Heat supply pipe network hydraulic balance adjusting system and method based on data acquisition

Abstract

The invention relates to the technical field of data processing, and discloses a heat supply pipe network hydraulic balance adjusting system and method based on data acquisition. According to the method, Internet of Things equipment is installed in a heat supply area of a power plant, an aggregation local area network is established through a wireless communication mode based on the installed Internet of Things equipment, an operation mode of the Internet of Things equipment is configured, and data in the heat supply area of the power plant is collected and monitored through the installed Internet of Things equipment. Meanwhile, data, collected in real time, in the heat supply area of the power plant are analyzed, the heat supply area of the power plant is regulated and controlled through a genetic algorithm on the basis of an analysis result, and the regulated and controlled result is uploaded in real time through the established aggregation local area network, so that real-time analysis and adjustment of the heat supply network are completed. And when the data uploaded in real time in the heat supply area of the power plant has fault data, the specific position of the fault in the heat supply area of the power plant is positioned, and maintenance personnel are arranged for maintenance, so that the real-time performance and the safety of hydraulic balance adjustment of the heat supply network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a heating pipe network hydraulic balance regulation system and method based on data collection. Background Art

[0002] Since the heating pipelines are located in the outside world, they are easily affected by the external environment. And since the mechanism model of the heating network involves complex flow and heat transfer knowledge, its calculation and control are difficult.

[0003] The existing Chinese patent application CN118133699A discloses a method and device for regulating water hydraulic balance based on artificial intelligence. The method predicts by establishing a simulation model, and performs static simulation calculations based on the prediction results to obtain static simulation calculation results; at the same time, the real-time operation data of the heating system is obtained, and the static simulation calculation results are corrected by using the obtained real-time operation data, and dynamic simulation calculations are performed to obtain dynamic simulation calculation results; the flow and pressure of each branch pipeline in the heating network are automatically adjusted; but since only static prediction simulation is used, abnormal conditions in the pipeline are not considered, and there are certain limitations. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a heating pipe network hydraulic balance regulation system and method based on data acquisition, which has the advantages of real-time, accuracy and safety, and solves the problem of difficult calculation and control of hydraulic regulation of heating pipelines.

[0006] (II) Technical solution

[0007] In order to solve the above-mentioned technical problem of difficult calculation and control of hydraulic regulation of heating pipelines, the present invention provides the following technical solutions:

[0008] This embodiment discloses a method for adjusting the hydraulic balance of a heating network based on data collection, which specifically includes the following steps:

[0009] S1. Install IoT devices in the heating area of ​​the power plant that needs to be monitored, and form an aggregated local area network based on the installed IoT devices through wireless communication mode;

[0010] S2. Configure the operation mode of the IoT device, and collect and monitor the data in the heating area of ​​the power plant in real time through the running IoT device;

[0011] S3, analyzing the data collected in real time within the heating area of ​​the power plant;

[0012] S4. Based on the obtained analysis results, the heating area of ​​the power plant is regulated by genetic algorithm, and the regulated results are uploaded in real time through the established aggregation local area network. The regulation results include the route of hot water reaching the target point, the heating temperature, and the pressure changes of each monitoring point and each section;

[0013] S5. When there is fault data in the data uploaded in real time within the heating area of ​​the power plant, locate the specific location of the fault within the heating area of ​​the power plant and arrange maintenance personnel to carry out repairs.

[0014] The present invention installs Internet of Things devices in the heating area of ​​a power plant, and forms an aggregated local area network through a wireless communication mode based on the installed Internet of Things devices, and configures the operation mode of the Internet of Things devices. The data in the heating area of ​​the power plant is collected and monitored through the installed Internet of Things devices. At the same time, the data collected in the heating area of ​​the power plant in real time is analyzed, and the heating area of ​​the power plant is regulated by a genetic algorithm based on the obtained analysis results. The results of the regulation are uploaded in real time through the formed aggregated local area network to complete the real-time analysis and regulation of the heating pipe network. At the same time, when there is fault data in the data in the heating area of ​​the power plant uploaded in real time, the specific location of the fault in the heating area of ​​the power plant is located and maintenance personnel are arranged to repair it, thereby improving the real-time and safety of the hydraulic balance regulation of the heating pipe network.

