An Adaptive Variable Frequency Control Method for Circulating Pumps in Heat Exchange Stations of a Courtyard Pipeline Heating System

Abstract

This application discloses an adaptive variable frequency control method for the circulating pump of a heat exchange station in a courtyard pipe network heating system, relating to the field of heat exchange station control technology. Based on achieving balance in the courtyard pipe network, this invention diagnoses abnormal operating data at the building's heat inlet using algorithms, compares and analyzes the operating data of the building's heat inlet to determine the most unfavorable loop in the courtyard pipe network, and adjusts the operating frequency of the circulating pump based on the actual operating data of the most unfavorable loop. Taking the "station-load" system as a whole, by determining the circulating pump frequency control cycle, dynamic and adaptive adjustment of the circulating pump frequency in the heat exchange station is achieved. Compared to traditional fixed frequency or fixed pressure difference control methods for circulating pumps, this method reduces fluctuations in indoor temperature, preventing overheating or overcooling, and by using the most unfavorable loop at the building's heat inlet to provide feedback and adjust the circulating pump operating frequency, thus achieving better energy-saving operation.

Description

Technical Field

[0001] This application relates to the field of heat exchange station control technology, and in particular to an adaptive variable frequency control method for the circulating pump of a heat exchange station in a courtyard pipe network heating system. Background Technology

[0002] Courtyard pipe network heating systems are a crucial link in the "source-network-station-load" system, and the heating industry is increasingly focusing on the balance and regulation of courtyard pipe networks. Publication No. CN113446660A discloses "A Method and System for Hydraulic Balance Regulation of a Secondary Network." This system, based on basic data of the courtyard pipe network, performs hydraulic calculations to determine the building's heating inlet for the most unfavorable loop. It then calculates the target value for the building's heating inlet for the most unfavorable loop using measured supply and return water temperatures and circulation flow rates. Based on the target value, flow control valves are manually adjusted on-site, and the operating frequency of the circulating pump is adjusted in conjunction with the heating parameters of the most unfavorable loop. However, this method requires monitoring the supply and return water temperatures and circulation flow rates of each heating inlet, resulting in excessive computational workload. Furthermore, it neglects the identification of the supply and demand status of the "station-load," the coupling between the heating inlets of each building, and feedback on the actual heating effect from users. It also fails to clearly define how the circulating pump within the heat exchange station adjusts its frequency based on the target value of the most unfavorable loop, making implementation extremely difficult.

[0003] Currently, the method of "relatively consistent return water temperature" has become a widely adopted approach in courtyard pipe networks. Announcement No. CN108826436B published "An Automatic Balancing Regulation Method for Secondary Heating Based on Return Water Temperature and Its Intelligent Energy Consumption Monitoring System." This system automatically adjusts the electric regulating valves at the heat inlets of each building by comparing the weighted average return water temperature value with the target value, thereby achieving balanced heating.

[0004] In actual engineering projects, the resistance along the courtyard pipe network changes due to variations in parameters such as on-site construction, maintenance, and flow rate. Furthermore, the occupancy rate and resistance of each building are adjusted annually, and the buildings with the most unfavorable loops will also change. The actual conditions of the courtyard pipe network system and the indoor temperature of heat users cannot be ignored; the most unfavorable loops should not be identified solely based on design conditions.

[0005] Currently, the control of circulating pumps in heat exchange stations of courtyard pipe network heating systems often relies on manual experience, employing a phased frequency or constant pressure differential control method. In actual projects, influenced by factors such as primary network regulation and outdoor meteorological parameters, relying solely on manual experience to adjust the circulating pump's operating frequency or pressure differential in stages frequently leads to insufficient or excessive heating. Therefore, there is an urgent need for a control method that combines user room temperature feedback with station load supply and demand matching. Summary of the Invention

[0006] In order to improve the energy distribution efficiency and reduce energy consumption in the heating system, this application provides an adaptive variable frequency control method for the circulating pump of the heat exchange station in a courtyard pipe network heating system.

