Method and device for regulating and controlling heat supply state of distributed heat supply system

Abstract

The invention relates to a heat supply state regulation and control method and device of a distributed heat supply system. The heat supply state regulation and control method of the distributed heat supply system comprises the steps that heat supply state data of the distributed heat supply system in a normal heat supply state and influence factor data influencing the heat supply state are obtained; on the basis of a clustering model, the influence factors influencing the heat supply state serve as clustering indexes, the heat supply state data in the normal heat supply state are clustered, and heat supply state data corresponding to different influence factor threshold intervals are obtained; based on the heat supply state data corresponding to the different influence factor threshold intervals, heat supply state judgment thresholds of the distributed heat supply system corresponding to the different influence factor threshold intervals are determined, so that heat supply state analysis and diagnosis are conducted on the heat supply state data, collected in real time, of the distributed heat supply system, and a diagnosis result is obtained; therefore, the accuracy of the diagnosis result of the heat supply state and the regulation and control quality of the heat supply state of the distributed heat supply system can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of integrated energy heating technology, and in particular to a heating state control method for a distributed heating system, a heating state control device for a distributed heating system, a storage medium and an electronic device. Background Art

[0002] With the continuous adjustment of national energy policies and the continuous improvement of environmental protection requirements, energy conservation and emission reduction have become the consensus and responsibility of the whole society. Traditional heating systems have some problems, such as high energy consumption and large heat loss. These are possible problems of heating systems. However, the problems of different heating systems may be different. This brings uncertainty to the solution of heating system problems. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure are intended to provide a method for controlling a heating state of a distributed heating system, a device for controlling a heating state of a distributed heating system, a storage medium, and an electronic device.

[0004] The technical solution of the present disclosure is achieved as follows:

[0005] In a first aspect, the present disclosure provides a method for controlling a heating state of a distributed heating system.

[0006] The method for controlling the heating state of a distributed heating system provided in the embodiment of the present disclosure includes:

[0007] Obtaining heating status data of the distributed heating system under normal heating status and data of factors affecting the heating status of the heating system;

[0008] Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators, and the heating state data of the distributed heating system under the normal heating state is clustered to obtain the heating state data corresponding to the threshold intervals of different influencing factors;

[0009] Based on the heating state data corresponding to the different influencing factor threshold intervals, determining the heating state judgment thresholds of the distributed heating system corresponding to the different influencing factor threshold intervals;

[0010] Based on the heating state judgment threshold of the distributed heating system under the normal heating state, the heating state data of the distributed heating system collected in real time is analyzed and diagnosed to obtain the diagnosis result of the real-time heating state of the distributed heating system;

[0011] Based on the diagnosis result of the real-time heating status of the distributed heating system, the heating status of the distributed heating system is regulated.

[0012] In some embodiments, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects;

[0013] Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating state data of the distributed heating system under the normal heating state, and obtain the heating state data corresponding to different threshold intervals of the influencing factors, including:

[0014] Based on the clustering model, taking the outdoor temperature that affects the thermal index of the heating system as the clustering index, the thermal index data of the distributed heating system under the normal heating state is clustered to obtain the thermal index data corresponding to different outdoor temperature threshold intervals;

[0015] Based on the clustering model, taking the outdoor temperature that affects the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project as the clustering index, clustering the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project, and obtaining the deviation data between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals; and

[0016] Based on the clustering model, the water supply flow that affects the deviation between the water supply temperature and the set value of the water supply temperature of the heating system is taken as the clustering index. The deviation between the water supply temperature and the set value of the water supply temperature of the heating system is clustered to obtain the deviation data between the water supply temperature and the set value of the water supply temperature of the heating system corresponding to different water supply flow threshold intervals.

[0017] In some embodiments, the determining of the heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals based on the heating state data corresponding to the different influencing factor threshold intervals includes:

[0018] For the heating status data corresponding to the different influencing factor threshold intervals, respectively determine the average value and standard deviation of the heating status data corresponding to each influencing factor threshold interval;

[0019] Based on the average value and standard deviation of the heating status data corresponding to the threshold intervals of each influencing factor, the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor is determined.

[0020] In some embodiments, the determining of the heating state judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval based on the average value and standard deviation of the heating state data corresponding to each influencing factor threshold interval includes:

[0021] Based on the average value and standard deviation of the thermal index data corresponding to different outdoor temperature threshold intervals, determining the thermal index state judgment threshold corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0022] Based on the average value and standard deviation of the deviation data between the average indoor temperature of users of the heating system and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals, determine the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0023] Based on the average value and standard deviation of the deviation data between the water supply temperature and the water supply temperature setting value of the heating system corresponding to different water supply flow threshold intervals, the deviation state judgment threshold between the water supply temperature and the water supply temperature setting value of the heating system corresponding to the distributed heating system corresponding to different water supply flow threshold intervals is determined.

[0024] In some embodiments, the heating state judgment threshold under the normal heating state of the distributed heating system is used to analyze and diagnose the heating state data of the distributed heating system collected in real time, and the diagnosis result of the real-time heating state of the distributed heating system is obtained, including:

[0025] If the total excess rate of the thermal indexes corresponding to the distributed heating systems corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment thresholds corresponding to the respective outdoor temperature threshold intervals is greater than a first percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is that the indoor temperature heating excess rate is high;

[0026] If the total exceeding rate of the deviation between the average indoor temperature of users of the heating system corresponding to different outdoor temperature threshold intervals and the average indoor temperature of the project exceeds the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is greater than the second percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is a poor hydraulic balance;

[0027] If the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow threshold intervals exceeds the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value corresponding to each water supply flow threshold interval is greater than the third percentage, then the diagnostic result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve.

[0028] In some embodiments, the heat supply state regulation of the distributed heat supply system based on the diagnosis result of the real-time heat supply state of the distributed heat supply system includes:

[0029] If the diagnosis result of the real-time heating status of the distributed heating system is that the indoor temperature heating excess rate is high, then adjusting the water supply temperature setting value of the distributed heating system according to the outdoor temperature;

[0030] If it is determined that the diagnosis result of the real-time heating status of the distributed heating system is poor hydraulic balance, the frequency of the electric frequency water pump is adjusted to adjust the input power of the electric frequency water pump;

[0031] If the diagnosis result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve, the water supply pipeline valve is replaced or optimized.

[0032] In some embodiments, the determining of the heating state judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval based on the average value and standard deviation of the heating state data corresponding to each influencing factor threshold interval includes:

[0033] The cumulative sum of the average value of the heating status data corresponding to the threshold intervals of each influencing factor and the standard deviation is used as the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor.

[0034] In a second aspect, the present disclosure provides a heating state control device for a distributed heating system, comprising:

[0035] A data acquisition module is used to acquire the heating status data of the distributed heating system under normal heating status and the data of influencing factors affecting the heating status of the heating system;

[0036] A sample clustering module is used to cluster the heating status data of the distributed heating system under normal heating status based on the clustering model and taking the influencing factors affecting the heating status of the heating system as clustering indicators to obtain heating status data corresponding to different threshold intervals of influencing factors;

[0037] A judgment threshold determination module, used to determine the heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals based on the heating state data corresponding to the different influencing factor threshold intervals;

[0038] A heating status diagnosis module is used to analyze and diagnose the heating status data of the distributed heating system collected in real time based on the heating status judgment threshold of the distributed heating system under normal heating status, so as to obtain a diagnosis result of the real-time heating status of the distributed heating system;

[0039] The heating status control module is used to control the heating status of the distributed heating system based on the diagnosis result of the real-time heating status of the distributed heating system.