[0015] Preferably, the forming of an aggregated local area network based on installed IoT devices through a wireless communication mode comprises the following steps:

[0016] S11, dividing the pipe network of the power plant heating area to be monitored into nodes and sections, and setting a monitoring station at each divided node;

[0017] S12. Each monitoring station installs an IoT device at the beginning of the pipe network section in the area where the power plant needs to supply heat. At the same time, a distance interval is set in the pipe network section in each power plant heating area, and n monitoring points are set according to the distance interval threshold;

[0018] S13, based on the pipeline network in the power plant heating area, collect the geographical location information of each group of pipeline networks in the power plant heating area and upload it in real time;

[0019] S14. Establish and save a network topology based on the collected geographical location information of the pipe network in each group of power plant heating areas and the location information of the monitoring points.

[0020] Preferably, said establishing and saving the network topology comprises the following steps:

[0021] Set a triplet E to save the established network topology;

[0022] E = (A, N, D);

[0023] Among them, A represents the serial number of the region to which the current monitoring point in the network topology belongs; N represents the serial number of the current monitoring point in the network topology; and D represents the distance between the current monitoring station and the adjacent monitoring station in the network topology.

[0024] The present invention completes the establishment of a topological network of the pipeline network in each group of power plant heating areas by dividing the pipeline network in the power plant heating area and setting distance intervals, clarifies the relationship between various monitoring points in the power plant heating area, and improves the accuracy of hydraulic balance regulation of the heating pipeline network.

[0025] Preferably, configuring the operation mode of the IoT device and collecting and monitoring the data in the heating area of ​​the power plant in real time through the running IoT device includes the following steps:

[0026] Based on the monitoring time of the power plant's heating area, two operating modes of IoT devices are configured: manual monitoring and periodic monitoring;

[0027] Manual monitoring: real-time monitoring of the heating area of ​​the power plant through monitoring commands input by management personnel;

[0028] The periodic monitoring: according to the user's maintenance requirements for the power plant heating area, set the monitoring time interval, regularly monitor the power plant heating area, automatically report the monitoring results and provide a performance analysis report;

[0029] The data collected and monitored in real time within the heating area of ​​the power plant through the running IoT devices include: water flow pressure, water flow temperature, and water flow rate.

[0030] The present invention configures the operating mode of the Internet of Things device and collects data in the heating area of ​​the power plant through different modes, thereby ensuring the accuracy and real-time performance of the data in the heating area of ​​the power plant.

[0031] Preferably, the analysis of the data collected in real time within the heating area of ​​the power plant comprises the following steps:

[0032] S31. Establish a water flow pressure and thermal calculation model in the heating area of ​​the power plant;

[0033] S32. Analyze the heating area of ​​the power plant based on the established water flow pressure and thermal calculation model.

[0034] Preferably, the establishment of a water flow pressure and thermal calculation model in the heating area of ​​the power plant comprises the following steps:

[0035] Set Q = [Q1, Q2, ..., Q m-1 ], where Q1 represents the flow vector of the first monitoring point, Q m-1 represents the flow vector of the m-1th monitoring point, Q represents the flow vector set of each monitoring point, inflow is positive and outflow is negative;

[0036] Set G = [G1, G2, ..., G n ], where G1 represents the flow vector of the first segment, G n represents the flow vector of the nth section, G represents the flow vector set of each section;

[0037] The relationship between the flow vector of the monitoring point and the flow vector of the section is as follows:

[0038] HG = Q;

[0039] Among them, H represents the pipe network association matrix, which indicates the connection relationship between monitoring points and sections;

[0040] Establish the water flow pressure and thermal calculation model in the heating area of ​​the power plant:

[0041] According to the hydraulic equation, the relationship model between water flow pressure and section flow is as follows:

[0042] ΔP=SGG+ZK;

[0043] Among them, ΔP represents the pressure change during hydraulic flow, S represents the resistance coefficient of the section pipeline, Z represents the height difference between sections, and K represents the head vector of the water pump;

[0044] The relationship model between water flow temperature and section flow is as follows:

[0045]

[0046] Among them, h out represents the section outlet temperature, h in Indicates the section inlet temperature, V in Indicates the flow velocity at the section inlet, V out represents the outlet flow rate of the section, l represents the heat loss of the pipe section, and q represents the internal flow rate of the section.

