A monitoring and precision heating regulation method and system based on comfort room temperature

Abstract

The application discloses a kind of based on comfort room temperature's monitoring and precision heating control method and system, comprising: collecting user room temperature data, dividing the room temperature data of user, and carrying out data preprocessing;According to the room temperature data obtained, the room temperature imbalance degree index of different heat supply area of heat station is calculated, threshold is judged and abnormal room temperature area is obtained;For abnormal room temperature area, the precision heating control of correction-prediction method is adopted;For the abnormal room temperature area after regulation, the area room temperature imbalance degree index is recalculated;The regulation effect of abnormal room temperature area after regulation is graded;The standard rate value of the area comfort room temperature after regulation is counted.The application uses the above-mentioned one based on comfort room temperature's monitoring and precision heating control method and system, realizes the monitoring and correction-prediction precision heating control based on comfort room temperature index, provides new ideas for on-demand precision heating of heating system, and improves the heating quality of heating system.

Description

Technical Field

[0001] This invention relates to the field of heating network control technology, and in particular to a method and system for monitoring and precisely regulating heating based on comfortable room temperature. Background Technology

[0002] Traditional heating station control methods rarely consider room temperature feedback correction, often resulting in inaccurate control due to high reliance on manual experience, energy waste due to coarse control granularity, and an inability to dynamically adjust to external changes. In recent years, the concept of precision heating has brought significant challenges to heating systems, requiring enhanced control of user room temperature through digitalization and intelligent methods. This involves using room temperature feedback as a control parameter to improve heating quality, reduce user complaints, and achieve precise heating control.

[0003] Currently, there is no complete control scheme for the comfort room temperature of heating systems. Often, employees increase heating output to reduce user complaints, ultimately resulting in energy waste. Therefore, this paper proposes a method and system for monitoring and precisely controlling heating based on comfort room temperature. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for monitoring and precise heating regulation based on comfort room temperature. By collecting room temperature data of heating users in different heating stations and combining it with monitoring relevant indicators of regional comfort room temperature, the invention corrects and predicts the regulation of substandard heating areas, dynamically adjusts the control parameters of the heating stations, and realizes precise heating regulation based on monitoring and correction-prediction of comfort room temperature indicators. This provides a new approach for precise on-demand heating in heating systems and improves the heating quality of heating systems.

[0005] To achieve the above objectives, this invention provides a method for monitoring and precisely controlling heating based on comfortable room temperature. This method is applied to a system for monitoring and precisely controlling heating based on comfortable room temperature and includes the following steps:

[0006] S1. Collect user room temperature data, divide user room temperature data according to the different heating areas of different heating stations, and perform data preprocessing;

[0007] S2. Based on the acquired room temperature data, calculate the room temperature imbalance index for different heating stations, determine the threshold, and identify abnormal room temperature areas.

[0008] S3. For areas with abnormal room temperature, adopt precise heating regulation using a correction-prediction method;

[0009] S4. For the abnormal room temperature areas after regulation, recalculate the regional room temperature unevenness index.

[0010] S5. Classify the control effect of abnormal room temperature areas after regulation into different levels;

[0011] S6, the regional comfort room temperature compliance rate after statistical regulation.

[0012] Preferably, in step S1, the method for collecting user room temperature data, segmenting the user room temperature data, and performing data preprocessing is as follows:

[0013] S11. Based on the user's room temperature measurement device, collect the user's room temperature data and record the room temperature of user i in area j at time t as T. i,j,t ;

[0014] S12. Based on the different heating areas of different heating stations, the room temperature data of users are divided. The room temperature of all heating users within the heating area j of different heating stations at time t is recorded in data group M. 1,t M 2,t M 3,t ... M j,t ;

[0015] S13. Perform data preprocessing based on the room temperature data received from the data acquisition module; wherein, duplicate values ​​in the acquired room temperature data are directly deleted, and missing values ​​in the acquired room temperature data are filled with the mean.

[0016] Preferably, in step S2, the specific process of calculating the room temperature imbalance index of different heating station heating areas based on the acquired room temperature data, determining the threshold, and obtaining abnormal room temperature areas is as follows:

[0017] S21. Based on the obtained room temperature data, calculate the room temperature imbalance index F(j) for the heating area j under the jurisdiction of different heating stations:

[0018]

[0019] Where m is the average number of times the user's daily room temperature is collected; N j T represents the total number of heating users in area j; i,j,t The room temperature data for user i in region j at time t; the room temperature unevenness index is referenced to a comfortable room temperature range of 18–24℃;

[0020] S22. Based on the room temperature imbalance index of heating area j of different heating stations in step S21, calculate the threshold f(j) for different heating areas j as follows:

[0021]

[0022] Where, N j The total number of heating users in area j;

[0023] S23. Based on the threshold f(j) in step S22, obtain the threshold range of different heating areas j as [0, f(j)].