[0007] Firstly, the adaptive variable frequency control method for the circulating pump of the heat exchange station in the courtyard pipe network heating system provided in this application adopts the following technical solution:

[0008] An adaptive variable frequency control method for the circulating pump of a heat exchange station in a courtyard pipe network heating system includes:

[0009] Collect relevant temperature information from the heat exchange station and heat users, and calculate the target return water temperature t at the heat inlet of each building. 2hmi The relevant temperature information of the heat exchange station includes the measured temperature (t) supplied by the secondary network at the heat exchange station. 2g The measured secondary network return temperature at the heat exchange station (t) 2h The relevant temperature information for heat users includes the indoor temperature t of the heat user. n outdoor temperature of heating users t w ;

[0010] Collect the valve opening K of the intelligent balancing valve at the heat inlet of each building. i Measured return water temperature (t) at the heating inlet of each building 2hi Based on the pre-set first judgment condition, the maximum valve opening K′ of the intelligent balancing valve for the building's heat inlet, after removing abnormal data from the building's heat inlet, is calculated. max ;

[0011] According to the valve opening K of the intelligent balancing valve at the heat inlet of each building i Measured return water temperature (t) at the heating inlet of each building 2hi Target return water temperature (t) at the heating inlet of each building 2hmi The maximum valve opening K′ of the intelligent balancing valve at the building's heat inlet with no abnormal data. max Representatives of heat users at the heating inlets of each building and their room temperature (t) ni The most unfavorable loop is identified by the set second judgment condition;

[0012] The opening K of the building's heating inlet b in the most unfavorable loop b The analysis was conducted, and the operating frequency of the circulating pump was adjusted based on the analysis results.

[0013] A further technical solution involves: calculating the target return water temperature t at the heat inlet of each building. 2hmi Specifically, this includes:

[0014] Based on the relevant temperature information from the heat exchange station and the relevant temperature information from the heat users, the cumulative average heating characteristic parameter α for each unit is calculated and can be obtained from the following formula:

[0015]

[0016] In the formula, k1 and k2 are the comprehensive heat transfer coefficient of the building envelope and the heat transfer coefficient of the heat dissipation equipment of the heat user, respectively (W / (m²)).2 ·℃), F1 and F2 are the comprehensive heat transfer area of ​​the lower enclosure structure of the heat exchange station and the comprehensive heat dissipation equipment area of ​​the heat user, respectively;

[0017] Determine the control cycle of the heat exchange station, and calculate the target return water temperature t of the heat exchange station based on the cumulative average heating characteristic parameter α under the current control cycle. 2hm It can be derived from the following formula:

[0018] t 2hm =2×[α(t) npm -t w )+t npm ]-t 2gm

[0019] In the formula, t npm For the target average room temperature, t 2gm The target value for the secondary network heating supply of the heat exchange station;

[0020] Based on the target return water temperature t of the heat exchange station 2hm Calculate the target return water temperature t at the heat inlet of each building. 2hmi， It can be derived from the following formula:

[0021] t 2hmi =β i t 2hm

[0022] In the formula, β i Correction coefficients for the heat inlets of each building.

[0023] A further technical solution is that, when determining the control cycle of the heat exchange station, the specific steps include:

[0024] The target value t for the secondary network heating supply of the heat exchange station is determined using an MLR network model. 2gm Predictions are made based on the target temperature t of the secondary network supply to the heat exchange station. 2gm The control cycle T of the heat exchange station is determined by the building's thermal inertia.

[0025] A further technical solution is as follows: the maximum valve opening K′ of the intelligent balancing valve for the building's heat inlet, which calculates the abnormal data of the building's heat inlet, is calculated. max Specifically, this includes:

[0026] According to the valve opening K of the intelligent balancing valve at the heat inlet of each building i The maximum opening degree K of the intelligent balancing valve at the heat inlet of each building was calculated. max Minimum valve opening K of the intelligent balancing valve for the heating inlet of each building min It can be derived from the following formula:

[0027] K max =max(K1, K2, ..., K) n)

[0028] K min =min(K1, K2, ..., K) n )

[0029] According to the maximum opening K max Minimum valve opening K min The system uses a pre-set first judgment condition to determine abnormal data of the building's heat inlet for the current period;

[0030] Remove outlier data and recalculate the maximum valve opening K′ of the intelligent balancing valve at the heat inlet of each building. max It can be derived from the following formula:

[0031] K′ max =max(K1, K2, ..., K) n )

[0032] A further technical solution is that, after determining the abnormal data of the building's heat inlet in the current period, it also includes outputting corresponding prompt information.