[0047] Preferably, the analysis of the heating area of ​​the power plant based on the established water flow pressure and thermal calculation model comprises the following steps:

[0048] S321, access the established network topology in sequence, and establish a power plant heating area index matrix W based on the access results;

[0049] S322, set a queue d, visit all monitoring points in the network topology based on the established power plant heating area index matrix W through a breadth-first algorithm, and put the access order and the serial number of the corresponding monitoring point into the queue d in sequence;

[0050] The breadth-first algorithm visits all monitoring points in the network topology and includes the following steps:

[0051] Select a monitoring point as the initial point, and visit the monitoring points adjacent to the initial point in turn until all monitoring points are visited;

[0052] S323. Dynamically analyze each monitoring point in queue d based on the established pressure and thermal calculation model within the heating area of ​​the power plant.

[0053] The present invention ensures the accuracy and real-time performance of data analysis within the power plant heating area by establishing a pressure and thermal calculation model within the power plant heating area and analyzing data collected in real time within the power plant heating area based on the established pressure and thermal calculation model.

[0054] Preferably, the regulating the heating area of ​​the power plant by means of a genetic algorithm based on the obtained analysis results comprises the following steps:

[0055] S41, set the genetic population size, number of iterations and chromosome encoding;

[0056] S42, initialize the population and randomly generate the initial population S gen ;

[0057] S43, using the relationship model between temperature and section flow as the fitness function of the genetic algorithm, and calculating the fitness of each individual in the population;

[0058] Each individual is assumed to represent a group of heating lines, and each group of heating lines represents the line for transporting hot water from the heat source to the target point;

[0059] The fitness calculation formula for each individual is as follows:

[0060]

[0061] Among them, Fit(t) represents the fitness of the tth individual, h out represents the outlet temperature of the section, ΔP represents the pressure change during the hydraulic flow process;

[0062] S44, selecting the best individuals from all individuals based on the roulette wheel method;

[0063] The calculation formula for selecting the best individuals among all individuals by roulette is as follows:

[0064]

[0065] Among them, α(t) represents the probability of individual t being selected, and T represents the population size;

[0066] S45, cross the selected excellent individuals by sequential crossover, and generate a new population S' after crossover gen ;

[0067] S46, randomly select an individual in the population to perform marginalization with a set probability, and generate a mutated population S" gen ;

[0068] S47, comparing the fitness difference ΔFit between the initial population and the population after crossover mutation by the genetic algorithm;

[0069] When ΔFit<0, it means that the fitness of the mutated population is higher than that of the initial population, and the population is accepted. When ΔFit≥0, it means that the fitness of the mutated population is lower than that of the initial population, and the population is rejected.

[0070] S48, judging whether the maximum number of iterations has been reached according to the number of iterations of the algorithm, outputting the optimal solution when the maximum number of iterations has been reached, and continuing to execute steps S44-S47 when the maximum number of iterations has not been reached;

[0071] The optimal solution of the output is set as the optimal heating circuit;

[0072] Set the temperature threshold and pressure threshold for each monitoring point and each section;

[0073] After the optimal heating route is determined, when the heating temperature is lower than the set temperature threshold, the hot water is regulated by increasing the temperature and flow rate;

[0074] After the optimal heating circuit is determined, when the pressure in the heating circuit is less than the set pressure threshold, it indicates that there is a fault in the current heating circuit.

[0075] The present invention regulates the heating lines in the heating area of ​​a power plant by using a genetic algorithm, and compares the real-time monitoring data of the target points in the lines after regulation with the set threshold value, and completes the hydraulic balance regulation of the heating network through the comparison results, thereby improving the real-time performance of the hydraulic balance regulation of the heating network.