[0024] S24. Determine whether the room temperature unevenness of different regions j meets the threshold requirement. Regions that do not meet the requirement are marked as abnormal room temperature regions j'.

[0025] Preferably, the specific process of using a correction-prediction method to precisely regulate heating in step S3 for areas with abnormal room temperature is as follows:

[0026] S31. Establish a regional comfort room temperature control prediction model;

[0027] S32. Establish a regional comfort room temperature control correction model;

[0028] S33. Correction of demand flow value obtained based on correction model and regulation flow value obtained based on prediction model.

[0029] Preferably, in step S31, a regional comfort room temperature regulation prediction model is established, as shown below:

[0030] S311. Obtain heating operation parameters from the operating database and calculate the average value;

[0031] S312. Based on the data obtained in step S311, establish a mapping model between valve opening degree and heating operation parameters, as shown below:

[0032]

[0033] Where, ξ j 'These are the control operating parameters of the heating system that affect the opening degree of the primary side valves;'

[0034] S313. Obtain the mean room temperature T of the abnormal room temperature region j'. 区域均,j' As shown below:

[0035]

[0036] Where, N j' To obtain the number of heating users in the abnormal room temperature zone j'; ∑T i,j',t To obtain the total room temperature data of heating users in heating area j' with abnormal room temperature; m is the number of times the user's daily room temperature is collected;

[0037] S314. Establish a mapping model between the regional mean room temperature and parameters, as shown below:

[0038]

[0039] Where, ω j'The value of the abnormal room temperature zone j' is a factor that affects the area of ​​the abnormal room temperature zone j', the building structure, and the proportion of heating users.

[0040] In step S32, a regional comfort room temperature regulation correction model is established, as shown below:

[0041] S321. Calculate the average heating load based on the user load data of the abnormal room temperature area j'. As shown below:

[0042]

[0043] Where m is the number of times the user's daily room temperature is collected; ∑Q i,j',t N represents the total heating load of region j at time t. j' The number of heating users in area j';

[0044] S322. Based on the acquired data, establish a mapping model for the heating load, as shown below:

[0045]

[0046] Preferably, in step S33, the regulation flow value obtained based on the prediction model is corrected based on the demand flow value obtained by the correction model, as shown below:

[0047] S331. Based on the regional comfort room temperature control prediction model and the expected regional average room temperature, obtain the valve opening parameter α for the next d days. d,j' ; where d is selected from 1 to 7 days;

[0048] S332. The relationship between valve opening and flow rate is shown below:

[0049]

[0050] in, Relative flow rate is the ratio of the flow rate at a certain opening degree of the control valve to the flow rate at its full opening. Relative opening: The ratio of a certain opening stroke to the full opening stroke of a control valve;

[0051] S333, Obtain the controlled flow rate G for the abnormal room temperature region j' d,j' ;

[0052] S334. Based on the valve opening parameter model, obtain the valve opening parameter α for different valve opening parameters. d,j' The corresponding T 一次回,d,j' ;

[0053] S335. Based on the regional comfort room temperature control correction model, obtain the demand load value Q of the abnormal room temperature region j'. d,j'The relationship between demand flow and demand load is calculated as follows:

[0054]

[0055] in, The average primary water supply temperature for the abnormal room temperature zone j'; T 一次回,d,j' Q represents the primary return water temperature corresponding to different valve opening parameters in the abnormal room temperature zone j'; d,j' For the abnormal room temperature region j', the demand load value is obtained based on the regional comfort room temperature regulation correction model; G' d,j' The required flow rate value for the abnormal room temperature region j';

[0056] S336. Obtain the flow rate value G' of the regional comfort room temperature requirement. d,j 'Calculate the flow deviation ΔG between the demand flow value and the control flow value.' d,j' As shown below:

[0057] ΔG d,j' =|G' d,j -G d,j |

[0058] S337, Based on flow deviation ΔG d,j 'Calculate the mean flow deviation' As shown below:

[0059]

[0060] S338, Based on the average flow deviation The flow deviation range is calculated as follows:

[0061]

[0062] S339, Determine the flow deviation ΔG d,j' Whether it is within the deviation range, make corresponding adjustments based on the results.

[0063] Preferably, the method for recalculating the regional room temperature imbalance index for the regulated abnormal room temperature area in step S4 is as follows:

[0064] S41. After the adjustment, the room temperature of user i in region j at time t is T'. j,i,t ;

[0065] S42. The room temperature data of users in different areas are collected again. The room temperature of all heating users within the heating area j of the same heating station at time t is re-recorded into data group M'. j,t ;

[0066] S43. Recalculate the regional room temperature imbalance F(j') of the abnormal room temperature region j' after regulation, as shown below:

[0067]

[0068] Where m represents the number of times the user's daily room temperature is collected; N j T represents the total number of heating users in area j; i,j',t is the room temperature data of user i at time t after the abnormal room temperature region j' is regulated; F(j') is the room temperature imbalance index after the regulation of region j'.