[0040] In a third aspect, the present disclosure provides a computer-readable storage medium on which a heating state control program of a distributed heating system is stored. When the heating state control program of the distributed heating system is executed by a processor, the heating state control method of the distributed heating system described in the first aspect is implemented.

[0041] In a fourth aspect, the present disclosure provides an electronic device comprising a memory, a processor, and a heating state control program for a distributed heating system stored in the memory and executable on the processor, wherein when the processor executes the heating state control program for the distributed heating system, the heating state control method for the distributed heating system described in the first aspect is implemented.

[0042] According to the embodiment of the present disclosure, the heating state control method of the distributed heating system includes obtaining the heating state data of the distributed heating system under the normal heating state and the influencing factor data affecting the heating state of the heating system; based on the clustering model, the heating state data of the distributed heating system under the normal heating state is clustered with the influencing factors affecting the heating state of the heating system as the clustering index, and the heating state data corresponding to different influencing factor threshold intervals are obtained; based on the heating state data corresponding to different influencing factor threshold intervals, the heating state judgment thresholds of the distributed heating system corresponding to different influencing factor threshold intervals are determined; based on the heating state judgment thresholds under the normal heating state of the distributed heating system, the heating state analysis and diagnosis are performed on the heating state data of the distributed heating system collected in real time, and the diagnosis result of the real-time heating state of the distributed heating system is obtained; based on the diagnosis result of the real-time heating state of the distributed heating system, the heating state control of the distributed heating system is performed. In the present application, a large amount of heating status data under the normal heating state of the distributed heating system and data on influencing factors affecting the heating state of the heating system are obtained. Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating status data under the normal heating state of the distributed heating system, and the heating status data and heating status judgment thresholds corresponding to different influencing factor threshold intervals are obtained. The real-time heating status diagnosis of the distributed heating system is performed through the heating status judgment thresholds corresponding to different influencing factor threshold intervals, which is conducive to achieving more refined analysis and improving the accuracy of the heating status diagnosis results, and further conducive to improving the heating status regulation quality of the distributed heating system.

[0043] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of a method for controlling a heating state of a distributed heating system according to an exemplary embodiment;

[0045] Figure 2 A heating problem diagnosis process of a distributed heating system according to an exemplary embodiment is shown Figure 1 ;

[0046] Figure 3 A heating problem diagnosis process of a distributed heating system according to an exemplary embodiment is shown Figure 2 ;

[0047] Figure 4 It is a schematic diagram of the structure of a heating state control device of a distributed heating system according to an exemplary embodiment. DETAILED DESCRIPTION

[0048] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0049] With the continuous adjustment of national energy policies and the continuous improvement of environmental protection requirements, energy conservation and emission reduction have become the consensus and responsibility of the whole society. Traditional heating systems have some problems, such as high energy consumption and large heat loss. These are possible problems of heating systems. However, the problems of different heating systems may be different. This brings uncertainty to the solution of heating system problems.

[0050] In view of the above situation, the present disclosure provides a method for controlling the heating state of a distributed heating system. Figure 1 FIG. 1 is a flow chart of a method for controlling the heating state of a distributed heating system according to an exemplary embodiment. Figure 1 As shown, the heating state control method of the distributed heating system includes:

[0051] Step 10: Acquire the heating status data of the distributed heating system under normal heating status and the data of the influencing factors affecting the heating status of the heating system;

[0052] Step 11: Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating state data of the distributed heating system under the normal heating state to obtain the heating state data corresponding to the threshold intervals of different influencing factors;

[0053] Step 12: Based on the heating state data corresponding to the different influencing factor threshold intervals, determine the heating state judgment thresholds of the distributed heating system corresponding to the different influencing factor threshold intervals;

[0054] Step 13: Based on the heating state judgment threshold of the distributed heating system under the normal heating state, the heating state data of the distributed heating system collected in real time is analyzed and diagnosed to obtain the diagnosis result of the real-time heating state of the distributed heating system;

[0055] Step 14: Based on the diagnosis result of the real-time heating status of the distributed heating system, the heating status of the distributed heating system is regulated.

[0056] In this exemplary embodiment, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects.

[0057] q is the heat index, Q is the cumulative heat supply, A is the heating area, HDD is the degree day; Δt 偏 =t 供 -t 设 ;t 供 is the hourly average water supply temperature. The water supply temperature in this application refers to the hourly average water supply temperature; t 设 Δt is the hourly average water supply temperature setting value; 偏 The deviation between the water supply temperature of the heating system and the set value of the water supply temperature;

[0058] is the average indoor temperature of the user, t i is the user's indoor temperature at the i-th moment in the hour, and m is the total number of user indoor temperature records;

[0059]

[0060] is the average indoor temperature of the project;

[0061] t j is the average indoor temperature of the jth user;

[0062] k is the total number of users with indoor temperature.

[0063] The indoor temperature exceeding standard rate of the project;

[0064] n 超 The total number of hours that the indoor temperature of the project exceeds the standard;

[0065] n 总 The total number of records of the project's hourly average indoor temperature.

[0066] In this exemplary embodiment, based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating state data of the distributed heating system in the normal heating state, and obtain the heating state data corresponding to the threshold intervals of different influencing factors. In the process of data collection, due to the instability of the influencing factors affecting the heating state of the heating system, this will cause the degree of influence of the influencing factors on the heating state of the heating system to be different in different threshold intervals. In order to improve the accuracy of the diagnosis and analysis of the heating state of the heating system, the clustering model can be used to cluster the influencing factors affecting the heating state of the heating system as clustering indicators to cluster the heating state data of the distributed heating system in the normal heating state, and obtain the heating state data corresponding to the threshold intervals of different influencing factors. For example, when the influencing factor is outdoor temperature, the outdoor temperature may include a larger range interval, for example, -0.5℃~-25℃. This interval can be divided into -0.5℃~-5℃~, -5℃~-15℃, -20℃~-25℃~, and so on according to the degree of data concentration. In this way, the heating status data corresponding to different outdoor temperature threshold intervals can be obtained. The water supply flow rate is also an influencing factor. The heating status data of the distributed heating system in the normal heating state can be clustered according to the threshold interval of the water supply flow rate to obtain the heating status data corresponding to the threshold interval of no water supply flow rate. The water supply flow rate includes a first threshold interval, a second threshold interval, a third threshold interval, and so on. In this way, the clustering model can be used to obtain the heating status data corresponding to the first threshold interval, the second threshold interval, and the third threshold interval of the water supply flow rate.

[0067] Then, based on the heating state data corresponding to different influencing factor threshold intervals, the heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals is determined; based on the heating state judgment threshold under the normal heating state of the distributed heating system, the heating state data of the distributed heating system collected in real time is analyzed and diagnosed to obtain the diagnosis result of the real-time heating state of the distributed heating system; based on the diagnosis result of the real-time heating state of the distributed heating system, the heating state of the distributed heating system is regulated. In this application, by obtaining a large amount of heating state data under the normal heating state of the distributed heating system and the influencing factor data affecting the heating state of the heating system, based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators, and the heating state data under the normal heating state of the distributed heating system are clustered to obtain the heating state data and heating state judgment threshold corresponding to different influencing factor threshold intervals. The real-time heating state diagnosis of the distributed heating system is performed through the heating state judgment threshold corresponding to different influencing factor threshold intervals, which is conducive to achieving more refined analysis, improving the accuracy of the heating state diagnosis results, and thus helping to improve the heating state regulation quality of the distributed heating system.