[0033] A further technical solution is that the first judgment condition and the corresponding prompt information include:

[0034] When the building's heating inlet valve opening degree K max >95%, measured return water temperature t 2hi ≤t 2hmi -10 indicates a need to check the temperature return probe on-site.

[0035] When the building's heating inlet valve opening degree K max >95%, measured return water temperature t 2hm -10≤t 2hi ≤t 2hmi -5 indicates a prompt to check the filter and vent air on-site;

[0036] When the building's heating inlet valve opening degree K min <5%, measured return water temperature t 2hi ≥t 2g -3 indicates a prompt to check on-site whether the temperature return probe is installed on the water supply.

[0037] A further technical solution is that identifying the most unfavorable loop specifically includes:

[0038] According to the valve opening K of the intelligent balancing valve at the heat inlet of each building i Measured return water temperature (t) at the heating inlet of each building 2hi Target return water temperature (t) at the heating inlet of each building 2hmi The maximum valve opening K′ of the intelligent balancing valve at the building's thermal inlet with no abnormal data. maxCalculate the temperature return deviation Δt at the heat inlet of each building. 2hi The valve opening difference ΔK between the intelligent balancing valves at the heating inlets of each building and the valve opening of each building. i It can be derived from the following formula:

[0039] Δt 2hi =t 2hmi -t 2hi

[0040] ΔK i =K i -K′ max

[0041] Based on the temperature return deviation value Δt of the heat inlet of each building 2hi The valve opening difference ΔK of the intelligent balancing valves at the heating inlets of each building i Each building's heating inlet, representing the room temperature (t) of the heat user. ni The most unfavorable loop is identified based on a preset second judgment condition, which includes:

[0042] Select ΔK i ≥5%, The building's heating inlet represents the room temperature (t). ni The smallest building's heating inlet is the most unfavorable loop.

[0043] A further technical solution involves adjusting the opening K of the building's thermal inlet b in the most unfavorable loop. b When conducting analysis and adjusting the operating frequency of the circulating pump based on the analysis results, the specific steps include:

[0044] Select the valve opening K of the building's thermal inlet b in the most unfavorable loop during the first half of the control cycle. b When K b When ≥95%, the circulating pump maintains its current frequency; K b When <95%, the circulation pump frequency is reduced until K. b ≥95%.

[0045] Secondly, the intelligent device provided in this application adopts the following technical solution:

[0046] A smart device includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as in any of the methods in the first aspect.

[0047] Thirdly, the computer-readable storage medium provided in this application adopts the following technical solution:

[0048] A computer-readable storage medium storing a computer program that can be loaded by a processor and executed as in any of the methods in the first aspect.

[0049] The beneficial effects of adopting the above technical solution are as follows:

[0050] This application, based on achieving a balanced courtyard pipe network, uses algorithms to diagnose abnormal operating data (valve opening, measured return water temperature) at the building's heat inlet. By comparing and analyzing the building's heat inlet operating data, the most unfavorable loop in the courtyard pipe network is identified. The operating frequency of the circulating pump is then adjusted based on the actual operating data of the most unfavorable loop (valve opening, difference between measured return water temperature and target return water temperature). Taking the "station-load" system as a whole, the circulating pump frequency adjustment cycle is determined to achieve dynamic and adaptive adjustment of the heat exchange station's circulating pump frequency. Compared to traditional methods of controlling circulating pumps with fixed frequency or pressure difference, this approach reduces fluctuations in indoor temperature, preventing overheating or overcooling. Furthermore, by using the most unfavorable loop at the building's heat inlet to provide feedback and adjust the circulating pump's operating frequency, energy-saving operation is better achieved. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the overall method steps provided in an embodiment of this application;

[0052] Figure 2 This is a detailed schematic diagram of the steps of a method provided in an embodiment of this application;

[0053] Figure 3 This is a schematic diagram showing another detailed method step provided in the embodiments of this application;

[0054] Figure 4 This is a detailed schematic diagram illustrating another method step provided in the embodiments of this application;

[0055] Figure 5 This is a schematic diagram showing the connection between the heating station and the heating inlet in this application;

[0056] Figure 6 This application lists the corresponding charts of valve opening degree and temperature in each building.