[0069] Preferably, the method for classifying the control effect of the abnormal room temperature region after control in step S5 is as follows:

[0070] S51. Record the room temperature imbalance of the abnormal room temperature region j' after regulation. If it meets the threshold range [0, f(j') + 0.2f(j')], it is grade A, which is better.

[0071] S52. Record the room temperature imbalance of the abnormal room temperature region j' after regulation. If it meets the threshold range [f(j')+0.2f(j'),f(j')+0.4f(j')], it is classified as Grade B (general).

[0072] S53. Record the room temperature unevenness of the abnormal room temperature area j' after regulation. If it does not meet the above threshold range, it is grade C unqualified.

[0073] Preferably, the method for calculating the regional comfort room temperature compliance rate after step S6 is as follows:

[0074] S61. The total number of qualified abnormal room temperature areas is N. 合格 :

[0075] N 合格 =N A +N B

[0076] S62. The total number of non-compliant abnormal room temperature areas is N. 不合格 :

[0077] N 不合格 =N C

[0078] S63, the comfort room temperature compliance rate is:

[0079]

[0080] Where N is the total number of abnormal room temperature regions; N 合格 This represents the total number of acceptable room temperatures in abnormal areas after regulation.

[0081] A system for monitoring and precisely controlling heating based on comfortable room temperature includes a data acquisition module, a comfortable room temperature monitoring module, an abnormal room temperature area acquisition module, an abnormal room temperature area control module, and an abnormal room temperature area assessment module.

[0082] The data acquisition module collects room temperature data from users based on the different heating areas of different heating stations.

[0083] The comfort room temperature monitoring module includes an abnormal room temperature area acquisition module, an abnormal room temperature area control module, and an abnormal room temperature area assessment module.

[0084] The abnormal room temperature area acquisition module calculates the room temperature imbalance index of different heating station heating areas based on the acquired room temperature data, determines the threshold, and acquires abnormal room temperature areas.

[0085] The abnormal room temperature zone control module implements precise heating control based on correction and prediction for abnormal room temperature zones.

[0086] The abnormal room temperature area assessment module recalculates the regional room temperature imbalance index for abnormal room temperature areas after regulation, classifies the regulation effect of abnormal room temperature areas after regulation into levels, and finally calculates the regional comfortable room temperature compliance rate after regulation.

[0087] Therefore, the present invention adopts the above-mentioned method and system for monitoring and precise heating regulation based on comfort room temperature. By collecting room temperature data of heating users in different heating stations and combining it with the monitoring of relevant indicators of regional comfort room temperature, the invention corrects and predicts the regulation of substandard heating areas and dynamically adjusts the control parameters of the heating stations. This achieves precise heating regulation based on monitoring and correction-prediction of comfort room temperature indicators, providing a new approach for on-demand precise heating in heating systems and improving the heating quality of heating systems.

[0088] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0089] Figure 1 This is a flowchart of a precise heating control method based on comfortable room temperature according to the present invention;

[0090] Figure 2 This is a schematic diagram of the principle of a precision heating control system based on comfortable room temperature according to the present invention.

[0091] Figure 3 This is a schematic diagram of the principle of a precision heating control system based on comfortable room temperature according to the present invention. Detailed Implementation

[0092] To make the objectives, technical solutions, and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the present invention and are not intended to limit the embodiments of the present invention.

[0093] like Figure 1 As shown, this invention provides a method for monitoring and precisely controlling heating based on comfortable room temperature, specifically including the following steps:

[0094] S1. Collect user room temperature data, divide user room temperature data according to the different heating areas of different heating stations, and perform data preprocessing.

[0095] S2. Calculate the room temperature imbalance index of the heating area under the jurisdiction of different heating stations based on the obtained room temperature data, determine the threshold and obtain the abnormal room temperature area.

[0096] S3. Implement precise heating regulation based on correction and prediction for areas with abnormal room temperature.

[0097] S4. Calculate the regional room temperature imbalance index again for the abnormal room temperature areas after regulation.

[0098] S5. Classify the control effect of abnormal room temperature areas after regulation into different levels;

[0099] S6, the regional comfort room temperature compliance rate after statistical regulation.

[0100] like Figure 2 As shown, the present invention also provides a system for monitoring and precise heating control based on comfortable room temperature, specifically including a data acquisition module and a comfortable room temperature monitoring module; wherein, the comfortable room temperature monitoring module includes an abnormal room temperature area acquisition module, an abnormal room temperature area control module, and an abnormal room temperature area assessment module.