[0076] This embodiment discloses a heating pipe network hydraulic balance regulation system based on data collection, including an Internet of Things device, a network topology module, a data analysis module, a control module and a display module;

[0077] The IoT device includes: a temperature monitoring module, a pressure monitoring module, and a flow monitoring module; the temperature monitoring module is used to monitor the temperature changes in the heating area of ​​the power plant in real time; the pressure monitoring module is used to monitor the pressure changes in the heating area of ​​the power plant in real time; the flow monitoring module is used to monitor the flow changes in the heating area of ​​the power plant in real time;

[0078] The network topology module is used to establish a network topology to display the pipeline routes in the heating area of ​​the power plant;

[0079] The data analysis module is used to analyze the data monitored in real time by the IoT device;

[0080] The control module is used to control the analyzed data;

[0081] The display module is used to display various data within the heating area of ​​the power plant in real time.

[0082] (III) Beneficial effects

[0083] Compared with the prior art, the present invention provides a heating pipe network hydraulic balance regulation system and method based on data acquisition, which has the following beneficial effects:

[0084] 1. The invention installs Internet of Things devices in the heating area of ​​a power plant, and forms an aggregated local area network based on the installed Internet of Things devices through a wireless communication mode, and configures the operation mode of the Internet of Things devices. The data in the heating area of ​​the power plant is collected and monitored through the installed Internet of Things devices. At the same time, the data in the heating area of ​​the power plant collected in real time is analyzed, and the heating area of ​​the power plant is regulated by a genetic algorithm based on the analysis results. The results of the regulation are uploaded in real time through the established aggregated local area network to complete the real-time analysis and regulation of the heating pipeline network. At the same time, when there is fault data in the data in the heating area of ​​the power plant uploaded in real time, the specific location of the fault in the heating area of ​​the power plant is located and maintenance personnel are arranged to repair it, thereby improving the real-time and safety of the hydraulic balance regulation of the heating pipeline network.

[0085] 2. The invention completes the establishment of the pipeline topology network of each group of power plant heating areas by dividing the pipeline network in the power plant heating area and setting distance intervals, clarifies the relationship between various monitoring points in the power plant heating area, and improves the accuracy of hydraulic balance regulation of the heating pipeline network.

[0086] 3. This invention configures the operating mode of the Internet of Things devices and collects data within the heating area of ​​the power plant through different modes, thereby ensuring the accuracy and real-time nature of the data within the heating area of ​​the power plant.

[0087] 4. The invention ensures the accuracy and real-time performance of data analysis within the heating area of ​​a power plant by establishing a pressure and thermal calculation model within the heating area of ​​a power plant and analyzing data collected in real time within the heating area of ​​the power plant based on the established pressure and thermal calculation model.

[0088] 5. The invention regulates the heating lines within the heating area of ​​a power plant by using a genetic algorithm, and compares the real-time monitoring data of the target points in the lines after regulation with the set thresholds, and completes the hydraulic balance regulation of the heating network through the comparison results, thereby improving the real-time performance of the hydraulic balance regulation of the heating network. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] Figure 1 It is a structural schematic diagram of the hydraulic balance adjustment method of the heating pipe network of the present invention. DETAILED DESCRIPTION

[0090] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0091] Example 1

[0092] This embodiment discloses a method for adjusting the hydraulic balance of a heating network based on data collection, which specifically includes the following steps:

[0093] S1. Install IoT devices in the heating area of ​​the power plant that needs to be monitored, and form an aggregated local area network based on the installed IoT devices through wireless communication mode;

[0094] The following steps are involved in forming an aggregated LAN based on the installed IoT devices through wireless communication mode:

[0095] S11, dividing the pipe network of the power plant heating area to be monitored into nodes and sections, and setting a monitoring station at each divided node;

[0096] S12. Each monitoring station installs an IoT device at the beginning of the pipe network section in the area where the power plant needs to supply heat. At the same time, a distance interval is set in the pipe network section in each power plant heating area, and n monitoring points are set according to the distance interval threshold;

[0097] S13, based on the pipeline network in the power plant heating area, collect the geographical location information of each group of pipeline networks in the power plant heating area and upload it in real time;

[0098] S14, establishing and saving a network topology based on the collected geographical location information of the pipe network in each group of power plant heating areas and the location information of the monitoring points;

[0099] Set a triplet E to save the established network topology;

[0100] E = (A, N, D);

[0101] Among them, A represents the serial number of the region to which the current monitoring point in the network topology belongs; N represents the serial number of the current monitoring point in the network topology; and D represents the distance between the current monitoring station and the adjacent monitoring station in the network topology.