[0057] Figure 7 This is a flowchart of a method provided in this application. Detailed Implementation

[0058] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this application or its application or use. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0059] Many specific details are set forth in the following description in order to provide a full understanding of this application. However, this application may also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0060] First, a brief introduction to the heat exchange station of the courtyard pipe network heating system. Within the heat exchange station, a smart heating monitoring platform analyzes received parameters, including the operating frequency of the circulating pump, secondary heating, secondary return heating, circulation flow rate, the opening degree of the intelligent balancing valve at the building's heat inlet, measured return water temperature, and indoor temperature of heat users. The power of the courtyard pipe network is provided by the circulating pump, achieving balance among the buildings, ensuring that the friction resistance along the pipes is uniform across all buildings. Due to changes in heat demand from users and the heat supply from the heat exchange station, valves in the most unfavorable loop buildings may not be fully open, or may have a small opening. This indicates that the circulating pump's operating frequency is too high, resulting in excessive power consumption. Therefore, the operating frequency of the circulating pump needs to be adjusted.

[0061] Based on the theory of unit supply and demand balance, this application formulates a building heat inlet regulation strategy, and further uses the opening degree of the heat inlet valve of the most unfavorable building and the user room temperature as the basis to autonomously regulate the operating frequency of the heat exchange station circulating pump, thus deriving a method and device for adaptive variable frequency control of the heat exchange station circulating pump.

[0062] like Figures 1-4 As shown, the adaptive frequency conversion control method for the circulating pump of the heat exchange station in a courtyard pipe network heating system disclosed in this application specifically includes the following steps:

[0063] Step S100: Collect relevant temperature information from the heat exchange station and heat users, and calculate the target return water temperature t at the heat inlet of each building. 2hmi .

[0064] Among them, the relevant temperature information of the heat exchange station includes the measured secondary network supply temperature (t) of the heat exchange station. 2g The measured secondary network return temperature at the heat exchange station (t) 2h Temperature information related to heat users includes the indoor temperature (t) of the heat user. n outdoor temperature of heating users t w .

[0065] Calculate the target return water temperature t at the heat inlet of each building. 2hmi Specifically, it includes the following steps:

[0066] Step S110: Calculate the cumulative average heating characteristic parameter α for each unit based on the relevant temperature information of the heat exchange station and the relevant temperature information of the heat users. This parameter can be obtained from equation (1):

[0067]

[0068] In equation (1), k1 and k2 are the comprehensive heat transfer coefficient of the building envelope and the heat transfer coefficient of the heat dissipation equipment of the heat user, respectively (W / (m²)). 2 ·℃), F1 and F2 are the comprehensive heat transfer area of ​​the lower enclosure structure of the heat exchange station and the comprehensive heat dissipation equipment area of ​​the heat user, respectively.

[0069] Step S120: Calculate the target temperature t of the secondary network supply to the heat exchange station using an MLR network model. 2gm Predictions are made based on the target temperature t of the secondary network supply to the heat exchange station. 2gm The control period T of the heat exchange station is determined based on the building's thermal inertia, and the target return water temperature t of the heat exchange station is calculated based on the average heating characteristic parameter α under the current control period. 2hm This can be derived from equation (2):

[0070] t 2hm =2×[α(t) npm -t w )+t npm ]-t 2gm (2)

[0071] In equation (2), t npm For the target average room temperature, t 2gm The target value for the secondary network heating supply of the heat exchange station.

[0072] Among them, building thermal inertia refers to the time required for a significant change in room temperature at heat users after a change in the amount of heat supplied by the heating station. An MLR network model is used to analyze the target value t of the secondary heating supply. 2gm The prediction method is based on existing technology and will not be elaborated upon here.