[0101] The data acquisition module includes: an indoor temperature measurement device and a temperature sensor; this module transmits the collected data to the abnormal room temperature monitoring module, which classifies the user's room temperature data according to the different heating areas of different heating stations;

[0102] The abnormal room temperature monitoring module is suitable for smart heating systems to determine whether to implement precise heating regulation based on comfort room temperature indicators;

[0103] The abnormal room temperature area acquisition module has functions such as preprocessing room temperature data, calculating room temperature imbalance index, and acquiring abnormal room temperature areas. The results are transmitted to the abnormal room temperature area control module. Based on the acquired room temperature data, the module calculates the room temperature imbalance index of different heating station heating areas, determines the threshold, and acquires abnormal room temperature areas.

[0104] The abnormal room temperature zone control module has functions such as zone comfort room temperature control correction and zone comfort room temperature control prediction, and adopts precise heating control through correction and prediction for abnormal room temperature zones.

[0105] The abnormal room temperature area assessment module recalculates the regional room temperature imbalance index for abnormal room temperature areas after regulation, obtains and detects the effect of regulation on abnormal room temperature areas, classifies abnormal room temperature areas after regulation into levels, and finally calculates the regional comfort room temperature compliance rate value after regulation.

[0106] Example

[0107] like Figure 3 As shown below, the working principle of a precision heating control system based on comfortable room temperature is as follows:

[0108] S1. Based on the data acquisition module, collect user room temperature data, divide the user room temperature data according to the different heating areas of different heating stations, and perform data preprocessing.

[0109] S11. Based on the user's room temperature measurement device, the indoor temperature is transmitted to the data acquisition module using a temperature sensor, the user's room temperature data is collected, and the room temperature of user i in area j at time t is recorded as T. 1,j,t T 2,j,t T 3,j,t ...T i,j,t .

[0110] S12. Based on the different heating areas of different heating stations, the room temperature data of users is divided. The room temperature of all heating users within the heating area j of different heating stations at time t is recorded in data group M. 1,t M 2,t M 3,t ... M j,t ;

[0111] Among them, M 1,t ={T 1,1,t T 2,1,t T 3,1,t ...T i,1,t}、M 2,t ={T 1,2,t T 2,2,t T 3,2,t ...T i,,2,t}、M 3,t ={T 1,3,t T 2,3,t T 3,3,t ...T i,3,t}、……M j,t ={T 1,j,t T 2,j,t T 3,j,t...T i,j,t}

[0112] S13. The abnormal room temperature area acquisition module preprocesses the room temperature data received from the data acquisition module, and directly deletes duplicate values ​​in the acquired room temperature data; it fills in missing values ​​in the acquired room temperature data using the mean value.

[0113] The imputation values ​​for the missing room temperature data are:

[0114]

[0115] in, For missing room temperature data; ∑ Ti,j,t The sum of all room temperature data collected daily from user i in region j at time t, without any missing data; n t This represents the total number of times daily user room temperature data was collected without any missing data.

[0116] S2. Based on the obtained room temperature data, calculate the room temperature imbalance index of the heating areas under the jurisdiction of different heating stations, determine the threshold, and obtain the abnormal room temperature areas.

[0117] S21. Based on the collected room temperature data of heating users, calculate the room temperature imbalance index F(j) for heating areas j of different heating stations, as shown below:

[0118]

[0119] Where m represents the number of times the user's daily room temperature data is collected; N j T represents the total number of heating users in area j; i,j,t The room temperature data for user i in region j at time t; the room temperature unevenness index is referenced to a comfortable room temperature range of 18–24℃;

[0120] S22. Based on the room temperature imbalance index of heating area j in different heating stations, calculate the threshold f(j) for different heating areas j, as shown below:

[0121]

[0122] Where, N j The total number of heating users in area j;

[0123] S23. The threshold range of different heating areas j obtained according to the threshold f(j) is [0, f(j)].

[0124] S24. Based on the different threshold ranges of different heating areas j, determine whether the room temperature unevenness of different areas meets the requirements; among them, areas where the room temperature unevenness index does not meet the threshold range are marked as abnormal room temperature areas j'; the total number of abnormal room temperature areas is N, as shown below:

[0125] N = ∑ j '

[0126] S3. Based on the comfort room temperature detection module, precise heating regulation is implemented for areas with abnormal room temperature through correction and prediction.

[0127] Based on the abnormal room temperature area acquisition module, the heating operation parameters of the abnormal room temperature area are obtained from the operation database and the temperature parameters of the abnormal room temperature area are obtained from the temperature database, and relevant data preprocessing is performed.

[0128] Based on the heating operation parameters corresponding to the operating database, including: valve opening α j',t Primary side return water temperature T 一次回,j',t Secondary water supply temperature T 二次供,j',t Secondary side return water temperature T 二次回,j',t Pump frequency f j',t User heating load Q i,j',t .