[0068] In some embodiments, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects;

[0069] Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating state data of the distributed heating system under the normal heating state, and obtain the heating state data corresponding to different threshold intervals of the influencing factors, including:

[0070] Based on the clustering model, taking the outdoor temperature that affects the thermal index of the heating system as the clustering index, the thermal index data of the distributed heating system under the normal heating state is clustered to obtain the thermal index data corresponding to different outdoor temperature threshold intervals;

[0071] Based on the clustering model, taking the outdoor temperature that affects the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project as the clustering index, clustering the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project, and obtaining the deviation data between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals; and

[0072] Based on the clustering model, the water supply flow that affects the deviation between the water supply temperature and the set value of the water supply temperature of the heating system is taken as the clustering index. The deviation between the water supply temperature and the set value of the water supply temperature of the heating system is clustered to obtain the deviation data between the water supply temperature and the set value of the water supply temperature of the heating system corresponding to different water supply flow threshold intervals.

[0073] In this exemplary embodiment, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects. Therefore, when clustering data, the thermal index data of the distributed heating system in the normal heating state can be clustered based on the clustering model, taking the outdoor temperature affecting the thermal index of the heating system as the clustering index, to obtain thermal index data corresponding to different outdoor temperature threshold intervals;

[0074] Based on the clustering model, taking the outdoor temperature that affects the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project as the clustering index, clustering the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project, and obtaining the deviation data between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals; and

[0075] Based on the clustering model, the water supply flow rate that affects the deviation between the water supply temperature and the set value of the water supply temperature of the heating system is used as the clustering index. The deviation between the water supply temperature and the set value of the water supply temperature of the heating system is clustered to obtain the deviation data between the water supply temperature and the set value of the water supply temperature of the heating system corresponding to different water supply flow rate threshold intervals. In this way, the clustering division of the heating status data corresponding to different influencing factor threshold intervals can be achieved, providing a more accurate analysis basis for the subsequent diagnosis and analysis of the heating status of the heating system.

[0076] In some embodiments, the determining of the heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals based on the heating state data corresponding to the different influencing factor threshold intervals includes:

[0077] For the heating status data corresponding to the different influencing factor threshold intervals, respectively determine the average value and standard deviation of the heating status data corresponding to each influencing factor threshold interval;

[0078] Based on the average value and standard deviation of the heating status data corresponding to the threshold intervals of each influencing factor, the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor is determined.

[0079] In this exemplary embodiment,

[0080] σ is the standard deviation of the heating status data corresponding to the threshold interval of each influencing factor;

[0081] x i is the i-th indicator data in the interval;

[0082] is the average value of all indicator data in the interval;

[0083] is the lower limit threshold of the heating state judgment threshold corresponding to the distributed heating system;

[0084] It is the upper limit threshold of the heating status judgment threshold corresponding to the distributed heating system; in this application, when performing heating status diagnosis and analysis, the upper limit threshold of the heating status judgment threshold can be used as the heating status judgment threshold to participate in the heating status diagnosis and analysis of the heating system.

[0085] In some embodiments, the determining of the heating state judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval based on the average value and standard deviation of the heating state data corresponding to each influencing factor threshold interval includes:

[0086] Based on the average value and standard deviation of the thermal index data corresponding to different outdoor temperature threshold intervals, determining the thermal index state judgment threshold corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0087] Based on the average value and standard deviation of the deviation data between the average indoor temperature of users of the heating system and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals, determine the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0088] Based on the average value and standard deviation of the deviation data between the water supply temperature and the water supply temperature setting value of the heating system corresponding to different water supply flow threshold intervals, the deviation state judgment threshold between the water supply temperature and the water supply temperature setting value of the heating system corresponding to the distributed heating system corresponding to different water supply flow threshold intervals is determined.

[0089] In this exemplary embodiment, since there are multiple influencing factors and heating status data, when determining the heating status judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval, the determination can be performed separately, including: determining the thermal index status judgment threshold corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals based on the average value and standard deviation of the thermal index data corresponding to different outdoor temperature threshold intervals;

[0090] Based on the average value and standard deviation of the deviation data between the average indoor temperature of users of the heating system and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals, determine the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0091] Based on the average value and standard deviation of the deviation data between the water supply temperature of the heating system and the water supply temperature setting value corresponding to different water supply flow rate threshold intervals, the state judgment threshold of the deviation state between the water supply temperature of the heating system and the water supply temperature setting value corresponding to the distributed heating system corresponding to different water supply flow rate threshold intervals is determined. In this way, the different factors that can be obtained are used to determine the judgment threshold of the heating state of the heating system, thereby providing a more accurate analysis basis for the subsequent diagnosis and analysis of the heating state of the heating system.

[0092] In some embodiments, the heating state judgment threshold under the normal heating state of the distributed heating system is used to analyze and diagnose the heating state data of the distributed heating system collected in real time, and the diagnosis result of the real-time heating state of the distributed heating system is obtained, including:

[0093] If the total excess rate of the thermal indexes corresponding to the distributed heating systems corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment thresholds corresponding to the respective outdoor temperature threshold intervals is greater than a first percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is that the indoor temperature heating excess rate is high;

[0094] If the total exceeding rate of the deviation between the average indoor temperature of users of the heating system corresponding to different outdoor temperature threshold intervals and the average indoor temperature of the project exceeds the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is greater than the second percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is a poor hydraulic balance;

[0095] If the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow threshold intervals exceeds the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value corresponding to each water supply flow threshold interval is greater than the third percentage, then the diagnostic result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve.

[0096] In this exemplary embodiment, based on the heating state judgment threshold value under the normal heating state of the distributed heating system, when the heating state analysis and diagnosis of the distributed heating system heating state data collected in real time is performed, the distributed heating system heating state data collected in real time can be combined with the heating state judgment threshold value under the normal heating state of the distributed heating system to perform a comprehensive analysis and judgment to determine the heating state of the heating system. For example, if the total excess rate of the thermal index corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold value corresponding to each outdoor temperature threshold interval is greater than the first percentage, then the diagnosis result of the real-time heating state of the distributed heating system is determined to be a high indoor temperature heating excess rate;

[0097] If the total exceeding rate of the deviation between the average indoor temperature of users of the heating system corresponding to different outdoor temperature threshold intervals and the average indoor temperature of the project exceeds the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is greater than the second percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is a poor hydraulic balance;

[0098] If the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow rate threshold intervals exceeds the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value deviation corresponding to each water supply flow rate threshold interval is greater than the third percentage, then the diagnosis result of the real-time heating state of the distributed heating system is determined to be poor water supply pipeline valve regulation performance. Among them, the first percentage, the second percentage, and the third percentage can be set as needed. For example, the first percentage is 40%, the second percentage is 30%, and the third percentage is 50%. Among them, the total excess rate of the thermal index corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold corresponding to each outdoor temperature threshold interval includes:

[0099] The different outdoor temperature threshold intervals include n outdoor temperature threshold intervals (x1, x2...xn);

[0100] The total excess rate of the thermal index corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold corresponding to each outdoor temperature threshold interval is P1;

[0101] P1 = (a1 + a2 + a3 + ... + an) / (A1 + A2 + A3 + ... + An); a1 is the number of users whose thermal indexes in the outdoor temperature threshold interval x1 exceed the thermal index state judgment threshold corresponding to the outdoor temperature threshold interval x1; an is the number of users whose thermal indexes in the outdoor temperature threshold interval xn exceed the thermal index state judgment threshold corresponding to the outdoor temperature threshold interval xn; A1 is the total number of users corresponding to the outdoor temperature threshold interval a1; An is the total number of users corresponding to the outdoor temperature threshold interval an;

