A method for controlling steam parameters of a precision-supplied steam pipe network

Abstract

The present application relates to a kind of precision supplied steam pipe network steam parameter control method, the steam pipe network includes one or more pipeline conveying device, the method comprises: S1, for each pipeline conveying device of steam pipe network, obtains the historical operation data of current pipeline conveying device;S2, according to the historical operation data of each pipeline conveying device, screening key data;S3, based on the key data of screening, obtains the conveying source adjustment parameter satisfying current pipeline conveying device;S4, according to the conveying source adjustment parameter of all pipeline conveying device, adjusts the conveying source control parameter of steam pipe network.This application finds the factory source steam parameter that satisfies all consumer user's steam pressure and temperature demand by analyzing historical operation data, reduces the fluctuation of pressure and temperature, makes production operation more stable, reduces steam loss, improves the economic benefit of thermal power plant.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of thermoelectricity, in particular to a steam parameter control method for precise supply of a steam pipe network. BACKGROUND

[0002] The existing thermal power plant delivers steam meeting the steam customer demand to the downstream customers through the steam pipe network. The downstream customers generally have clear steam pressure or temperature requirements. In order to avoid contract disputes in actual operation and control, the thermal power plant generally tends to provide steam with higher parameters to all users to meet the steam use requirements of the downstream customers, which causes excessive supply and waste of steam heat.

[0003] There is a relatively obvious delay in the transportation process of steam, which may reach 1-3 hours, which will cause serious hysteresis of terminal user temperature change. The traditional fluid mechanics calculation method has difficulties in application in the research of pipe network steam transportation law, because of its complex modeling, low accuracy, large calculation amount and long time-consuming. At present, the operation of the steam pipe network of the thermal power plant is seriously dependent on the experience of the operation personnel, and there is no scientific theory support, so the steam parameters cannot be optimized and controlled. In addition, the steam will produce pressure and temperature loss in the pipe transportation process, and the condensate water will be produced in the heat exchange process with the pipe wall, which will cause steam flow loss, and the value is as high as 20%-30% in actual operation. These problems are common in the actual operation of the existing thermal power plant customers, and have certain representativeness.

[0004] Therefore, it is urgent to provide a steam parameter control method which can effectively reduce the loss of steam pipe and realize real-time adjustment of steam parameters to achieve precise supply. SUMMARY

[0005] (I) Technical problems to be solved

[0006] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present application provides a steam parameter control method for precise supply of a steam pipe network.

[0007] (II) Technical scheme

[0008] In order to achieve the above-mentioned purpose, the main technical scheme adopted by the present application comprises:

[0009] In a first aspect, the present application provides a steam parameter control method for precise supply of a steam pipe network, the steam pipe network comprising one or more pipeline transportation devices, and the method comprising:

[0010] S1, for each pipeline transportation device of the steam pipe network, obtaining the historical operation data of the current pipeline transportation device, the historical operation data comprising: source control parameters; user side parameters; the distance between the user side and the transportation starting side;

[0011] S2, cleaning historical operation data of each pipeline conveying device according to the historical operation data, and screening key data in the cleaned historical operation data by using a pre-defined screening strategy;

[0012] S3, constructing adjustment information for monitoring and adjusting current data based on the screened key data, and obtaining a conveying source adjustment parameter meeting the current pipeline conveying device based on the adjustment information;

[0013] S4, adjusting a conveying source control parameter of the steam pipe network according to the conveying source adjustment parameter of all pipeline conveying devices.

[0014] Optionally, the conveying source control parameter includes temperature, pressure and flow rate on the side of the plant source.

[0015] The user side parameter includes temperature, pressure and flow rate on each user side.

[0016] Correspondingly, the S4 includes:

[0017] The maximum value of the pressure in the conveying source adjustment parameter of each pipeline conveying device in all pipeline conveying devices is taken as the conveying source adjustment parameter one of the steam pipe network, and the pressure value on the plant source side of the steam pipe network is adjusted.