[0129] The mean value was calculated based on the acquired data, including the mean valve opening in the abnormal room temperature region j'. for:

[0130]

[0131] Average primary return water temperature in abnormal room temperature zone j' for:

[0132]

[0133] Average secondary water supply temperature in abnormal room temperature zone j' for:

[0134]

[0135] Average secondary return water temperature in abnormal room temperature zone j' for:

[0136]

[0137] Average pump frequency in abnormal room temperature zone j' for:

[0138]

[0139] Average heating load of users in abnormal room temperature zone j' for:

[0140]

[0141] Where m is the number of times the user's daily room temperature is collected; ∑Q i,j',t N represents the total heating load of region j at time t. j The number of heating users in area j';

[0142] Based on the temperature parameters corresponding to the temperature database, including: the outdoor temperature T of the abnormal room temperature area j' corresponding to the room temperature collection time t. out,j',t The outdoor temperature T' of the abnormal room temperature area j' in the next d days out,j',d .

[0143] The average value was calculated based on the acquired data, including the average outdoor temperature of the abnormal room temperature area j'. for:

[0144]

[0145] Where m represents the number of times the user's daily room temperature data is collected; N j The number of heating users in area j';

[0146] S31. Based on the abnormal room temperature area control module, establish a regional comfort room temperature control prediction model; wherein, the regional comfort room temperature control prediction model includes: an abnormal room temperature area valve opening model and an abnormal room temperature area mean model.

[0147] S311. Based on the above operating database, obtain the heating operation parameters and calculate the valve opening α in the abnormal room temperature zone j'. j',t Primary side return water temperature T 一次回,j',t Secondary water supply temperature T 二次供,j',t Secondary side return water temperature T 二次回,j',t Pump frequency f j',t ;

[0148] S312. Based on the data obtained in step S311, establish a mapping model between valve opening degree and heating operation parameters, as shown below:

[0149]

[0150] Where, ξ j' Fuzzy control parameters for the valve opening degree of the heating system in the abnormal room temperature region j';

[0151] S313. Based on the established regional valve opening model, establish a regional mean model to obtain the regional mean room temperature T of the abnormal room temperature region j'. 区域均,j'As shown below:

[0152]

[0153] Where, N j' To obtain the number of heating users in the abnormal room temperature zone j'; ∑T i,j',t To obtain the total room temperature data of heating users in heating area j' with abnormal room temperature; m is the number of times the user's daily room temperature is collected;

[0154] S314, Based on obtaining the average room temperature T of the abnormal room temperature area 区域均,j' Establish a mapping model between the regional mean room temperature and parameters:

[0155]

[0156] Where, ω j' The value of the abnormal room temperature zone j' is a factor affecting the area of ​​the abnormal room temperature zone j', and the building structure and the proportion of heating users in the abnormal room temperature zone j' are different.

[0157] S32. Establish a regional comfort room temperature control correction model.

[0158] S321. Based on the above operating database, obtain the heating operation parameters and calculate the average heating load of users in the abnormal room temperature zone j'.

[0159] S322. Based on the acquired data, establish a mapping model for the heating load, as shown below:

[0160]

[0161] in, The average outdoor temperature of the abnormal room temperature area j'; T 区域均,j' The mean room temperature of region j', which represents the abnormal room temperature region. The average heating load for users in the abnormal room temperature zone j'.

[0162] S33. Correction of demand flow value obtained based on correction model and regulation flow value obtained based on prediction model.

[0163] S331. Based on the regional comfort room temperature control prediction model and the expected regional average room temperature, obtain the valve opening parameter α for the next d days. 1,j' α 2,j' α 3,j' ..., α d,j' ;

[0164] Among them, d is generally selected as 1 to 7 days;

[0165] S332. The relationship between valve opening and flow rate is shown below:

[0166]

[0167] in, Relative flow rate is the ratio of the flow rate at a certain opening degree of the control valve to the flow rate at its full opening. Relative opening: The ratio of a certain opening stroke to the full opening stroke of a control valve;

[0168] S333, Based on valve opening parameter α 1,j' α 2,j' α 3,j' ..., α d,j' Obtain the controlled flow rate G in the abnormal room temperature region j' 1,j' G 2,j' G 3,j' ...G d,j' ;

[0169] S334. Based on the valve opening parameter model, obtain the valve opening parameter α for different valve opening parameters. d,j' The corresponding T 一次回,d,j' ;

[0170] S335. Based on the regional comfort room temperature control correction model, obtain the demand load value Q of the abnormal room temperature region j'. 1,j' Q 2,j' Q 3,j' Q d,j' The relationship between demand flow and demand load is shown below:

[0171]

[0172] in, The average primary water supply temperature for the abnormal room temperature zone j'; T 一次回,d,j' Q represents the primary return water temperature corresponding to different valve opening parameters in the abnormal room temperature zone j'; d,j' For the abnormal room temperature region j', the demand load value is obtained based on the regional comfort room temperature regulation correction model; G' d,j' The required flow rate value for the abnormal room temperature region j';