[0102] S2. Configure the operation mode of the IoT device, and collect and monitor the data in the heating area of ​​the power plant in real time through the running IoT device;

[0103] Based on the monitoring time of the power plant's heating area, two operating modes of IoT devices are configured: manual monitoring and periodic monitoring;

[0104] Manual monitoring: real-time monitoring of the heating area of ​​the power plant through monitoring commands input by management personnel;

[0105] The periodic monitoring: according to the user's maintenance requirements for the power plant heating area, set the monitoring time interval, regularly monitor the power plant heating area, automatically report the monitoring results and provide a performance analysis report;

[0106] The data collected and monitored in real time within the power plant’s heating area through the running IoT devices include: water flow pressure, water flow temperature, and water flow rate;

[0107] S3, analyzing the data collected in real time within the heating area of ​​the power plant;

[0108] The analysis of the real-time collected data within the power plant heating area includes the following steps:

[0109] S31. Establish a water flow pressure and thermal calculation model in the heating area of ​​the power plant;

[0110] Set Q = [Q1, Q2, ..., Q m-1 ], where Q1 represents the flow vector of the first monitoring point, Q m-1 represents the flow vector of the m-1th monitoring point, Q represents the flow vector set of each monitoring point, inflow is positive and outflow is negative;

[0111] Set G = [G1, G2, ..., G n ], where G1 represents the flow vector of the first segment, G n represents the flow vector of the nth section, G represents the flow vector set of each section;

[0112] Furthermore, the relationship between the flow vector of the monitoring point and the flow vector of the section is as follows:

[0113] HG = Q;

[0114] Among them, H represents the pipe network association matrix, which indicates the connection relationship between monitoring points and sections;

[0115] Furthermore, the water flow pressure and thermal calculation model in the heating area of ​​the power plant is established:

[0116] According to the hydraulic equation, the relationship model between water flow pressure and section flow is as follows:

[0117] ΔP=SGG+ZK;

[0118] Among them, ΔP represents the pressure change during hydraulic flow, S represents the resistance coefficient of the section pipeline, Z represents the height difference between sections, and K represents the head vector of the water pump;

[0119] The relationship model between temperature and zone flow is as follows:

[0120]

[0121] Among them, h out represents the section outlet temperature, h in Indicates the section inlet temperature, V in Indicates the flow rate at the section inlet, V out represents the outlet flow rate of the section, l represents the heat loss of the pipe section, and q represents the internal flow rate of the section;

[0122] S32, analyzing the heating area of ​​the power plant based on the established water flow pressure and thermal calculation model;

[0123] The analysis of the heating area of ​​the power plant based on the established water flow pressure and thermal calculation model includes the following steps:

[0124] S321, access the established network topology in sequence, and establish a power plant heating area index matrix W based on the access results;

[0125] S322, set a queue d, based on the established power plant heating area index matrix W, access all monitoring points in the network topology through a breadth-first algorithm, and put the access order and the serial number of the corresponding monitoring point into the queue d in sequence;

[0126] The breadth-first algorithm visits all monitoring points in the network topology and includes the following steps:

[0127] Select a monitoring point as the initial point, and visit the monitoring points adjacent to the initial point in turn until all monitoring points are visited;

[0128] S323, dynamically analyzing each monitoring point in queue d based on the established pressure and thermal calculation model in the heating area of ​​the power plant;

[0129] S4. Based on the obtained analysis results, the heating area of ​​the power plant is regulated by genetic algorithm, and the regulated results are uploaded in real time through the established aggregation local area network. The regulation results include the route of hot water reaching the target point, the heating temperature, and the pressure changes of each monitoring point and each section;