[0073] Step S130: Based on the target return water temperature t of the heat exchange station 2hm Calculate the target return water temperature t at the heat inlet of each building. 2hmi， This can be derived from equation (3):

[0074] t 2gmi =β i t 2hm (3)

[0075] In equation (3), β i Correction coefficients for the heat inlets of each building.

[0076] Step S200: Collect the valve opening K of the intelligent balancing valve at the heat inlet of each building. i Measured return water temperature (t) at the heating inlet of each building 2hi Based on the pre-set first judgment condition, the maximum valve opening K′ of the intelligent balancing valve for the building's heat inlet, after removing abnormal data from the building's heat inlet, is calculated. max .

[0077] The abnormal data for building heating inlets includes data showing that the opening of the building heating inlet's intelligent balancing valve is too small. The maximum valve opening K′ of the building heating inlet's intelligent balancing valve is calculated after removing the abnormal data. max Specifically, the process includes the following steps:

[0078] Step S210: Based on the valve opening K of the intelligent balancing valve at the heat inlet of each building. i The maximum opening degree K of the intelligent balancing valve at the heat inlet of each building was calculated. max Minimum valve opening K of the intelligent balancing valve for the heating inlet of each building min It can be derived from the following formula:

[0079] K max =max(K1, K2, ..., K) n (4)

[0080] K min =min(K1, K2, ..., K) n (5)

[0081] Step S220: Based on the maximum opening K max Minimum valve opening K min The system uses a pre-set first judgment condition to determine abnormal data at the building's heat inlet for the current period and outputs corresponding prompts.

[0082] The first judgment condition and the corresponding prompt information include:

[0083] When the building's heating inlet valve opening degree K max >95%, measured return water temperature t 2hi ≤t 2hmi -10 indicates a need to check the temperature return probe on-site.

[0084] When the building's heating inlet valve opening degree K max >95%, measured return water temperature t 2hmi -10≤t 2hi ≤t 2hmi -5 indicates a prompt to check the filter and vent air on-site;

[0085] When the building's heating inlet valve opening degree K min <5%, measured return water temperature t 2hi ≥t 2g -3 indicates a prompt to check on-site whether the temperature return probe is installed on the water supply.

[0086] Step S230: Remove abnormal data and recalculate the maximum valve opening K′ of the intelligent balancing valve at the heat inlet of each building. max This can be derived from equation (6):

[0087] K′ max =max(K1, K2, ..., K) n (6)

[0088] Step S300: Based on the valve opening K of the intelligent balancing valve at the heat inlet of each building. i Measured return water temperature (t) at the heating inlet of each building 2hi Target return water temperature (t) at the heating inlet of each building 2hmi Representatives of heat users at the heating inlets of each building and their room temperature (t) ni The most unfavorable loop is identified by setting a second judgment condition.

[0089] Among them, the room temperature t of each building's heat inlet heat user is represented by ni The average room temperature for valid users is the measured average room temperature, excluding abnormal users and users without heating. Identifying the most unfavorable loop specifically includes the following steps:

[0090] Step S310: Based on the valve opening K of the intelligent balancing valve at the heat inlet of each building. i Measured return water temperature (t) at the heating inlet of each building 2hi Target return water temperature (t) at the heating inlet of each building 2hmi The maximum valve opening K′ of the intelligent balancing valve at the building's thermal inlet with no abnormal data. max Calculate the temperature return deviation Δt at the heat inlet of each building. 2hi The valve opening difference ΔK between the intelligent balancing valves at the heating inlets of each building and the valve opening of each building. i It can be derived from equations (7) and (8):

[0091] Δt 2hi =t 2hmi -t 2hi (7)

[0092] ΔK i =K i -K′ max (8)

[0093] Step S320: Based on the temperature return deviation value Δt of the heat inlet for each building 2hi The valve opening difference ΔK of the intelligent balancing valves at the heating inlets of each building i Each building's heating inlet, representing the room temperature (t) of the heat user. ni The most unfavorable loop is identified based on a preset second judgment condition, which includes:

[0094] Select ΔK i ≥5%, The building's heating inlet represents the room temperature (t). ni The smallest building's heating inlet is the most unfavorable loop.