[0102] The total excess rate of the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals exceeding the state judgment threshold of the deviation between the average indoor temperature of the users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is P2;

[0103] P2=(b1+b2+b3+…+bn) / (B1+B2+B3+…+Bn); b1 is the number of users whose average indoor temperature of the heating system users corresponding to the outdoor temperature threshold interval x1 deviates from the average indoor temperature of the project, exceeding the state judgment threshold of the average indoor temperature of the users corresponding to the outdoor temperature threshold interval x1 and the average indoor temperature of the project; bn is the number of users whose average indoor temperature of the heating system users corresponding to the outdoor temperature threshold interval xn deviates from the average indoor temperature of the project, exceeding the state judgment threshold of the average indoor temperature of the users corresponding to the outdoor temperature threshold interval xn and the average indoor temperature of the project; B1 is the total number of users corresponding to the outdoor temperature threshold interval x1; Bn is the total number of users corresponding to the outdoor temperature threshold interval xn;

[0104] The total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow rate threshold intervals exceeding the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value deviation corresponding to each water supply flow rate threshold interval is P3;

[0105] P3=(c1+c2+c3+…+cn) / (C1+C2+C3+…+Cn); c1 is the number of users whose water supply temperature of the heating system corresponding to the water supply flow threshold interval x1 deviates from the water supply temperature setting value and exceeds the state judgment threshold of the water supply flow threshold interval x1; cn is the number of users whose water supply temperature of the heating system corresponding to the outdoor temperature threshold interval xn deviates from the water supply temperature setting value and exceeds the state judgment threshold of the water supply flow threshold interval xn; C1 is the total number of users corresponding to the outdoor temperature threshold interval c1; Cn is the total number of users corresponding to the outdoor temperature threshold interval cn. In this way, by comparing the total excess rate of the thermal index corresponding to the distributed heating system corresponding to the above different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold corresponding to the respective outdoor temperature threshold intervals with the first percentage, the problem of the indoor temperature heating excess rate is determined, thereby determining the heating state of the heating system. The hydraulic balance state in the real-time heating state of the distributed heating system is determined by comparing the total excess rate of the deviation between the average indoor temperature of the heating system users and the project average indoor temperature corresponding to the above-mentioned different outdoor temperature threshold intervals and the state judgment threshold of the average indoor temperature of the users and the project average indoor temperature corresponding to the respective outdoor temperature threshold intervals with the second percentage.

[0106] The regulating performance of the water supply pipe valve of the heating system is determined by comparing the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to the above-mentioned different water supply flow threshold intervals exceeding the state judgment threshold of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to each water supply flow threshold interval with the third percentage.

[0107] In some embodiments, the heat supply state regulation of the distributed heat supply system based on the diagnosis result of the real-time heat supply state of the distributed heat supply system includes:

[0108] If the diagnosis result of the real-time heating status of the distributed heating system is that the indoor temperature heating excess rate is high, then adjusting the water supply temperature setting value of the distributed heating system according to the outdoor temperature;

[0109] If it is determined that the diagnosis result of the real-time heating status of the distributed heating system is poor hydraulic balance, the frequency of the electric frequency water pump is adjusted to adjust the input power of the electric frequency water pump;

[0110] If the diagnosis result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve, the water supply pipeline valve is replaced or optimized.

[0111] In this exemplary embodiment, when it is determined that the real-time heating state of the distributed heating system is abnormal, specific abnormal state processing measures can be taken according to the specific abnormal state to solve the abnormal heating problem of the heating system. For example, if the diagnosis result of the real-time heating state of the distributed heating system is that the indoor temperature heating over-standard rate is high, the water supply temperature setting value of the distributed heating system is adjusted according to the outdoor temperature;

[0112] If it is determined that the diagnosis result of the real-time heating status of the distributed heating system is poor hydraulic balance, the frequency of the electric frequency water pump is adjusted to adjust the input power of the electric frequency water pump;

[0113] If the diagnosis result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve, the water supply pipeline valve is replaced or optimized.

[0114] In the present application, when diagnosing the heating status of the heating system, if there are multiple problems mentioned above, the water supply status can be adjusted at the same time. For example, if there are problems of poor hydraulic balance and poor regulating performance of the water supply pipeline valve at the same time, the frequency of the electric frequency water pump can be adjusted to adjust the input power of the electric frequency water pump while replacing or optimizing the water supply pipeline valve.

[0115] In some embodiments, the determining of the heating state judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval based on the average value and standard deviation of the heating state data corresponding to each influencing factor threshold interval includes:

[0116] The cumulative sum of the average value of the heating status data corresponding to the threshold intervals of each influencing factor and the standard deviation is used as the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor.

[0117] Figure 2 A heating problem diagnosis process of a distributed heating system according to an exemplary embodiment is shown Figure 1 .like Figure 2 As shown in the figure, the heating problem diagnosis process of the distributed heating system includes:

[0118] Step 20, configure diagnostic rules: configure diagnostic rules for distributed heating and define the data required by the diagnostic rules;

[0119] Step 21, obtaining data: obtaining required data from the local automatic control system or database;

[0120] Step 22, data processing: processing the data obtained from the local control system or database, including eliminating non-heating period data, abnormal data processing, data calculation, and storing the original data and processed data;

[0121] Step 23, data diagnosis: according to the diagnosis rules configured in the diagnosis knowledge base, use the acquired data to diagnose the project and output the diagnosis problems and suggestions;

[0122] Step 24: Results presentation: present diagnostic issues and suggestions.

[0123] Figure 3 A heating problem diagnosis process of a distributed heating system according to an exemplary embodiment is shown Figure 2 .like Figure 3 As shown in the figure, the heating problem diagnosis process of the distributed heating system includes:

[0124] Step 30, obtaining the hot index of the query time;

[0125] Step 31: Determine whether the thermal index exceeds 70 kJ / m 2 / DD, end if not exceeded;

[0126] Step 32: Thermal index exceeds 70 kJ / m 2 / DD, then get the hourly indoor temperature during the query time;

[0127] Step 33, calculating the indoor temperature exceeding standard rate within the query time;

[0128] Step 34, determine whether the indoor temperature exceeding the standard rate exceeds 40%, if not, end;

[0129] Step 35: If the indoor temperature exceeding standard rate exceeds 40%, it is determined that the indoor temperature exceeding standard rate is high;

[0130] Step 36: If the indoor temperature exceeds the standard rate, optimize the temperature regulation;

[0131] Step 37, obtaining the hourly water supply temperature and the water supply temperature setting value within the query time;

[0132] Step 38, calculating the cumulative number of hours that the absolute value of the difference between the water supply temperature and the water supply temperature setting value exceeds 2°C;

[0133] Step 39, determine whether the proportion of the absolute value of the difference exceeding 2°C in the total time is greater than 30%, if not, end;

[0134] Step 40: If the absolute value of the difference exceeds 2°C for a proportion of the total time greater than 30%, it is determined that the valve regulation performance is poor;

[0135] Step 41: If it is determined that the valve regulation performance is poor, the regulating valve is optimized / replaced;

[0136] Step 42, obtaining the average indoor temperature of each user and the average indoor temperature of the project at the query time;

[0137] Step 43, calculating the difference between the average indoor temperature of each user and the project;

[0138] Step 44, determine whether the proportion of the difference between the indoor temperature of each user and the indoor temperature of the project evaluation exceeding 2°C exceeds 50%, if not, end;

[0139] Step 45, if the difference between the indoor temperature of each user and the indoor temperature of the project evaluation exceeds 2°C, the hydraulic balance difference is determined;

[0140] Step 46: Determine if the hydraulic balance is poor, and adjust the hydraulic balance.