[0173] S336. Obtain the flow rate value G' of the regional comfort room temperature requirement. 1,j' G' 2,j' G' 3,j' ...G' d,j' The flow deviation ΔG between the demand flow value and the control flow value d,j' As shown below:

[0174] ΔG d,j' =|G' d,j -Gd,j |

[0175] S337, Based on flow deviation ΔG d,j' Calculate the mean flow deviation for:

[0176]

[0177] S338, Based on the average flow deviation The calculated flow deviation range is:

[0178]

[0179] S339. Determine the flow deviation ΔG d,j' If the flow rate deviation is within the acceptable range, adjust the valve opening directly; otherwise, adjust the valve opening until the flow rate deviation is within the acceptable range, obtain the final valve opening parameters, and update the regional comfort room temperature control prediction model.

[0180] S4. Based on the abnormal room temperature area assessment module, the regional room temperature imbalance index is recalculated for the abnormal room temperature area after regulation.

[0181] S41. After the adjustment, the room temperature of user i in region j' at time t is collected again, and is T' 1,j',t 、T' 2,j',t 、T' 3,j',t ...T' i,j',t ;

[0182] S42. The room temperature data of users in different areas are further divided. The room temperature of all heating users within the heating area j of the same heating station at time t is re-recorded into data group M'. j,t ; among which, M' j’,t ={T' 1,j’,t 、T' 2,j’,t 、T' 3,j’,t ...T' i,j’,t};

[0183] S43. Perform data preprocessing on the acquired data again, wherein the data preprocessing method is the same as the aforementioned preprocessing method;

[0184] S44. Based on the collected room temperature data of heating users after adjustment, recalculate the room temperature imbalance index F(j') for the abnormal room temperature area j':

[0185]

[0186] Where m represents the number of times the user's daily room temperature is collected; N j T represents the total number of heating users in area j; i,j',tis the room temperature data of user i at time t after the abnormal room temperature region j' is regulated; F(j') is the room temperature imbalance index after the regulation of region j'.

[0187] S5. Judge the room temperature unevenness index according to the threshold range, and classify the effect after regulation into levels.

[0188] Based on the temperature imbalance index of abnormal temperature zone j' in different heating stations, the threshold range f(j') of abnormal temperature zone j' is calculated as follows:

[0189]

[0190] Where, N j Let J be the total number of heating users in area j; the threshold range is [0, f(j')]; then, the room temperature unevenness index is judged again based on the threshold range:

[0191] S51. Record the room temperature imbalance of the abnormal room temperature region j' after regulation. If it meets the threshold range [0, f(j') + 0.2f(j')], it is grade A, which is better.

[0192] S52. Record the room temperature imbalance of abnormal room temperature region j' after regulation. If it meets the threshold range [f(j')+0.2f(j'),f(j')+0.4f(j')], then it is classified as Grade B (general).

[0193] S53. If the room temperature imbalance of the abnormal room temperature area j' after regulation does not meet the above threshold range, it is grade C unqualified.

[0194] S6, the rate of compliance of regional comfortable room temperature after statistical regulation.

[0195] Define room temperature series data set N A N B N C After statistical control, the room temperature of abnormal areas is classified into different levels and recorded. Abnormal room temperature areas belonging to levels A and B are defined as meeting the room temperature compliance requirements. Abnormal room temperature areas belonging to level C are defined as not meeting the room temperature compliance requirements.

[0196] S61. Calculate the total number of abnormal room temperature regions belonging to Class A and Class B as N. 合格 As shown below:

[0197] N 合格 =N A +N B

[0198] S62. Calculate the total number of abnormal room temperature regions belonging to level C as N. 不合格 As shown below:

[0199] N 不合格=N C

[0200] S63. Calculate the comfort room temperature compliance rate, as shown below:

[0201]

[0202] Where N is the total number of abnormal room temperature regions; N 合格 This represents the total number of acceptable room temperatures in abnormal areas after regulation.

[0203] Therefore, the present invention adopts the above-mentioned method and system for monitoring and precise heating regulation based on comfort room temperature. By collecting room temperature data of heating users in different heating stations and combining it with the monitoring of relevant indicators of regional comfort room temperature, the invention corrects and predicts the regulation of substandard heating areas and dynamically adjusts the control parameters of the heating stations. This achieves precise heating regulation based on monitoring and correction-prediction of comfort room temperature indicators, providing a new approach for on-demand precise heating in heating systems and improving the heating quality of heating systems.