[0095] It should be understood that the most unfavorable loop refers to the loop in the courtyard pipe network that suffers the greatest loss along its length relative to other buildings. Figure 5 Taking this as an example, when heat inlet 1 reaches the balance target, the valve opening is 50%; when heat inlet n reaches the balance target, the valve opening is 30%; when heat inlet 2 reaches the balance target, the valve opening is 80%. Therefore, heat inlet 2 is the most unfavorable loop.

[0096] Step S400: Determine the opening K of the building's thermal inlet b for the most unfavorable loop. b The analysis was conducted, and the operating frequency of the circulating pump was adjusted based on the analysis results.

[0097] Specifically, the valve opening K of the building's thermal inlet b in the most unfavorable loop during the first half of the control cycle is selected. b When K b When ≥95%, the circulating pump maintains its current frequency; K b When <95%, the circulation pump frequency is reduced until K. b ≥95%.

[0098] After the circulating pump operating frequency is issued, the smart heating monitoring platform issues control commands to the heat exchange station control cabinet, which then issues the control commands to the circulating pump frequency converter. The circulating pump then executes the target value within the current control cycle.

[0099] The following examples demonstrate the regulatory effect of this invention.

[0100] Please refer to Figure 5 and Figure 6 :

[0101] The building area of ​​the study subject is 122,615.44 m². 2 The actual heating area during the 2022-2023 heating season was 82,047.16 m². 2 The heat exchange station serves the heating needs of 27 buildings, and 40 heat users on-site are equipped with room temperature data acquisition devices to monitor their heating status. Under adjusted operating parameters, the station's return water temperature change rate and the actual measured return water temperature changes in the buildings were recorded, with a data collection period of 2 hours and a station adjustment period of 1 day. Data from January 31st to February 7th, 2023 (8 days in total) were used for verification.

[0102] (1) Calculate the cumulative average heating characteristic parameter α of the heat exchange station, and fit the data of secondary heating, secondary return, indoor temperature of heat users, and outdoor meteorological data of the heat exchange station:

[0103]

[0104] (2) Using the MLR network model, the predicted values ​​for secondary heating from February 1st to February 7th are: 42.44℃, 43.06℃, 42.44℃, 42.11℃, 41.39℃, 42.54℃, and 42.36℃.

[0105] (3) Select the measured return water temperature t at the heat inlet of each building. 2hi Target return water temperature t 2hmi And valve opening parameters, compiled as follows Figure 4 As shown. The maximum valve opening at the heating inlets of buildings 131-1, 143-17, Unit 3 of Building 145, Unit 3 of Building 9-1 of Dacheng, Unit 2-1 of Building A of Rifeng Community, Unit 2-2 of Building A of Rifeng Community, Unit 1-1 of Building C of Rifeng Community, Unit 2-1 of Building C of Rifeng Community, and Unit 2-2 of Building C of Rifeng Community is 100%. The measured return water temperature and the target return water temperature difference are all within ±1℃, with no abnormal data. The minimum valve opening at the heating inlet of the building is 17%, and the measured return water temperature and the target return water temperature difference is 0.59℃. Based on comprehensive analysis, there are no abnormal building heating inlets.

[0106] (4) Online identification of the most unfavorable loop: Combine the building heat inlet with the maximum valve opening of 100% in step (3), compare the representative room temperature data of the building, and the heat inlet with the lowest representative room temperature value is Unit 3 of Building 145, which is the heat inlet of the most unfavorable loop building.

[0107] (5) Based on the valve opening collected at the start of the current control cycle at the thermal inlet of the building in the most unfavorable loop, according to... Figure 7 Adjust the frequency of the circulating pump using the specified method until the valve opening is greater than 95%. This completes the adaptive adjustment of the circulating pump frequency.

[0108] (6) Analysis of the control effect in this case shows that the standard deviation of the room temperature for heat users is 0.06, indicating excellent stability. The variable frequency operation of the circulating pump maximizes energy saving and consumption reduction while ensuring the stability of the room temperature for heat users.