[0141] The present disclosure provides a heating state control device for a distributed heating system. Figure 4 FIG. 1 is a schematic diagram of a heating state control device of a distributed heating system according to an exemplary embodiment. Figure 4 As shown, the heating state control device of the distributed heating system includes:

[0142] The data acquisition module 40 is used to acquire the heating status data of the distributed heating system under normal heating status and the data of the influencing factors affecting the heating status of the heating system;

[0143] The sample clustering module 41 is used to cluster the heating status data of the distributed heating system under normal heating status based on the clustering model and taking the influencing factors affecting the heating status of the heating system as clustering indicators to obtain heating status data corresponding to different threshold intervals of influencing factors;

[0144] A judgment threshold determination module 42, configured to determine a heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals based on the heating state data corresponding to the different influencing factor threshold intervals;

[0145] A heating state diagnosis module 43 is used to analyze and diagnose the heating state data of the distributed heating system collected in real time based on the heating state judgment threshold of the distributed heating system in the normal heating state, and obtain a diagnosis result of the real-time heating state of the distributed heating system;

[0146] The heating state control module 44 is used to control the heating state of the distributed heating system based on the diagnosis result of the real-time heating state of the distributed heating system.

[0147] In this exemplary embodiment, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects.

[0148] q is the heat index, Q is the cumulative heat supply, A is the heating area, HDD is the degree day; Δt 偏 =t 供 -t 设 ;t 供 is the hourly average water supply temperature. The water supply temperature in this application refers to the hourly average water supply temperature; t 设 Δt is the hourly average water supply temperature setting value; 偏 The deviation between the water supply temperature of the heating system and the set value of the water supply temperature;

[0149] is the average indoor temperature of the user, t i is the user's indoor temperature at the i-th moment in the hour, and m is the total number of user indoor temperature records;

[0150]

[0151] is the average indoor temperature of the project;

[0152] t j is the average indoor temperature of the jth user;

[0153] k is the total number of users with indoor temperature.

[0154] The indoor temperature exceeding standard rate of the project;

[0155] n 超 The total number of hours that the indoor temperature of the project exceeds the standard;

[0156] n 总 The total number of records of the project's hourly average indoor temperature.

[0157] In this exemplary embodiment, based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating state data of the distributed heating system in the normal heating state, and obtain the heating state data corresponding to the threshold intervals of different influencing factors. In the process of data collection, due to the instability of the influencing factors affecting the heating state of the heating system, this will cause the degree of influence of the influencing factors on the heating state of the heating system to be different in different threshold intervals. In order to improve the accuracy of the diagnosis and analysis of the heating state of the heating system, the clustering model can be used to cluster the influencing factors affecting the heating state of the heating system as clustering indicators to cluster the heating state data of the distributed heating system in the normal heating state, and obtain the heating state data corresponding to the threshold intervals of different influencing factors. For example, when the influencing factor is outdoor temperature, the outdoor temperature may include a larger range interval, for example, -0.5℃~-25℃. This interval can be divided into -0.5℃~-5℃~, -5℃~-15℃, -20℃~-25℃~, and so on according to the degree of data concentration. In this way, the heating status data corresponding to different outdoor temperature threshold intervals can be obtained. The water supply flow rate is also an influencing factor. The heating status data of the distributed heating system in the normal heating state can be clustered according to the threshold interval of the water supply flow rate to obtain the heating status data corresponding to the threshold interval of no water supply flow rate. The water supply flow rate includes a first threshold interval, a second threshold interval, a third threshold interval, and so on. In this way, the clustering model can be used to obtain the heating status data corresponding to the first threshold interval, the second threshold interval, and the third threshold interval of the water supply flow rate.

[0158] Then, based on the heating state data corresponding to different influencing factor threshold intervals, the heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals is determined; based on the heating state judgment threshold under the normal heating state of the distributed heating system, the heating state data of the distributed heating system collected in real time is analyzed and diagnosed to obtain the diagnosis result of the real-time heating state of the distributed heating system; based on the diagnosis result of the real-time heating state of the distributed heating system, the heating state of the distributed heating system is regulated. In this application, by obtaining a large amount of heating state data under the normal heating state of the distributed heating system and the influencing factor data affecting the heating state of the heating system, based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators, and the heating state data under the normal heating state of the distributed heating system are clustered to obtain the heating state data and heating state judgment threshold corresponding to different influencing factor threshold intervals. The real-time heating state diagnosis of the distributed heating system is performed through the heating state judgment threshold corresponding to different influencing factor threshold intervals, which is conducive to achieving more refined analysis, improving the accuracy of the heating state diagnosis results, and thus helping to improve the heating state regulation quality of the distributed heating system.

[0159] In some embodiments, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects;

[0160] The sample clustering module 41 is used to

[0161] Based on the clustering model, taking the outdoor temperature that affects the thermal index of the heating system as the clustering index, the thermal index data of the distributed heating system under the normal heating state is clustered to obtain the thermal index data corresponding to different outdoor temperature threshold intervals;

[0162] Based on the clustering model, taking the outdoor temperature that affects the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project as the clustering index, clustering the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project, and obtaining the deviation data between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals; and

[0163] Based on the clustering model, the water supply flow that affects the deviation between the water supply temperature and the set value of the water supply temperature of the heating system is taken as the clustering index. The deviation between the water supply temperature and the set value of the water supply temperature of the heating system is clustered to obtain the deviation data between the water supply temperature and the set value of the water supply temperature of the heating system corresponding to different water supply flow threshold intervals.

[0164] In this exemplary embodiment, the heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of projects; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of projects. Therefore, when clustering data, the thermal index data of the distributed heating system in the normal heating state can be clustered based on the clustering model, taking the outdoor temperature affecting the thermal index of the heating system as the clustering index, to obtain thermal index data corresponding to different outdoor temperature threshold intervals;

[0165] Based on the clustering model, taking the outdoor temperature that affects the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project as the clustering index, clustering the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project, and obtaining the deviation data between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals; and

[0166] Based on the clustering model, the water supply flow rate that affects the deviation between the water supply temperature and the set value of the water supply temperature of the heating system is used as the clustering index. The deviation between the water supply temperature and the set value of the water supply temperature of the heating system is clustered to obtain the deviation data between the water supply temperature and the set value of the water supply temperature of the heating system corresponding to different water supply flow rate threshold intervals. In this way, the clustering division of the heating status data corresponding to different influencing factor threshold intervals can be achieved, providing a more accurate analysis basis for the subsequent diagnosis and analysis of the heating status of the heating system.

[0167] In some embodiments, the judgment threshold determination module 42 is used to

[0168] For the heating status data corresponding to the different influencing factor threshold intervals, respectively determine the average value and standard deviation of the heating status data corresponding to each influencing factor threshold interval;

[0169] Based on the average value and standard deviation of the heating status data corresponding to the threshold intervals of each influencing factor, the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor is determined.

[0170] In this exemplary embodiment,

[0171] σ is the standard deviation of the heating status data corresponding to the threshold interval of each influencing factor;

[0172] x i is the i-th indicator data in the interval;

[0173] is the average value of all indicator data in the interval;

[0174] is the lower limit threshold of the heating state judgment threshold corresponding to the distributed heating system;

[0175] It is the upper limit threshold of the heating status judgment threshold corresponding to the distributed heating system; in this application, when performing heating status diagnosis and analysis, the upper limit threshold of the heating status judgment threshold can be used as the heating status judgment threshold to participate in the heating status diagnosis and analysis of the heating system.