[0018] The maximum value of the temperature in the conveying source adjustment parameter of each pipeline conveying device in all pipeline conveying devices is taken as the conveying source adjustment parameter two of the steam pipe network, and the temperature value on the plant source side of the steam pipe network is adjusted.

[0019] The conveying source adjustment parameter of all pipeline conveying devices includes the conveying source adjustment parameter one and the conveying source adjustment parameter two.

[0020] Optionally, when the adjustment information is pressure, the S2 includes:

[0021] S21, screening a key user group including at least one key user by using one or more of the following means:

[0022] According to the distance between the user side and the conveying starting side in the historical operation data, screening a user with the farthest distance;

[0023] According to the user side flow rate in the historical operation data, screening a user with a flow rate higher than a pre-set high threshold value and lower than a pre-set low threshold value;

[0024] According to the user side pressure and the plant source side pressure in the historical operation data, screening a user with the largest pressure loss under the same pressure demand;

[0025] S22, data cleaning is performed by using a clustering outlier identification method to obtain cleaned historical operation data;

[0026] S23, filtering historical operation data of users in all the key user groups as the key data according to the cleaned historical operation data.

[0027] Optionally, when the adjustment information is temperature, the S2 comprises:

[0028] S24, a key user group including at least one key user is screened by using one or more of the following means:

[0029] screening users with the farthest distance according to the distance between the user side and the delivery starting side in the historical operation data;

[0030] screening users with the flow rate on the user side exceeding a preset high threshold and being lower than a preset low threshold according to the flow rate on the user side in the historical operation data;

[0031] screening users with the largest temperature loss under the same temperature demand according to the user side temperature and the plant source side temperature in the historical operation data;

[0032] S25, data cleaning is performed by using a clustering outlier identification method, and data with a user side temperature value exceeding a preset overheating threshold is removed, to obtain cleaned historical operation data;

[0033] S26, filtering historical operation data of users in all the key user groups as the key data according to the cleaned historical operation data.

[0034] Optionally, when the adjustment information is pressure, the S3 comprises:

[0035] S31, for each user in the key data, pressure adjustment information of the user is obtained according to the user side pressure of the user and the plant source side pressure and flow rate of the user;

[0036] S32, selecting a maximum value as a delivery source pressure adjustment parameter satisfying the current pipeline delivery device according to the pressure adjustment information of the users in all the key data.

[0037] Optionally, the S31 comprises:

[0038] S311, obtaining a user side pressure drop of the user according to the plant source side pressure of the key data and the user side pressure of the user; the user side pressure drop is a difference between the plant source side pressure and the user side pressure of the user;

[0039] S312, fitting the user side pressure drop of the user and the plant source side flow rate data in a specified time period to obtain the following formula one and formula two,

[0040] Equation One

[0041] Equation Two

[0042] wherein ΔP is the user-side pressure drop of the user, P is the plant-source-side pressure, P' is the user-side pressure, D is the plant-source-side flow rate, a, b, c are constant coefficients obtained by fitting; and

[0043] S313, obtaining, based on Equation Two and the currently monitored P' and D, a plant-source-side pressure value corresponding to the user-side pressure requirement of the user as pressure adjustment information of the user.

[0044] Optionally, when the adjustment information is temperature, the S3 comprises:

[0045] S33, for each user in the key data, obtaining temperature adjustment information of the user according to the user-side temperature and the plant-source-side temperature and flow rate of the user;

[0046] S34, selecting a maximum value as a temperature adjustment parameter of the delivery source of the current pipeline delivery device according to the temperature adjustment information of the users in all the key data.