[0204] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring and precision heating regulation based on comfort room temperature, the method is applied to a monitoring and precision heating regulation system based on comfort room temperature, characterized in that, Includes the following steps: S1. Collect user room temperature data, divide user room temperature data according to the different heating areas of different heating stations, and perform data preprocessing; S2. Based on the acquired room temperature data, calculate the room temperature imbalance index for different heating stations' heating areas, determine the threshold, and identify abnormal room temperature areas. The specific process is as follows: S21、According to the acquired room temperature data, the heat supply area under jurisdiction of different heat stations is calculated j the room temperature imbalance degree index of the heat supply area under jurisdiction of the heat station F(j) is: ； in, m The average number of times the user's daily room temperature is collected; N j for j Total number of district heating users; for j area i user t Real-time room temperature data; Room temperature unevenness index reference comfort room temperature range 18~24℃; S22. Based on the heating areas of different heating stations as described in step S21 j The room temperature unevenness index is used to calculate different heating areas. j threshold for: ； in, N j for j Total number of district heating users; S23, Based on the threshold value in step S22 To obtain information from different heating areas j The threshold range is [0, ]; S24. Determine different regions j Does the room temperature unevenness meet the threshold requirements? Areas that do not meet the requirements are marked as abnormal room temperature areas. j’ ; S3. For areas with abnormal room temperature, adopt precise heating regulation using a correction-prediction method; S4. For the abnormal room temperature areas after regulation, recalculate the regional room temperature unevenness index. S5. Classify the control effect of abnormal room temperature areas after regulation into different levels; S6, the regional comfort room temperature compliance rate after statistical regulation.

2. The method for monitoring and precise heating control based on comfortable room temperature according to claim 1, characterized in that, In step S1, the method for collecting user room temperature data, segmenting the user room temperature data, and performing data preprocessing is as follows: S11. Based on the user's room temperature measurement device, collect and record the user's room temperature data. j area i user t The room temperature at time is T i,j,t ; S12. Based on the different heating areas of different heating stations, divide the room temperature data of users into different categories, and define the heating areas of different heating stations. j All heating users included in the scope t The room temperature at that moment was recorded in the dataset. M 1,t , M 2,t , M 3,t , …… , M j,t ; S13. Perform data preprocessing based on the room temperature data received from the data acquisition module; wherein, duplicate values ​​in the acquired room temperature data are directly deleted, and missing values ​​in the acquired room temperature data are filled with the mean.

3. The method for monitoring and precise heating control based on comfortable room temperature according to claim 1, characterized in that, In step S3, the specific process of using a correction-prediction method to precisely regulate heating for areas with abnormal room temperatures is as follows: S31. Establish a regional comfort room temperature control prediction model; S32. Establish a regional comfort room temperature control correction model; S33. Correction of demand flow value obtained based on correction model and regulation flow value obtained based on prediction model.

4. The method for monitoring and precise heating control based on comfortable room temperature according to claim 3, characterized in that, In step S31, a regional comfort room temperature regulation prediction model is established, as shown below: S311. Obtain heating operation parameters from the operating database and calculate the average value; S312. Based on the data obtained in step S311, establish a mapping model between valve opening degree and heating operation parameters, as shown below: ； in, Abnormal room temperature region j’ The average valve opening; Abnormal room temperature region j’ The average temperature of the primary return water; Abnormal room temperature region j’ The average secondary water supply temperature; Abnormal room temperature region j’ The average temperature of the secondary return water; These are the control operating parameters of the heating system that affect the opening degree of the primary side valves; S313, Obtain abnormal room temperature area j’ Regional average room temperature As shown below: ； in, To obtain abnormal room temperature regions j’ The number of heating users; To obtain heating areas with abnormal room temperature j’ The sum of indoor temperature data for all heating users; m The number of times the user's daily room temperature is collected; S314. Establish a mapping model between the regional mean room temperature and parameters, as shown below: ； in, Abnormal room temperature region j’ The average primary water supply temperature; Abnormal room temperature region j’ The average frequency of the water pumps; Abnormal room temperature region j’ The average outdoor temperature; Abnormal room temperature region j’ Influencing factors, values ​​due to abnormal room temperature regions j’ The size of the area, the structure of the building, and the proportion of heating users vary; In step S32, a regional comfort room temperature regulation correction model is established, as shown below: S321. Regarding the acquired abnormal room temperature area j’ Calculate the average heating load based on user load data. As shown below: ； in, m The number of times the user's daily room temperature is collected; for j’ area t Total heating load at any given time; for j’ Number of district heating users; S322. Based on the acquired data, establish a mapping model for the heating load, as shown below: 。 5. The method for monitoring and precise heating control based on comfortable room temperature according to claim 3, characterized in that, In step S33, the control flow value obtained based on the prediction model is corrected based on the demand flow value obtained by the correction model, as shown below: S331. Based on the regional comfort room temperature regulation prediction model and the expected regional average room temperature, obtain future... d Daily valve opening parameters ;in, d Select 1-7 days; S332. The relationship between valve opening and flow rate is shown below: ； in, Relative flow rate is the ratio of the flow rate at a certain opening degree of the control valve to the flow rate at its full opening degree. Relative opening: The ratio of a certain opening stroke to the full opening stroke of a control valve; S333, Obtain abnormal room temperature area j’ Regulated flow value ; S334. Based on the valve opening parameter model, obtain different valve opening parameters. The corresponding ; S335. Based on the regional comfort room temperature regulation correction model, obtain the abnormal room temperature areas. j’ Demand load value The relationship between demand flow and demand load is calculated as follows: ； in, Abnormal room temperature region j’ Average primary water supply temperature; Abnormal room temperature region j’ Primary return water temperature corresponding to different valve opening parameters; Abnormal room temperature region j’ Demand load values ​​obtained based on a regional comfort room temperature control correction model; Abnormal room temperature region j’ The demand flow value; S336. Obtain the flow rate value of regional comfort room temperature requirement. Calculate the flow deviation between the demand flow value and the control flow value. As shown below: ； S337, Based on Flow Deviation Calculate the mean flow deviation As shown below: ； S338, Based on the average flow deviation The flow deviation range is calculated as follows: ； S339, Determine the flow deviation Whether it is within the deviation range, make corresponding adjustments based on the results.