[0176] In some embodiments, the judgment threshold determination module 42 is used to

[0177] Based on the average value and standard deviation of the thermal index data corresponding to different outdoor temperature threshold intervals, determining the thermal index state judgment threshold corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0178] Based on the average value and standard deviation of the deviation data between the average indoor temperature of users of the heating system and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals, determine the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0179] Based on the average value and standard deviation of the deviation data between the water supply temperature and the water supply temperature setting value of the heating system corresponding to different water supply flow threshold intervals, the deviation state judgment threshold between the water supply temperature and the water supply temperature setting value of the heating system corresponding to the distributed heating system corresponding to different water supply flow threshold intervals is determined.

[0180] In this exemplary embodiment, since there are multiple influencing factors and heating status data, when determining the heating status judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval, the determination can be performed separately, including: determining the thermal index status judgment threshold corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals based on the average value and standard deviation of the thermal index data corresponding to different outdoor temperature threshold intervals;

[0181] Based on the average value and standard deviation of the deviation data between the average indoor temperature of users of the heating system and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals, determine the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals;

[0182] Based on the average value and standard deviation of the deviation data between the water supply temperature of the heating system and the water supply temperature setting value corresponding to different water supply flow rate threshold intervals, the state judgment threshold of the deviation state between the water supply temperature of the heating system and the water supply temperature setting value corresponding to the distributed heating system corresponding to different water supply flow rate threshold intervals is determined. In this way, the different factors that can be obtained are used to determine the judgment threshold of the heating state of the heating system, thereby providing a more accurate analysis basis for the subsequent diagnosis and analysis of the heating state of the heating system.

[0183] In some embodiments, the heating status diagnosis module 43 is used to

[0184] If the total excess rate of the thermal indexes corresponding to the distributed heating systems corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment thresholds corresponding to the respective outdoor temperature threshold intervals is greater than a first percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is that the indoor temperature heating excess rate is high;

[0185] If the total exceeding rate of the deviation between the average indoor temperature of users of the heating system corresponding to different outdoor temperature threshold intervals and the average indoor temperature of the project exceeds the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is greater than the second percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is a poor hydraulic balance;

[0186] If the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow threshold intervals exceeds the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value corresponding to each water supply flow threshold interval is greater than the third percentage, then the diagnostic result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve.

[0187] In this exemplary embodiment, based on the heating state judgment threshold value under the normal heating state of the distributed heating system, when the heating state analysis and diagnosis of the distributed heating system heating state data collected in real time is performed, the distributed heating system heating state data collected in real time can be combined with the heating state judgment threshold value under the normal heating state of the distributed heating system to perform a comprehensive analysis and judgment to determine the heating state of the heating system. For example, if the total excess rate of the thermal index corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold value corresponding to each outdoor temperature threshold interval is greater than the first percentage, then the diagnosis result of the real-time heating state of the distributed heating system is determined to be a high indoor temperature heating excess rate;

[0188] If the total exceeding rate of the deviation between the average indoor temperature of users of the heating system corresponding to different outdoor temperature threshold intervals and the average indoor temperature of the project exceeds the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is greater than the second percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is a poor hydraulic balance;

[0189] If the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow rate threshold intervals exceeds the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value deviation corresponding to each water supply flow rate threshold interval is greater than the third percentage, then the diagnosis result of the real-time heating state of the distributed heating system is determined to be poor water supply pipeline valve regulation performance. Among them, the first percentage, the second percentage, and the third percentage can be set as needed. For example, the first percentage is 40%, the second percentage is 30%, and the third percentage is 50%. Among them, the total excess rate of the thermal index corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold corresponding to each outdoor temperature threshold interval includes:

[0190] The different outdoor temperature threshold intervals include n outdoor temperature threshold intervals (x1, x2...xn);

[0191] The total excess rate of the thermal index corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold corresponding to each outdoor temperature threshold interval is P1;

[0192] P1 = (a1 + a2 + a3 + ... + an) / (A1 + A2 + A3 + ... + An); a1 is the number of users whose thermal indexes in the outdoor temperature threshold interval x1 exceed the thermal index state judgment threshold corresponding to the outdoor temperature threshold interval x1; an is the number of users whose thermal indexes in the outdoor temperature threshold interval xn exceed the thermal index state judgment threshold corresponding to the outdoor temperature threshold interval xn; A1 is the total number of users corresponding to the outdoor temperature threshold interval a1; An is the total number of users corresponding to the outdoor temperature threshold interval an;

[0193] The total excess rate of the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals exceeding the state judgment threshold of the deviation between the average indoor temperature of the users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is P2;

[0194] P2=(b1+b2+b3+…+bn) / (B1+B2+B3+…+Bn); b1 is the number of users whose average indoor temperature of the heating system users corresponding to the outdoor temperature threshold interval x1 deviates from the average indoor temperature of the project, exceeding the state judgment threshold of the average indoor temperature of the users corresponding to the outdoor temperature threshold interval x1 and the average indoor temperature of the project; bn is the number of users whose average indoor temperature of the heating system users corresponding to the outdoor temperature threshold interval xn deviates from the average indoor temperature of the project, exceeding the state judgment threshold of the average indoor temperature of the users corresponding to the outdoor temperature threshold interval xn and the average indoor temperature of the project; B1 is the total number of users corresponding to the outdoor temperature threshold interval x1; Bn is the total number of users corresponding to the outdoor temperature threshold interval xn;

[0195] The total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow rate threshold intervals exceeding the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value deviation corresponding to each water supply flow rate threshold interval is P3;

[0196] P3=(c1+c2+c3+…+cn) / (C1+C2+C3+…+Cn); c1 is the number of users whose water supply temperature of the heating system corresponding to the water supply flow threshold interval x1 deviates from the water supply temperature setting value and exceeds the state judgment threshold of the water supply flow threshold interval x1; cn is the number of users whose water supply temperature of the heating system corresponding to the outdoor temperature threshold interval xn deviates from the water supply temperature setting value and exceeds the state judgment threshold of the water supply flow threshold interval xn; C1 is the total number of users corresponding to the outdoor temperature threshold interval c1; Cn is the total number of users corresponding to the outdoor temperature threshold interval cn. In this way, by comparing the total excess rate of the thermal index corresponding to the distributed heating system corresponding to the above different outdoor temperature threshold intervals exceeding the thermal index state judgment threshold corresponding to the respective outdoor temperature threshold intervals with the first percentage, the problem of the indoor temperature heating excess rate is determined, thereby determining the heating state of the heating system. The hydraulic balance state in the real-time heating state of the distributed heating system is determined by comparing the total excess rate of the deviation between the average indoor temperature of the heating system users and the project average indoor temperature corresponding to the above-mentioned different outdoor temperature threshold intervals and the state judgment threshold of the average indoor temperature of the users and the project average indoor temperature corresponding to the respective outdoor temperature threshold intervals with the second percentage.

[0197] The regulating performance of the water supply pipe valve of the heating system is determined by comparing the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to the above-mentioned different water supply flow threshold intervals exceeding the state judgment threshold of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to each water supply flow threshold interval with the third percentage.

