 / (n1+n2), g is the adjustment coefficient of the heating anomaly coefficient, and h is the maximum fitting slope.

5. The heat management system according to claim 4, characterized in that: The first calculation module is used for: The first calculation module is used to determine the adjustment coefficient g of the heating abnormality coefficient according to the following steps; The first calculation module is used to count a first number n3 of heating data differences on the heating data fitting curve; The first calculation module is used to pre-set a first preset adjustment coefficient, a second preset adjustment coefficient and a third preset adjustment coefficient; The first calculation module is used for selecting the first preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when n3 / (n1+n2)<1; The first calculation module is used for selecting the second preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when 1≤n3 / (n1+n2)<1.2; The first calculation module is used for selecting the third preset adjustment coefficient as the adjustment coefficient g of the heating abnormality coefficient when 1.2≤n3 / (n1+n2).

6. The heat management system according to claim 1, characterized in that: The second calculation module is used for: The second calculation module is used to divide the preset time range into multiple time node intervals, and determine the first heating flow data and the second heating flow data of each time node interval, wherein the first heating flow data is the heating flow data corresponding to the end time of each time node interval, and the second heating flow data is the difference between the heating flow data corresponding to the start time and the end time of each time node interval; The second calculation module is used to determine a first historical heating response coefficient of the heating system according to the first heating flow data and the second heating flow data, wherein the first historical heating response coefficient is a product value of the first heating flow data and the second heating flow data; The second calculation module is used to determine the first heating temperature data and the second heating temperature data of each time node interval, wherein the first heating temperature data is the heating temperature data corresponding to the end time of each time node interval, and the second heating temperature data is the heating temperature data difference between the heating temperature data corresponding to the start time and the end time of each time node interval; The second calculation module is used to determine a second historical heating response coefficient of the heating system according to the first heating temperature data and the second heating temperature data, wherein the second historical heating response coefficient is a product value of the first heating temperature data and the second heating temperature data; The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to each time node interval according to the first historical heating response coefficient and the second historical heating response coefficient; The second calculation module is used to calculate the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients.

7. The heat management system according to claim 6, characterized in that: The second calculation module is used for: The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to the time node interval according to the following formula: ； Among them, k is the comprehensive historical heating response coefficient, p1 is the first calculation coefficient, q1 is the first historical heating response coefficient, q2 is the second historical heating response coefficient, p2 is the second calculation coefficient, p1<0, p2<0.

8. The heat management system according to claim 1, characterized in that: The second calculation module is used for: The second calculation module is used to extract the same comprehensive historical heating response coefficient from all comprehensive historical heating response coefficients, and obtain multiple comprehensive historical heating response coefficient sequences; The second calculation module is used to count the number of the first comprehensive historical heating response coefficient sequence of the comprehensive historical heating response coefficient sequence; The second calculation module is used to extract a comprehensive historical heating response coefficient from all comprehensive historical heating response coefficient sequences, and calculate the first comprehensive historical heating response coefficient and value; The second calculation module is used to obtain a preset preset comprehensive historical heating response coefficient, eliminate all comprehensive historical heating response coefficient sequences that are less than the preset comprehensive historical heating response coefficient, and count the number of second comprehensive historical heating response coefficient sequences of the remaining comprehensive historical heating response coefficient sequences; The second calculation module is used to extract a comprehensive historical heating response coefficient from the remaining comprehensive historical heating response coefficient sequence, and calculate the second comprehensive historical heating response coefficient and value; The second calculation module is used to calculate the historical heating response coefficient of the heating system according to the first comprehensive historical heating response coefficient sequence number, the second comprehensive historical heating response coefficient sequence number, the first comprehensive historical heating response coefficient sum value and the second comprehensive historical heating response coefficient sum value.

9. The heat management system according to claim 1, characterized in that: The data optimization module is used for: Presetting a first preset historical heating response coefficient and a second preset historical heating response coefficient; Presetting a first preset optimization coefficient, a second preset optimization coefficient, and a third preset optimization coefficient; When the historical heating response coefficient is less than the first preset historical heating response coefficient, the product value of the first preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system; When the historical heating response coefficient is greater than or equal to the first preset historical heating response coefficient and less than the second preset historical heating response coefficient, the product value of the second preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system; When the historical heating response coefficient is greater than or equal to the second preset historical heating response coefficient, the product value of the third preset optimization coefficient and the heating abnormality coefficient is calculated and used as the target heating abnormality coefficient of the heating system.

10. The heat management system according to claim 1, characterized in that: The acceptance signing module is used for: The acceptance signing module is used to determine that there is no abnormal operation of the heating system when the target heating abnormality coefficient is less than the preset target heating abnormality coefficient; The acceptance signing module is used to determine that the heating system is operating abnormally when the target heating abnormality coefficient is greater than or equal to the preset target heating abnormality coefficient.

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