[0047] Optionally, the S33 comprises:

[0048] S331, determining, according to the key data, a delay time of the steam temperature from the plant-source-side to the user-side by using a time axis translation algorithm or a time delay algorithm based on fast Fourier transform;

[0049] S332, according to the key data and the delay time, performing time axis translation alignment processing on the user-side temperature, the plant-source-side flow rate and the plant-source-side temperature data of the user to obtain non-delay key data eliminating the delay influence of the steam temperature from the plant-source-side to the user-side;

[0050] S333, fitting the non-delay key data according to the user-side temperature, the plant-source-side flow rate and the plant-source-side temperature data of the user to obtain Equation Three and Equation Four:

[0051] Equation Three

[0052] Equation Four

[0053] wherein T' is the user-side temperature of the user, T is the plant-source-side temperature, D is the plant-source-side flow rate, d, e, f are constant coefficients obtained by fitting; and

[0054] S334, based on formula four and the current monitored T' and D, obtain the plant source side temperature value corresponding to the user side temperature demand of the user as the temperature adjustment information of the user.

[0055] The present application finds the relationship between the pressure loss from the plant source to the steam consumption side and the steam flow in the pipeline based on the loss characteristics of the steam pipeline obtained from the historical operation data, calculates the plant source supply pressure under different demands according to the pressure demand of the user, and finds the time delay of the steam temperature conduction to the consumption end through the historical operation data, and calculates the optimal supply temperature based on the time delay, which can meet the demand of the user end for the steam quality, and also effectively reduce the demand for the plant source steam parameters. The method of the present application applied to the control of the steam pipeline can reduce the fluctuations of the pressure and temperature, make the production operation more stable, reduce the steam loss, and improve the economic benefit of the thermal power plant.

[0056] In the second aspect, the present application provides a steam pipeline control device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the precise supply steam pipeline steam parameter control method of any one of the above first aspect when executing the computer program.

[0057] In the third aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the precise supply steam pipeline steam parameter control method of any one of the above first aspect when executed by a processor.

[0058] (Three) beneficial effects

[0059] Compared with the prior art, the present application finds the plant source steam parameters that meet the steam pressure and temperature demands of all consumption end users through the analysis of the historical operation data, reduces the fluctuations of the pressure and temperature, makes the production operation more stable, reduces the steam loss, and improves the economic benefit of the thermal power plant. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1 The flowchart of the steam pipeline steam parameter control method provided by an embodiment of the present application is shown in the figure;

[0061] Figure 2 The process block diagram of the adjustment information provided by an embodiment of the present application is shown in the figure;

[0062] Figure 3 The pressure drop fitting curve of a key user A provided by an embodiment of the present application is shown in the figure;

[0063] Figure 4A pressure drop fitting curve of a key user B provided for an embodiment of the present application;

[0064] Figure 5 A pressure maximum function curve of all key users of a pipeline provided for an embodiment of the present application;

[0065] Figure 6 A process block diagram of adjustment information for temperature provided for an embodiment of the present application;

[0066] Figure 7 A schematic diagram of a time delay relationship between user side temperature and plant source side flow signal provided for an embodiment of the present application;

[0067] Figure 8 A time delay trend graph of a time axis translation algorithm provided for an embodiment of the present application;

[0068] Figure 9 A time delay histogram of a time delay algorithm based on fast Fourier transform for judging time delay provided for an embodiment of the present application;

[0069] Figure 10 A scatter plot distribution and function relationship between user side temperature and plant source side temperature and flow after data alignment in time delay processing of a key user provided for an embodiment of the present application;

[0070] Figure 11 A temperature maximum function curve of a pipeline provided for an embodiment of the present application. DETAILED DESCRIPTION

[0071] In order to better understand the above technical solutions, the exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided so that the present application can be more clearly, thoroughly understood, and the scope of the present application can be completely conveyed to those skilled in the art.

[0072] In the existing billing mode based on the actual accepted steam flow of enterprise customers, the parameters of the plant steam source (temperature and pressure, steam superheat, etc.) are regulated to a certain extent. Under the condition of meeting the needs of steam customers, the steam source parameters and steam transportation loss are minimized to effectively improve the economic efficiency of the pipe network operation and the overall energy efficiency of the power plant.