[0130] Based on the obtained analysis results, the regulation of the heating area of ​​the power plant through the genetic algorithm includes the following steps:

[0131] S41, set the genetic population size, number of iterations and chromosome encoding;

[0132] S42, initialize the population and randomly generate the initial population S gen ;

[0133] S43, using the relationship model between temperature and section flow as the fitness function of the genetic algorithm, and calculating the fitness of each individual in the population;

[0134] Each individual is assumed to represent a group of heating lines, and each group of heating lines represents the line for transporting hot water from the heat source to the target point;

[0135] The fitness calculation formula for each individual is as follows:

[0136]

[0137] Among them, Fit(t) represents the fitness of the tth individual, h out represents the outlet temperature of the section, ΔP represents the pressure change during the hydraulic flow process;

[0138] S44, selecting the best individuals from all individuals based on the roulette wheel method;

[0139] The calculation formula for selecting the best individuals among all individuals by roulette is as follows:

[0140]

[0141] Among them, α(t) represents the probability of individual t being selected, and T represents the population size;

[0142] S45, cross the selected excellent individuals by sequential crossover, and generate a new population S' after crossover gen ;

[0143] S46, randomly select an individual in the population to perform marginalization with a set probability, and generate a mutated population S" gen ;

[0144] S47, comparing the fitness difference ΔFit between the initial population and the population after crossover mutation by the genetic algorithm;

[0145] When ΔFit<0, it means that the fitness of the mutated population is higher than that of the initial population, and the population is accepted. When ΔFit≥0, it means that the fitness of the mutated population is lower than that of the initial population, and the population is rejected.

[0146] S48, judging whether the maximum number of iterations has been reached according to the number of iterations of the algorithm, outputting the optimal solution when the maximum number of iterations has been reached, and continuing to execute steps S44-S47 when the maximum number of iterations has not been reached;

[0147] The optimal solution of the output is set as the optimal heating circuit;

[0148] Set the temperature threshold and pressure threshold for each monitoring point and each section;

[0149] After the optimal heating route is determined, when the heating temperature is lower than the set temperature threshold, the hot water is regulated by increasing the temperature and flow rate;

[0150] After the optimal heating line is determined, if the pressure in the heating line is less than the set pressure threshold, it indicates that there is a fault in the current heating line;

[0151] S5. When there is fault data in the data uploaded in real time within the heating area of ​​the power plant, locate the specific location of the fault within the heating area of ​​the power plant and arrange maintenance personnel to repair it;

[0152] When the pipeline is repaired, the corresponding pipeline in the repaired heating area of ​​the power plant is immediately measured and monitored, the latest measured data in the heating area of ​​the power plant is entered, and the monitoring status of the heating area of ​​the power plant is displayed synchronously.

[0153] Example 2

[0154] This embodiment discloses a heating network hydraulic balance regulation system based on data collection, including: an Internet of Things device, a network topology module, a data analysis module, a control module and a display module;

[0155] The IoT device includes: a temperature monitoring module, a pressure monitoring module, and a flow monitoring module; the temperature monitoring module is used to monitor the temperature changes in the heating area of ​​the power plant in real time; the pressure monitoring module is used to monitor the pressure changes in the heating area of ​​the power plant in real time; the flow monitoring module is used to monitor the flow changes in the heating area of ​​the power plant in real time;

[0156] The network topology module is used to establish a network topology to display the pipeline routes in the heating area of ​​the power plant;

[0157] The data analysis module is used to analyze the data monitored in real time by the IoT device;

[0158] The control module is used to control the analyzed data;

[0159] The display module is used to display various data within the heating area of ​​the power plant in real time.