6. The method for monitoring and precise heating control based on comfortable room temperature according to claim 1, characterized in that, The method for recalculating the regional room temperature imbalance index for the regulated abnormal room temperature area in step S4 is as follows: S41, After re-collection and adjustment j area i user t The room temperature at time 1 was respectively ; S42. Collect room temperature data for users in different areas again, within the same heating station's service area. j All heating users included in the scope t The room temperature at that moment was re-recorded into the dataset. ; S43. Recalculate the abnormal room temperature region after regulation. j’ Regional temperature unevenness As shown below: ； in, m The number of times the user's daily room temperature is collected; N j for j Total number of district heating users; Abnormal room temperature region j’ After regulation i user t Room temperature data at any given time; for j’ Indicators of room temperature unevenness after regional regulation.

7. The method for monitoring and precise heating control based on comfortable room temperature according to claim 1, characterized in that, The method for classifying the control effect of the abnormal room temperature region after control in step S5 is as follows: S51. Record the abnormal room temperature area after regulation. j’ The room temperature unevenness, if it meets the threshold range [0, +0.2 If the result is A, then it is better; S52. Record the abnormal room temperature area after regulation. j’ The room temperature unevenness, if it meets the threshold range [ +0.2 , +0.4 If it is, then it is classified as Grade B (general). S53. Record abnormal room temperature areas after regulation. j’ If the room temperature unevenness does not meet the above threshold range, it is classified as Grade C and is considered unqualified.

8. The method for monitoring and precise heating control based on comfortable room temperature according to claim 1, characterized in that, The method for calculating the regional comfort room temperature compliance rate after step S6 is as follows: S61. The total number of qualified abnormal room temperature areas is: N 合格 : ； S62. The total number of abnormal room temperature areas that do not meet the standards is: N 不合格 : ； S63, the comfort room temperature compliance rate is: ； in, N This represents the total number of areas with abnormal room temperatures. N 合格 This represents the total number of acceptable room temperatures in abnormal areas after regulation.

9. A system for monitoring and precisely controlling heating based on comfortable room temperature, characterized in that: It includes a data acquisition module, a comfortable room temperature monitoring module, an abnormal room temperature area acquisition module, an abnormal room temperature area control module, and an abnormal room temperature area assessment module; The data acquisition module collects room temperature data from users based on the different heating areas of different heating stations. The comfort room temperature monitoring module includes an abnormal room temperature area acquisition module, an abnormal room temperature area control module, and an abnormal room temperature area assessment module. The abnormal room temperature area acquisition module calculates the room temperature imbalance index of different heating station heating areas based on the acquired room temperature data, determines the threshold, and acquires abnormal room temperature areas. Among them, the room temperature unevenness index F(j) The calculation method is as follows: ； in, m The average number of times the user's daily room temperature is collected; N j for j Total number of district heating users; for j area i user t Real-time room temperature data; Room temperature unevenness index reference comfort room temperature range 18~24℃; According to the heating area of ​​different heating stations j The room temperature unevenness index is used to calculate different heating areas. j threshold for: ； in, N j for j Total number of district heating users; According to the threshold The threshold range for obtaining different heating areas j is [0, ]; Determine different regions j Does the room temperature unevenness meet the threshold requirements? Areas that do not meet the requirements are marked as abnormal room temperature areas. j’ ; The abnormal room temperature zone control module implements precise heating control based on correction and prediction for abnormal room temperature zones. The abnormal room temperature area assessment module recalculates the regional room temperature imbalance index for abnormal room temperature areas after regulation, classifies the regulation effect of abnormal room temperature areas after regulation into levels, and finally calculates the regional comfortable room temperature compliance rate after regulation.

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