[0073] The present application mainly aims at the pressure and temperature control problem of steam transportation pipe network user in engineering practice, obtains the loss characteristics of steam pipeline through historical operation data, finds the relationship between the pressure loss from the plant source to the steam consumption side and the steam flow in the pipeline, calculates the plant source supply pressure under different requirements according to the pressure requirement of the user; and finds the time delay of steam temperature conduction to the consumption end through historical operation data, calculates the best supply temperature on the basis of time delay, which can meet the requirement of the user end to the steam quality, and also can effectively reduce the requirement of the plant source steam parameters.

[0074] In order to better understand the technical scheme of the present application, some professional terms related to the present application are introduced as follows.

[0075] Saturation temperature and superheat degree: steam terminology, the inflection point of vapor-liquid conversion of steam at different pressures is the saturation temperature at this pressure, and the temperature higher than the saturation temperature is the superheat degree, and if the superheat degree is too low, it is easy to condense into water. For example, the saturation temperature corresponding to the pressure of 0.5mpa is 151 degrees, and if the current temperature is 161 degrees, the current superheat degree is 10 degrees.

[0076] Example one

[0077] As shown in Figure 1 The present embodiment provides a precise steam parameter control method for steam pipe network, the steam pipe network includes one or more pipeline transportation devices, and the method comprises the following steps:

[0078] S1, for each pipeline transportation device of the steam pipe network, obtaining the historical operation data of the current pipeline transportation device, the historical operation data comprising: transportation source control parameters; user side parameters; the distance between the user side and the transportation starting side;

[0079] S2, according to the historical operation data of each pipeline transportation device, cleaning the historical operation data and screening the key data in the cleaned historical operation data by using the pre-defined screening strategy;

[0080] S3, based on the screened key data, constructing adjustment information for monitoring and adjusting the current data; and obtaining the transportation source adjustment parameters meeting the current pipeline transportation device based on the adjustment information;

[0081] S4, adjusting the transportation source control parameters of the steam pipe network according to the transportation source adjustment parameters of all pipeline transportation devices.

[0082] It should be noted that the transportation source control parameters include: the temperature, pressure and flow of the plant source side; and the user side parameters include: the temperature, pressure and flow of each user side;

[0083] Correspondingly, the S4 specifically comprises:

[0084] The maximum value of the pressure in the delivery source adjustment parameter of each pipeline delivery device is taken as the delivery source adjustment parameter one (i.e. the delivery source pressure adjustment parameter) of the steam pipe network, and the plant source side pressure value of the steam pipe network is adjusted;

[0085] The maximum value of the temperature in the delivery source adjustment parameter of each pipeline delivery device is taken as the delivery source adjustment parameter two (i.e. the delivery source temperature adjustment parameter) of the steam pipe network, and the plant source side temperature value of the steam pipe network is adjusted;

[0086] The delivery source adjustment parameters of all pipeline delivery devices include the delivery source adjustment parameter one and the delivery source adjustment parameter two.

[0087] It should be noted that the historical operation data is usually read from the real-time data of the steam pipe network DCS control system.

[0088] It can be understood that the control method of the present application has two types of adjustment information of steam parameters, i.e. pressure and temperature, and the specific steps of the control method will be described below according to the cases that the adjustment information is pressure and temperature. In order to facilitate understanding, the processing process when the adjustment information is pressure and the processing process when the adjustment information is temperature are provided in the embodiments. Figure 2 and Figure 6 .