[0198] In some embodiments, the heating state control module 44 is used to

[0199] If the diagnosis result of the real-time heating status of the distributed heating system is that the indoor temperature heating excess rate is high, then adjusting the water supply temperature setting value of the distributed heating system according to the outdoor temperature;

[0200] If it is determined that the diagnosis result of the real-time heating status of the distributed heating system is poor hydraulic balance, the frequency of the electric frequency water pump is adjusted to adjust the input power of the electric frequency water pump;

[0201] If the diagnosis result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve, the water supply pipeline valve is replaced or optimized.

[0202] In this exemplary embodiment, when it is determined that the real-time heating state of the distributed heating system is abnormal, specific abnormal state processing measures can be taken according to the specific abnormal state to solve the abnormal heating problem of the heating system. For example, if the diagnosis result of the real-time heating state of the distributed heating system is that the indoor temperature heating over-standard rate is high, the water supply temperature setting value of the distributed heating system is adjusted according to the outdoor temperature;

[0203] If it is determined that the diagnosis result of the real-time heating status of the distributed heating system is poor hydraulic balance, the frequency of the electric frequency water pump is adjusted to adjust the input power of the electric frequency water pump;

[0204] If the diagnosis result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve, the water supply pipeline valve is replaced or optimized.

[0205] In some embodiments, the judgment threshold determination module 42 is used to

[0206] The cumulative sum of the average value of the heating status data corresponding to the threshold intervals of each influencing factor and the standard deviation is used as the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor.

[0207] In this exemplary embodiment, the electronic device includes a distributed heating state control system, which may be composed of a data acquisition module, a data processing module, a diagnostic knowledge base module, a diagnostic module, a result presentation module, and the like.

[0208] The data acquisition module is responsible for acquiring data and obtaining corresponding data from the local control system or database, such as water supply temperature, return water temperature, user indoor temperature and other diagnostic rule required data.

[0209] The data processing module is responsible for processing the acquired data, including eliminating non-operating data, processing abnormal data, calculating data, and storing the original data and processed data.

[0210] The diagnostic knowledge base module is responsible for configuring and storing energy consumption diagnostic rules for distributed heating.

[0211] The diagnosis module is used to utilize the module of the diagnosis knowledge base to call the energy-saving diagnosis rules stored in the diagnosis knowledge base module, diagnose the processed data stored in the data processing and storage module, and output and save the diagnosis conclusion.

[0212] The result presentation module is used to query and display the problem description and optimization suggestions of energy-saving diagnosis.

[0213] According to the preset diagnostic rules, the real-time collected data required for energy-saving diagnosis is obtained, including heating supply, water supply temperature, water supply temperature set value, return water temperature, and indoor temperature. The data is instantaneous data with a granularity of minutes or seconds. Data is obtained through PLC, DCS distributed control system, SCADA, metering instruments, indoor temperature acquisition platform, etc., and then transmitted through DTU and gateway, and stored in the database. Among them, the SCADA system is a computer-based DCS (distributed control system) and power automation monitoring system; the DTU data transmission unit is a device specifically used to transmit data from remote field equipment to the central control room or host computer system by wireless or wired means.

[0214] Among them, data processing is divided into three parts: elimination of non-heating period data, abnormal data processing, and data processing.

[0215] ① Data from non-heating period are eliminated:

[0216] To analyze the data of heating time and determine the generation time of the data, it is necessary to exclude the data of non-heating time based on the start time and end time of the heating period.

[0217] ②Abnormal data processing:

[0218] In order to avoid the influence of abnormal data on the diagnosis results, the abnormal data needs to be eliminated. The processing rules are as follows: ① Eliminate null value data; ② Eliminate over-limit data. When the data of the measuring point exceeds the normal range, the data is directly eliminated. The normal range of water supply temperature is 0-100℃, the normal range of return water temperature is: 0-100℃; the normal range of indoor temperature is 0-50℃.

[0219] ③Data processing:

[0220] In order to reduce the amount of data to be analyzed, improve diagnostic efficiency, and reduce the impact of data fluctuations on diagnostic results caused by changes in working conditions, real-time data at the minute or second level (average of 3,600 data) is processed into data at the hourly granularity (average at the minute level is the hourly granularity). The processing rule is to directly average the supply water temperature, return water temperature, and indoor temperature during the heating period.

[0221] In this application, according to the diagnostic rules, the calculation of data is completed, such as the calorific value mark, the deviation of the water supply temperature from the set value, etc.

[0222] The distributed heating energy consumption diagnosis method and tool system consists of a data acquisition module, a data processing module, a diagnosis knowledge base module, a diagnosis module, a result presentation module, etc.

[0223] Energy consumption diagnosis rules and problem diagnosis rules for distributed heating are configured in the diagnostic knowledge base. The problem diagnosis rules are composed of diagnosis rule classification, rule attribution, diagnosis logic, problem description, optimization suggestions, and data requirements.

[0224] According to the preset diagnosis rules, the real-time data collected for energy-saving diagnosis is obtained, including water supply temperature, water supply temperature set value, return water temperature, and indoor temperature. The data is instantaneous data with a granularity of minutes or seconds.

[0225] Data is acquired through PLC, DCS, SCADA, metering instruments, indoor temperature collection platform, etc., then transmitted through DTU and gateway and stored in the database.

[0226] Data processing is divided into three parts: elimination of non-heating period data, abnormal data processing, and data calculation.

[0227] According to the diagnosis knowledge base configuration rules, the required data is obtained for diagnosis. When the data triggers the diagnosis rules, the problem description and optimization suggestions are output.

[0228] Through the energy-saving diagnosis system, the diagnosis results are presented on the PC or APP. The historical diagnosis results can be queried. The diagnosis results and optimization suggestions can be presented in a variety of ways such as labels and text descriptions. The diagnosed problem descriptions and optimization suggestions correspond one to one.

[0229] The present disclosure provides a computer-readable storage medium on which a heating state control program of a distributed heating system is stored. When the heating state control program of the distributed heating system is executed by a processor, the heating state control method of the distributed heating system described in the above embodiments is implemented.

[0230] The present disclosure provides an electronic device, including a memory, a processor, and a heating state control program of a distributed heating system stored in the memory and executable on the processor. When the processor executes the heating state control program of the distributed heating system, the heating state control method of the distributed heating system described in the above-mentioned embodiments is implemented.

[0231] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0232] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0233] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0234] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the referred device or element 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 disclosure.

[0235] In addition, the terms "first", "second", etc. used in the embodiments of the present disclosure are only used for descriptive purposes and should not be understood as indicating or implying relative importance, or implicitly indicating the number of technical features indicated in the embodiments. Therefore, the features defined by the terms "first", "second", etc. in the embodiments of the present disclosure may explicitly or implicitly indicate that at least one of the features is included in the embodiment. In the description of the present disclosure, the word "multiple" means at least two or two or more, such as two, three, four, etc., unless otherwise clearly and specifically defined in the embodiments.

[0236] In the present disclosure, unless otherwise clearly specified or limited in the embodiments, the terms "installed", "connected", "connected" and "fixed" etc. appearing in the embodiments should be understood in a broad sense. For example, the connection can be a fixed connection, a detachable connection, or an integrated connection. It can be understood that it can also be a mechanical connection, an electrical connection, etc.; of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two elements, or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to the specific implementation situation.