[0160] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for regulating the hydraulic balance of a heating network based on data collection, characterized in that: The following steps are involved: S1. Install IoT devices in the heating area of ​​the power plant that needs to be monitored, and form an aggregated local area network based on the installed IoT devices through wireless communication mode; S2. Configure the operation mode of the IoT device, and collect and monitor the data in the heating area of ​​the power plant in real time through the running IoT device; S3, analyzing the data collected in real time within the heating area of ​​the power plant; S4. Based on the obtained analysis results, the heating area of ​​the power plant is regulated by genetic algorithm, and the regulated results are uploaded in real time through the established aggregation local area network. The regulation results include the route of hot water reaching the target point, the heating temperature, and the pressure changes of each monitoring point and each section; S5. When there is fault data in the data uploaded in real time within the heating area of ​​the power plant, locate the specific location of the fault within the heating area of ​​the power plant and arrange maintenance personnel to carry out repairs.

2. A method for adjusting the hydraulic balance of a heating network based on data acquisition according to claim 1, characterized in that: The method of forming an aggregated local area network based on installed IoT devices through wireless communication mode includes the following steps: S11, dividing the pipe network of the power plant heating area to be monitored into nodes and sections, and setting a monitoring station at each divided node; S12. Each monitoring station installs an IoT device at the beginning of the pipe network section in the area where the power plant needs to supply heat. At the same time, a distance interval is set in the pipe network section in each power plant heating area, and n monitoring points are set according to the distance interval threshold; S13, based on the pipeline network in the power plant heating area, collect the geographical location information of each group of pipeline networks in the power plant heating area and upload it in real time; S14. Establish and save a network topology based on the collected geographical location information of the pipe network in each group of power plant heating areas and the location information of the monitoring points.

3. A method for adjusting the hydraulic balance of a heating network based on data acquisition according to claim 2, characterized in that: The said establishing and saving the network topology comprises the following steps: Set a triplet E to save the established network topology; E = (A, N, D); Among them, A represents the serial number of the region to which the current monitoring point in the network topology belongs; N represents the serial number of the current monitoring point in the network topology; and D represents the distance between the current monitoring station and the adjacent monitoring station in the network topology.

4. A method for adjusting the hydraulic balance of a heating network based on data acquisition according to claim 1, characterized in that: The configuration of the operation mode of the IoT device and the real-time collection and monitoring of data in the heating area of ​​the power plant through the running IoT device include the following steps: Based on the monitoring time of the power plant's heating area, two operating modes of IoT devices are configured: manual monitoring and periodic monitoring; Manual monitoring: real-time monitoring of the heating area of ​​the power plant through monitoring commands input by management personnel; The periodic monitoring: according to the user's maintenance requirements for the power plant heating area, set the monitoring time interval, regularly monitor the power plant heating area, automatically report the monitoring results and provide a performance analysis report; The data collected and monitored in real time within the heating area of ​​the power plant through the running IoT devices include: water flow pressure, water flow temperature, and water flow rate.

5. The method for adjusting the hydraulic balance of a heating network based on data acquisition according to claim 1 is characterized in that: The analysis of the data collected in real time within the heating area of ​​the power plant comprises the following steps: S31. Establish a water flow pressure and thermal calculation model in the heating area of ​​the power plant; S32. Analyze the heating area of ​​the power plant based on the established water flow pressure and thermal calculation model.

6. A method for adjusting the hydraulic balance of a heating network based on data acquisition according to claim 5, characterized in that: The establishment of the pressure and thermal calculation model within the power plant heating area comprises the following steps: Set Q = [Q1, Q2, ..., Q m-1 ], where Q1 represents the flow vector of the first monitoring point, Q m-1 represents the flow vector of the m-1th monitoring point, Q represents the flow vector set of each monitoring point, inflow is positive and outflow is negative; Set G = [G1, G2, ..., G n ], where G1 represents the flow vector of the first segment, G n represents the flow vector of the nth section, G represents the flow vector set of each section; The relationship between the flow vector of the monitoring point and the flow vector of the section is as follows: HG = Q; Among them, H represents the pipe network association matrix, which indicates the connection relationship between monitoring points and sections; Establish the water flow pressure and thermal calculation model in the heating area of ​​the power plant: According to the hydraulic equation, the relationship model between water flow pressure and section flow is as follows: ΔP=SGG+ZK; Among them, ΔP represents the pressure change during hydraulic flow, S represents the resistance coefficient of the section pipeline, Z represents the height difference between sections, and K represents the head vector of the water pump; The relationship model between temperature and zone flow is as follows: Among them, h out represents the section outlet temperature, h in Indicates the section inlet temperature, V in Indicates the flow velocity at the section inlet, V out represents the outlet flow rate of the section, l represents the heat loss of the pipe section, and q represents the internal flow rate of the section.