[0089] For example, please refer to Figure 1 and Figure 2 When the adjustment information is pressure,

[0090] The S2 can obtain the key data through the following sub-steps:

[0091] S21, at least one key user is obtained through screening by using one or more of the following means:

[0092] According to the distance between the user side and the delivery starting side in the historical operation data, the user with the longest distance is screened;

[0093] According to the user side flow in the historical operation data, the user with the flow exceeding the preset high threshold value and being lower than the preset low threshold value is screened;

[0094] According to the user side pressure and the plant source side pressure in the historical operation data, the user with the largest pressure loss under the same pressure demand is screened;

[0095] S22, data cleaning is performed by using a clustering outlier identification method to obtain the cleaned historical operation data;

[0096] S23, filtering the historical operation data of all users in the key user group as the key data according to the cleaned historical operation data.

[0097] It can be understood that in step S23, the historical operation data of all users in the key user group is filtered, and the purpose is to retain only the historical operation data of the users in the key user group in the filtered key data.

[0098] After obtaining the key data, the S3 is used to obtain a delivery source pressure adjustment parameter meeting the current pipeline delivery device, and specifically includes:

[0099] S31, for each user in the key data, obtaining pressure adjustment information of the user according to user-side pressure and plant source-side pressure and flow of the user;

[0100] S32, selecting a maximum value as the delivery source pressure adjustment parameter meeting the current pipeline delivery device according to the pressure adjustment information of the users in all the key data.

[0101] The S31 includes the following sub-steps S311-S313.

[0102] S311, obtaining user-side pressure drop of the user according to plant source-side pressure of the key data and user-side pressure of the user; the user-side pressure drop is the difference between the plant source-side pressure and the user-side pressure of the user;

[0103] S312, fitting the user-side pressure drop of the user and the plant source-side flow data in a specified time period to obtain the following formula one and formula two,

[0104] formula one;

[0105] formula two;

[0106] wherein ΔP is the user-side pressure drop of the user, P is the plant source-side pressure, P' is the user-side pressure, D is the plant source-side flow, and a, b, and c are constant coefficients obtained by fitting;

[0107] S313, obtaining a plant source-side pressure value meeting the user-side pressure requirement of the user based on formula two and the currently monitored P' and D as the pressure adjustment information of the user.

[0108] For example, referring to Figure 3 and Figure 4 , which are pressure drop fitting curves (corresponding to formula one) of two key users A and B of the embodiment.

[0109] It should be explained that in step S313, only the user-side pressure demand P' of the current user can also be obtained, see Figure 2 P' can be obtained by determining the minimum pressure demand of the current user; and then the function relationship between the source-side pressure P and the flow D is obtained from formula two as the pressure adjustment information of the user corresponding to different flows, for example, the pressure adjustment information of the i-th user is the function P i (D); accordingly, in step S32, the pressure adjustment information of each user is a pressure function with the source-side flow as the variable, and the maximum pressure function can be obtained by taking the maximum value of the pressure functions of all users, where N is the number of key users, as shown in Figure 5 The figure is a pressure maximum function obtained by taking the maximum value of the pressure functions of all key users of one pipeline in the embodiment, as the source pressure adjustment parameter of the pipeline delivery device with the source-side flow as the parameter.

[0110] Through the above processing steps for the adjustment information as pressure, the pressure adjustment information meeting the current pipeline pressure supply demand can be obtained; further, because the pipelines are usually controlled uniformly in the steam pipe network, according to the step S4 of the control method, the maximum value of the pressure adjustment information of each pipeline in the steam pipe network can be obtained, that is, the source-side pressure control parameter of the steam pipe network.

[0111] Further, when the adjustment information is temperature, see Figure 1 and Figure 6 , the S2 can obtain the key data through the following sub-steps:

[0112] The S2 can obtain the key data through the following sub-steps:

[0113] S24, at least one key user group is obtained by screening using one or more of the following means:

[0114] According to the distance between the user side and the delivery starting side in the historical operation data, the users farthest away are screened;

[0115] According to the user-side flow in the historical operation data, the users whose user-side flow exceeds the preset high threshold and is lower than the preset low threshold are screened;

[0116] According to the user-side temperature and the source-side temperature in the historical operation data, the users with the largest temperature loss under the same temperature demand are screened;

[0117] For example, see the example of "selecting key users" in Figure 6 , 1-5 end users farthest away, 1-5 users with the largest flow, etc. can be selected to construct the key user group.