[0109] This application also discloses an intelligent device, which includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed by any of the aforementioned methods.

[0110] This application also discloses a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by any of the methods described above.

[0111] The above description of the embodiments is only used to provide a detailed introduction to the technical solutions of this application. However, the description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention, and should not be construed as a limitation of the present invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this invention should be covered within the protection scope of this invention.

Claims

1. A method for adaptive variable frequency control of a circulation pump of a heat exchange station of a yard pipe network heating system, characterized in that, The method comprises the following steps: Collect heat exchange station related temperature information and heat user related temperature information, calculate each building heat inlet target return water temperature t 2hmi ; the heat exchange station related temperature information includes heat exchange station measured secondary network supply temperature t 2g And heat exchange station measured secondary network return temperature t 2h , the heat user related temperature information includes heat user indoor temperature t n And heat user outdoor temperature t w ; Collecting the valve opening degree Ki of the intelligent balancing valve at the heat supply inlet of each building and the measured return water temperature t at the heat supply inlet of each building 2hi , and combining a first judgment condition to calculate the maximum valve opening degree K' of the intelligent balancing valve at the heat supply inlet of each building excluding abnormal data max , wherein it specifically comprises: According to the valve opening K of the intelligent balancing valve of the heat inlet of each building i , the maximum valve opening K of the intelligent balancing valve of the heat inlet of each building max and the minimum valve opening K of the intelligent balancing valve of the heat inlet of each building min are calculated; According to the maximum opening degree K max , the minimum valve opening degree K min , and the first judgment condition set in advance, it is judged that the current period building heat inlet abnormal data; Wherein the first judgment condition includes: when building heat inlet valve opening K max > 95%, measured return water temperature t 2hi ≤ t 2hmi -10; when building heat inlet valve opening K max > 95%, measured return water temperature t 2hm -10 ≤ t 2hi ≤ t 2hmi -5; when building heat inlet valve opening K min < 5%, measured return water temperature t 2hi ≥ t 2g -3; The abnormal data is eliminated and the maximum valve opening degree K' of the intelligent balancing valve of each building heat inlet is recalculated max ; According to the valve opening degree Ki of each building heat inlet intelligent balance valve, the measured return water temperature t of each building heat inlet 2hi , the target return water temperature t of each building heat inlet 2hmi , the maximum valve opening degree K' of the building heat inlet intelligent balance valve without abnormal data max , and the representative room temperature t of the heat user of each building heat inlet ni The most unfavorable loop is identified through the set second judgment condition; wherein, the most unfavorable loop is identified specifically includes: According to the valve opening degree K of the intelligent balancing valve of each building heat inlet i , the measured return water temperature t of each building heat inlet 2hi , the target return water temperature t of each building heat inlet 2hmi , and the maximum valve opening degree K' of the intelligent balancing valve of the building heat inlet without abnormal data max The return temperature deviation value Δt of each building heat inlet is calculated 2hi , and the valve opening degree difference ΔK of the intelligent balancing valve of each building heat inlet i , which is obtained by the following formula: Δt 2hi = t 2hmi - t 2hi ; AK i = K i - K' max ; According to the heat inlet temperature deviation value Δt of each building 2hi , the valve opening difference value ΔK of the intelligent balancing valve of the heat inlet of each building i , the representative room temperature t of the heat user of the heat inlet of each building ni , and the preset second judgment condition, the most unfavorable loop is identified. Select ΔK i ≥ 5%, of the building heat inlet, the building heat inlet represents the room temperature t ni The minimum building heat inlet is the most unfavorable loop; The opening degree K of the building heat inlet b of the worst loop b The analysis is performed and the operating frequency of the circulating pump is adjusted according to the analysis result.