7. A method for adjusting the hydraulic balance of a heating network based on data acquisition according to claim 5, characterized in that: The analysis of the heating area of ​​the power plant based on the established water flow pressure and thermal calculation model includes the following steps: S321, access the established network topology in sequence, and establish a power plant heating area index matrix W based on the access results; S322, set a queue d, based on the established power plant heating area index matrix W, access all monitoring points in the network topology through a breadth-first algorithm, and put the access order and the serial number of the corresponding monitoring point into the queue d in sequence; The breadth-first algorithm visits all monitoring points in the network topology and includes the following steps: Select a monitoring point as the initial point, and visit the monitoring points adjacent to the initial point in turn until all monitoring points are visited; S323. Dynamically analyze each monitoring point in queue d based on the established pressure and thermal calculation model within the heating area of ​​the power plant.

8. The method for adjusting the hydraulic balance of a heating network based on data collection according to claim 1, characterized in that: The method of regulating the heating area of ​​the power plant by using a genetic algorithm based on the obtained analysis results comprises the following steps: S41, set the genetic population size, number of iterations and chromosome encoding; S42, initialize the population and randomly generate the initial population S gen ; S43, using the relationship model between temperature and section flow as the fitness function of the genetic algorithm, and calculating the fitness of each individual in the population; Each individual is assumed to represent a group of heating lines, and each group of heating lines represents the line for transporting hot water from the heat source to the target point; The fitness calculation formula for each individual is as follows: Among them, Fit(t) represents the fitness of the tth individual, h out represents the outlet temperature of the section, ΔP represents the pressure change during the hydraulic flow process; S44, selecting the best individuals from all individuals based on the roulette wheel method; The calculation formula for selecting the best individuals among all individuals by roulette is as follows: Among them, α(t) represents the probability of individual t being selected, and T represents the population size; S45, cross the selected excellent individuals by sequential crossover, and generate a new population S' after crossover gen ; S46, randomly select an individual in the population to perform marginalization with a set probability, and generate a mutated population S" gen ; S47, comparing the fitness difference ΔFit between the initial population and the population after crossover mutation by the genetic algorithm; When ΔFit<0, it means that the fitness of the mutated population is higher than that of the initial population, and the population is accepted. When ΔFit≥0, it means that the fitness of the mutated population is lower than that of the initial population, and the population is rejected. S48, judging whether the maximum number of iterations has been reached according to the number of iterations of the algorithm, outputting the optimal solution when the maximum number of iterations has been reached, and continuing to execute steps S44-S47 when the maximum number of iterations has not been reached; The optimal solution of the output is set as the optimal heating circuit; Set the temperature threshold and pressure threshold for each monitoring point and each section; After the optimal heating route is determined, when the heating temperature is lower than the set temperature threshold, the hot water is regulated by increasing the temperature and flow rate; After the optimal heating circuit is determined, when the pressure in the heating circuit is less than the set pressure threshold, it indicates that there is a fault in the current heating circuit.

9. A system for implementing the method for adjusting the hydraulic balance of a heating network based on data collection according to any one of claims 1 to 8, characterized in that: Including IoT devices, network topology module, data analysis module, control module and display module; The IoT device includes: a temperature monitoring module, a pressure monitoring module, and a flow monitoring module; the temperature monitoring module is used to monitor the temperature changes in the heating area of ​​the power plant in real time; the pressure monitoring module is used to monitor the pressure changes in the heating area of ​​the power plant in real time; the flow monitoring module is used to monitor the flow changes in the heating area of ​​the power plant in real time; The network topology module is used to establish a network topology to display the pipeline routes in the heating area of ​​the power plant; The data analysis module is used to analyze the data monitored in real time by the IoT device; The control module is used to control the analyzed data; The display module is used to display various data within the heating area of ​​the power plant in real time.

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