[0118] S25, data cleaning is performed by using a clustering outlier identification method, and data in which the user-side temperature exceeds a preset overheating threshold is removed, to obtain cleaned historical operation data;

[0119] It should be noted that in a specific implementation, when cleaning data with an overheating feature anomaly, the preset overheating threshold can be set to 5 degrees.

[0120] S26, filtering historical operation data of users in all the key user groups as the key data according to the cleaned historical operation data.

[0121] It can be understood that in step S26, the historical operation data of users in all the key user groups is filtered, and the purpose is to retain only the historical operation data of users in the key user groups in the filtered key data.

[0122] After obtaining the key data, the delivery source temperature adjustment parameter that meets the current pipeline delivery device is obtained by S3, and specifically includes:

[0123] S33, for each user in the key data, obtaining temperature adjustment information of the user according to the user-side temperature and the source-side temperature and flow of the user;

[0124] S34, selecting a maximum value as the delivery source temperature adjustment parameter that meets the current pipeline delivery device according to the temperature adjustment information of the users in all the key data.

[0125] In actual application, S33 can include the following sub-steps S331-S334:

[0126] S331, determining a delay time of steam temperature from the source side to the user side by using a time axis translation algorithm or a time delay algorithm based on fast Fourier transform according to the key data;

[0127] S332, aligning and processing the user-side temperature, the source-side flow and the source-side temperature data of the user according to a time axis according to the key data and the delay time, to obtain non-delay key data in which the delay influence of steam temperature from the source side to the user side is eliminated;

[0128] Because there is a relatively obvious delay phenomenon when steam conducts in the pipeline network, the value can reach 1-3 hours, which can cause serious hysteresis of terminal user temperature change. If the source-side temperature, flow and user-side temperature data with the same time stamp are directly used without processing, the analysis result cannot reflect the actual operation condition. Therefore, the delay processing is needed to realize the logical correspondence of the source-side data and the user-side data in temperature analysis.

[0129] Specifically, the embodiment provides two methods for determining the delay time of steam temperature from the plant source side to the user side,

[0130] The first time axis translation algorithm is to constantly translate the entire flow data segment of several periods backward, and constantly analyze the correlation coefficient with the temperature data segment. The time with the highest regression coefficient score is the maximum possible delay time. The analysis result is shown in Figure 8 .

[0131] The second is a time delay algorithm based on fast Fourier transform. The time delay algorithm based on fast Fourier transform is used to traverse the operation history data, and the time delay of each small data segment is calculated. Then, the distribution (histogram) of the obtained time delay is analyzed. The delay time corresponding to the maximum density distribution can be considered as the maximum likelihood delay time, as shown in Figure 9 .

[0132] It should be noted that before the steps of the above delay processing, the time lag cross-correlation method can be used to evaluate the signal dynamics of the plant source data and the key user parameters, such as the influence characteristics of the plant source steam temperature change or flow change on the downstream user temperature, and to find the main correlation factors, as shown in Figure 7 .

[0133] S333, fitting the non-delay key data according to the user side temperature, plant source side flow, and temperature data of the user to obtain formula three and formula four:

[0134] , formula three;

[0135] , formula four;

[0136] Where T' is the user side temperature of the user, T is the plant source side temperature, D is the plant source side flow, d, e, and f are the constant coefficients obtained by fitting;

[0137] As shown in Figure 10 , it is the temperature fitting curve (corresponding to formula three) of a key user in the embodiment.

[0138] S334, based on formula four and the currently monitored T' and D, obtaining the plant source side temperature value corresponding to the user side temperature demand of the user as the temperature adjustment information of the user.