[0237] In the present disclosure, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0238] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A method for controlling the heating state of a distributed heating system, characterized in that: include: Obtaining heating status data of the distributed heating system under normal heating status and data of factors affecting the heating status of the heating system; Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators, and the heating state data of the distributed heating system under the normal heating state is clustered to obtain the heating state data corresponding to the threshold intervals of different influencing factors; Based on the heating state data corresponding to the different influencing factor threshold intervals, determining the heating state judgment thresholds of the distributed heating system corresponding to the different influencing factor threshold intervals; Based on the heating state judgment threshold of the distributed heating system under the normal heating state, the heating state data of the distributed heating system collected in real time is analyzed and diagnosed to obtain the diagnosis result of the real-time heating state of the distributed heating system; Based on the diagnosis result of the real-time heating status of the distributed heating system, the heating status of the distributed heating system is regulated.

2. The method for controlling the heating state of a distributed heating system according to claim 1, characterized in that: The heating status data at least includes thermal index data, water supply temperature, water supply temperature setting value, average indoor temperature of users and average indoor temperature of the project; the influencing factors at least include indoor temperature affecting the thermal index of the heating system, water supply flow affecting the deviation between the water supply temperature of the heating system and the water supply temperature setting value, and indoor temperature affecting the deviation between the average indoor temperature of users of the heating system and the average indoor temperature of the project; Based on the clustering model, the influencing factors affecting the heating state of the heating system are used as clustering indicators to cluster the heating state data of the distributed heating system under the normal heating state, and obtain the heating state data corresponding to different threshold intervals of the influencing factors, including: Based on the clustering model, taking the outdoor temperature that affects the thermal index of the heating system as the clustering index, the thermal index data of the distributed heating system under the normal heating state is clustered to obtain the thermal index data corresponding to different outdoor temperature threshold intervals; Based on the clustering model, taking the outdoor temperature that affects the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project as the clustering index, clustering the deviation between the average indoor temperature of the heating system users and the average indoor temperature of the project, and obtaining the deviation data between the average indoor temperature of the heating system users and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals; and Based on the clustering model, the water supply flow that affects the deviation between the water supply temperature and the set value of the water supply temperature of the heating system is taken as the clustering index. The deviation between the water supply temperature and the set value of the water supply temperature of the heating system is clustered to obtain the deviation data between the water supply temperature and the set value of the water supply temperature of the heating system corresponding to different water supply flow threshold intervals.

3. The method for controlling the heating state of a distributed heating system according to claim 2, characterized in that: The determining, based on the heating state data corresponding to the different influencing factor threshold intervals, the heating state judgment thresholds of the distributed heating system corresponding to the different influencing factor threshold intervals comprises: For the heating status data corresponding to the different influencing factor threshold intervals, respectively determine the average value and standard deviation of the heating status data corresponding to each influencing factor threshold interval; Based on the average value and standard deviation of the heating status data corresponding to the threshold intervals of each influencing factor, the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor is determined.

4. The method for controlling the heating state of a distributed heating system according to claim 3, characterized in that: The determining of the heating state judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval based on the average value and standard deviation of the heating state data corresponding to each influencing factor threshold interval includes: Based on the average value and standard deviation of the thermal index data corresponding to different outdoor temperature threshold intervals, determining the thermal index state judgment threshold corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals; Based on the average value and standard deviation of the deviation data between the average indoor temperature of users of the heating system and the average indoor temperature of the project corresponding to different outdoor temperature threshold intervals, determine the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the distributed heating system corresponding to different outdoor temperature threshold intervals; Based on the average value and standard deviation of the deviation data between the water supply temperature and the water supply temperature setting value of the heating system corresponding to different water supply flow threshold intervals, the deviation state judgment threshold between the water supply temperature and the water supply temperature setting value of the heating system corresponding to the distributed heating system corresponding to different water supply flow threshold intervals is determined.

5. The method for controlling the heating state of a distributed heating system according to claim 4, characterized in that: The heating state judgment threshold under the normal heating state of the distributed heating system is used to analyze and diagnose the heating state data of the distributed heating system collected in real time, and obtain the diagnosis result of the real-time heating state of the distributed heating system, including: If the total excess rate of the thermal indexes corresponding to the distributed heating systems corresponding to different outdoor temperature threshold intervals exceeding the thermal index state judgment thresholds corresponding to the respective outdoor temperature threshold intervals is greater than a first percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is that the indoor temperature heating excess rate is high; If the total exceeding rate of the deviation between the average indoor temperature of users of the heating system corresponding to different outdoor temperature threshold intervals and the average indoor temperature of the project exceeds the state judgment threshold of the deviation between the average indoor temperature of users and the average indoor temperature of the project corresponding to the respective outdoor temperature threshold intervals is greater than the second percentage, it is determined that the diagnosis result of the real-time heating state of the distributed heating system is a poor hydraulic balance; If the total excess rate of the deviation between the heating system water supply temperature and the water supply temperature setting value corresponding to different water supply flow threshold intervals exceeds the state judgment threshold of the heating system water supply temperature and the water supply temperature setting value corresponding to each water supply flow threshold interval is greater than the third percentage, then the diagnostic result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve.

6. The method for controlling the heating state of a distributed heating system according to claim 5, characterized in that: The heat supply state regulation of the distributed heat supply system based on the diagnosis result of the real-time heat supply state of the distributed heat supply system comprises: If the diagnosis result of the real-time heating status of the distributed heating system is that the indoor temperature heating excess rate is high, then adjusting the water supply temperature setting value of the distributed heating system according to the outdoor temperature; If it is determined that the diagnosis result of the real-time heating status of the distributed heating system is poor hydraulic balance, the frequency of the electric frequency water pump is adjusted to adjust the input power of the electric frequency water pump; If the diagnosis result of the real-time heating status of the distributed heating system is determined to be poor adjustment performance of the water supply pipeline valve, the water supply pipeline valve is replaced or optimized.

7. The method for controlling the heating state of a distributed heating system according to claim 3, characterized in that: The determining of the heating state judgment threshold corresponding to the distributed heating system corresponding to each influencing factor threshold interval based on the average value and standard deviation of the heating state data corresponding to each influencing factor threshold interval includes: The cumulative sum of the average value of the heating status data corresponding to the threshold intervals of each influencing factor and the standard deviation is used as the heating status judgment threshold corresponding to the distributed heating system corresponding to the threshold intervals of each influencing factor.

8. A heating state control device for a distributed heating system, characterized in that: include: A data acquisition module is used to acquire the heating status data of the distributed heating system under normal heating status and the data of influencing factors affecting the heating status of the heating system; A sample clustering module is used to cluster the heating status data of the distributed heating system under normal heating status based on the clustering model and taking the influencing factors affecting the heating status of the heating system as clustering indicators to obtain heating status data corresponding to different threshold intervals of influencing factors; A judgment threshold determination module, used to determine the heating state judgment threshold of the distributed heating system corresponding to different influencing factor threshold intervals based on the heating state data corresponding to the different influencing factor threshold intervals; A heating status diagnosis module is used to analyze and diagnose the heating status data of the distributed heating system collected in real time based on the heating status judgment threshold of the distributed heating system under normal heating status, so as to obtain a diagnosis result of the real-time heating status of the distributed heating system; The heating status control module is used to control the heating status of the distributed heating system based on the diagnosis result of the real-time heating status of the distributed heating system.

9. A computer-readable storage medium, characterized in that: A heating state control program of a distributed heating system is stored thereon, and when the heating state control program of the distributed heating system is executed by a processor, a heating state control method of a distributed heating system according to any one of claims 1-7 is implemented.

10. An electronic device, characterized in that: The invention comprises a memory, a processor and a heating state control program of a distributed heating system which is stored in the memory and can be run on the processor. When the processor executes the heating state control program of the distributed heating system, the heating state control method of the distributed heating system described in any one of claims 1 to 7 is implemented.

Images