2. The adaptive frequency conversion control method for the circulating pump of the heat exchange station of the garden pipe network heating system according to claim 1, characterized in that, The calculating the building heat inlet target return water temperature t 2hmi comprises specifically: According to the heat exchange station related temperature information and the heat user related temperature information, the cumulative average heating characteristic parameter α of each unit is calculated, and the cumulative average heating characteristic parameter α can be obtained by the following formula: ； In the formula, k1 and k2 are the overall heat transfer coefficient of the envelope and the heat transfer coefficient of the heat user heat dissipation equipment respectively, w / (m 2 ℃), and F1 and F2 are the overall heat transfer area of the envelope and the overall heat dissipation area of the heat user heat dissipation equipment respectively. determining a regulation period of the heat exchange station, and calculating a target return water temperature t of the heat exchange station according to a cumulative average heating characteristic parameter a in the current regulation period 2hm may be obtained by the following formula: t 2h = 2 x [a(t npm -t w )+t npm ]-t 2gm ; In the formula, t npm is the target average room temperature, t 2gm is the target value of the secondary network supply temperature of the heat exchange station; According to the target return water temperature t of the heat exchange station 2hm The target return water temperature t of the heat supply inlet of each building is calculated 2hmi The target return water temperature t of the heat supply inlet of each building is calculated t 2hmi = β i t 2hm ; In the formula, β i is the correction coefficient for the heat inlet of each building.

3. The adaptive frequency conversion control method for the circulating pump of the heat exchange station of the garden pipe network heating system according to claim 2, characterized in that: The determination of the heat exchange station regulation period specifically comprises the following steps: The target value t for the secondary network heating supply of the heat exchange station is determined using an MLR network model. 2gm Predictions are made based on the target temperature t of the secondary network supply to the heat exchange station. 2gm The control cycle T of the heat exchange station is determined by the building's thermal inertia.

4. The adaptive frequency conversion control method for the circulating pump of the heat exchange station of the garden pipe network heating system according to claim 1, characterized in that, The maximum valve opening K' of the intelligent balancing valve of the building heat inlet is calculated by removing the abnormal data of the building heat inlet max When, specifically comprising: According to the valve opening degree Ki of the intelligent balancing valve of each building heat inlet, the maximum opening degree K of the intelligent balancing valve of each building heat inlet is calculated max and the minimum valve opening degree K of the intelligent balancing valve of each building heat inlet min , which can be obtained by the following formula: K max = max (K1, K2,..., K n ); K min = min (K1, K2,..., K n ); According to the maximum opening K max , the minimum valve opening K min and the first judgment condition set in advance, it is judged that the current period building heat inlet abnormal data; The abnormal data is eliminated and the maximum valve opening degree K' of the intelligent balancing valve of each building heat inlet is recalculated max This can be derived from the following formula: K' max = max (K1, K2,..., K n ).

5. The adaptive frequency conversion control method for the circulating pump of the heat exchange station of the garden pipe network heating system according to claim 4, characterized in that, After the current period building heat inlet abnormal data is judged, the corresponding prompt information is further output.

6. The adaptive frequency conversion control method for the circulating pump of the heat exchange station of the garden pipe network heating system according to claim 5, characterized in that, The corresponding prompt information comprises: When the building heat inlet valve opening K max > 95%, the measured return water temperature t 2hi ≤ t 2hmi -10, prompting the on-site inspection of the return temperature probe; When the building heat inlet valve opening K max > 95%, the measured return water temperature t 2hm -10≤t 2hi ≤t 2hmi -5, prompting on-site filter inspection and air exhaust; When the building heat inlet valve opening K min <5%, the measured return water temperature t 2hi ≥t 2g -3, prompt on-site inspection of the return temperature probe whether installed on the water supply.

7. The adaptive frequency conversion control method for the circulating pump of the heat exchange station of the garden pipe network heating system according to claim 1, characterized in that, The opening degree K of the building heat inlet b of the most unfavorable loop b The analysis and adjusting the operating frequency of the circulating pump according to the analysis result specifically include: Select the most unfavorable loop of the upper half of the control cycle building heat inlet b valve opening K b When K b ≥ 95%, the circulating pump keeps the current frequency; K b < 95%, the circulating pump is reduced in frequency until K b ≥ 95%.

8. A smart device, comprising: The device comprises a memory and a processor, and the memory stores a computer program capable of being loaded and executed by the processor and performing the method of any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The memory stores a computer program capable of being loaded and executed by the processor and performing the method of any one of claims 1 to 7.

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