[0139] It should be explained that in step S334, only the user side temperature demand T' of the current user can be obtained, and the function relationship between the plant source side temperature and flow obtained from formula four is used as the temperature adjustment information corresponding to different flows of the user. For example, the temperature adjustment information of the i-th user is the function T i(D); correspondingly, in step S34, the temperature adjustment information of each user is a temperature function with the factory source side flow as a variable, and the maximum temperature function can be obtained by taking the maximum of the temperature functions of all users , where N is the number of key users, as shown in the figure, which is the maximum temperature function obtained by taking the maximum of the temperature functions of all key users of a pipeline, as the delivery source temperature adjustment parameter of the pipeline delivery device with the factory source side flow as a parameter. Figure 11

[0140] It should be noted that, as shown in Figure 6 "using the saturation temperature corresponding to the pressure demand of the key user to calculate the factory source temperature", when the user side temperature demand T' of the user is obtained, the saturation temperature corresponding to the user side pressure value that meets the user can also be based on, and on this basis, an overheat degree of 5-10 degrees is added as the user side temperature demand T' of the user.

[0141] Based on the steps of the above adjustment information control method of temperature type, the time delay of steam temperature conduction to the user side is found through historical operation data, and the optimal supply temperature (i.e. the obtained temperature adjustment information) is calculated based on the time delay, which can not only meet the demand of the user side for steam quality, but also effectively reduce the demand for factory source steam parameters.

[0142] The precise control method of steam pipe network operation parameters based on historical operation data analysis provided in the embodiment can analyze the factory source side pressure and temperature control parameters by combining the current pipeline flow, power plant supply temperature and supply pressure, and temperature and pressure information of terminal consumer users, which has important stable control and economic significance for the operation of the pipe network in thermal power production.

[0143] Embodiment Two

[0144] The embodiment provides a steam pipe network control device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the precise supply steam pipe network steam parameter control method according to any one of the above embodiment one when executing the computer program.

[0145] Embodiment Three

[0146] The embodiment provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program implements the steps of the precise supply steam pipe network steam parameter control method according to any one of the above embodiment one when executed by a processor.

[0147] ​It should be noted that, in the description of the present application, the description of the terms "one embodiment", "some embodiments", "an embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are contained in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0148] Although the preferred embodiments of the present application have been described, those skilled in the art can make further changes and modifications to these embodiments after learning the basic creative concept. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application.

Claims

1. A method for controlling parameters of a steam network with precision feed of steam, characterized by, The steam pipe network comprises one or more pipeline delivery devices, and the method comprises: S1, for each pipeline delivery device of the steam pipe network, obtaining historical operation data of the current pipeline delivery device, the historical operation data comprising: source control parameters; user side parameters; distance between the user side and the delivery starting side; S2, according to the historical operation data of each pipeline delivery device, cleaning the historical operation data and screening key data in the cleaned historical operation data by using a pre-defined screening strategy; S3, based on the screened key data, constructing adjustment information for monitoring and adjusting the current data; and obtaining source adjustment parameters meeting the current pipeline delivery device based on the adjustment information; S4, adjusting the source control parameters of the steam pipe network according to the source adjustment parameters of all pipeline delivery devices; When the adjustment information is pressure, the S2 comprises: S21, screening at least one key user group comprising one or more key users by using one or more of the following means: According to the distance between the user side and the delivery starting side of the historical operation data, screening the user with the farthest distance; According to the user side flow of the historical operation data, screening the user with the flow exceeding the pre-set high threshold and being lower than the pre-set low threshold; According to the user side pressure and the source side pressure of the historical operation data, screening the user with the largest pressure loss under the same pressure demand; S22, using a clustering outlier identification method to clean the data to obtain the cleaned historical operation data; S23, according to the cleaned historical operation data, filtering the historical operation data of all users in the key user group as the key data.

2. The method according to claim 1, wherein: The source control parameters comprise: temperature, pressure and flow of the source side; The user side parameters comprise: temperature, pressure and flow of each user side; Correspondingly, the S4 comprises: Taking the maximum value of the pressure in the source adjustment parameter of each pipeline delivery device in all pipeline delivery devices as the source adjustment parameter one of the steam pipe network, and adjusting the source side pressure value of the steam pipe network; Taking the maximum value of the temperature in the source adjustment parameter of each pipeline delivery device in all pipeline delivery devices as the source adjustment parameter two of the steam pipe network, and adjusting the source side temperature value of the steam pipe network; The source adjustment parameters of all pipeline delivery devices comprise: the source adjustment parameter one and the source adjustment parameter two.

3. The method of claim 1, wherein, When the adjustment information is temperature, the S2 comprises: S24, screening at least one key user group comprising one or more key users by using one or more of the following means: According to the distance between the user side and the delivery starting side of the historical operation data, screening the user with the farthest distance; According to the user side flow of the historical operation data, screening the user with the flow exceeding the pre-set high threshold and being lower than the pre-set low threshold; According to the user side temperature and the source side temperature of the historical operation data, screening the user with the largest temperature loss under the same temperature demand; S25, data cleaning is performed by using a clustering outlier identification method, and data in which a user-side temperature value exceeds a preset overheating threshold is removed, to obtain cleaned historical operation data; S26, according to the cleaned historical operation data, historical operation data of users in all the key user groups is filtered as the key data.

4. The method of claim 1, wherein, When the adjustment information is pressure, the S3 includes: S31, for each user in the key data, user-side pressure and plant-source-side pressure and flow of the user are used to obtain pressure adjustment information of the user; S32, according to pressure adjustment information of users in all the key data, a maximum value is selected as a delivery source pressure adjustment parameter that meets a current pipeline delivery device.

5. The method of claim 4, wherein, The S31 includes: S311, user-side pressure drop of the user is obtained according to plant-source-side pressure of the key data and user-side pressure of the user; the user-side pressure drop is a difference between the plant-source-side pressure and the user-side pressure of the user; S312, user-side pressure drop of the user and plant-source-side flow data in a specified time period are fitted to obtain the following formulas one and two, , Equation One; , Equation Two; wherein ΔP is the user-side pressure drop of the user, P is the plant-source-side pressure, P' is the user-side pressure, D is the plant-source-side flow, a, b, c are constant coefficients obtained by fitting; S313, based on the formula two and currently monitored P' and D, a plant-source-side pressure value that meets user-side pressure demand of the user is obtained as the pressure adjustment information of the user.

6. The method of claim 1, wherein, When the adjustment information is temperature, the S3 includes: S33, for each user in the key data, user-side temperature and plant-source-side temperature and flow of the user are used to obtain temperature adjustment information of the user; S34, according to temperature adjustment information of users in all the key data, a maximum value is selected as a delivery source temperature adjustment parameter that meets a current pipeline delivery device.

7. The method of claim 6, wherein, The S33 includes: S331, according to the key data, a time axis translation algorithm or a time delay algorithm based on fast Fourier transform is used to determine a delay time of steam temperature from the plant-source-side to the user-side; S332, according to the key data and the delay time, user-side temperature, plant-source-side flow and plant-source-side temperature data of the user are time axis translation aligned to obtain non-delay key data in which a delay influence of steam temperature from the plant-source-side to the user-side is eliminated; S333, the non-delay key data is fitted according to user-side temperature, plant-source-side flow and temperature data of the user to obtain the following formulas three and four: Equation Three; , Equation Four; wherein T' is the user-side temperature of the user, T is the plant-source-side temperature, D is the plant-source-side flow, d, e, f are constant coefficients obtained by fitting; S334, based on the formula four and currently monitored T' and D, a plant-source-side temperature value that meets user-side temperature demand of the user is obtained as the temperature adjustment information of the user.

8. A steam network control device, characterized in that The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the precise supply steam pipe network steam parameter control method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the precise supply steam pipe network steam parameter control method according to any one of claims 1 to 7.

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