Characteristic parameter identification and correction method and system for hydraulic online simulation model

Abstract

The invention provides a characteristic parameter identification and correction method and system for a hydraulic online simulation model, and belongs to the technical field of data processing, and the method specifically comprises the steps: determining the combined scheduling processing data of a pipe network with different state changes according to the historical scheduling data of a heat supply pipe network, determining the scheduling influence condition of the heat supply pipe network between the heating stations of the different state change pipe networks in different joint scheduling processing times, determining the correlation coefficients of the different state change pipe networks based on the scheduling influence condition, and determining the state change pipe network based on the correlation coefficients of the different state change pipe networks. According to the method, the association condition of the change pipe network group formed by different state change pipe networks is determined, and the characteristic parameter identification correction method of the hydraulic simulation model is determined based on the association condition, so that the reliability of load scheduling processing is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of parameter identification in operation status analysis and model optimization of a heating pipe network, and particularly relates to a method and system for identifying and correcting characteristic parameters of a hydraulic online simulation model. Background Art

[0002] In the operation and management of heating networks, hydraulic simulation models are core tools for load scheduling and state identification. Existing technologies typically evaluate the operating status of heating systems by constructing hydraulic simulation models and combining them with network monitoring data. For example, in invention patent application CN202411639677.X, "Method, Device, and Medium for Hydraulic Optimization of Heating Pipe Networks," model parameter optimization is achieved by matching historical data with real-time monitoring data. CN202411260710.8, "Initial Parameter Generation Method Based on NUMAP Steady-State Calculation," utilizes steady-state calculations to generate initial parameters to improve model accuracy.

[0003] As heating networks operate longer, factors like scaling on pipe walls and valve aging can cause dynamic changes in parameters like the network's resistance coefficient and flow distribution. Existing hydraulic simulation model parameter update strategies often rely on periodic manual calibration or fixed threshold triggers, failing to respond to subtle changes in network status in real time. This results in a decrease in model prediction accuracy over time.

[0004] Existing solutions lack systematic verification of the distribution density of monitoring devices and the validity of data. For example, when monitoring devices are sparsely deployed or malfunction, abnormal data can directly affect the identification of model parameters. However, existing technologies lack a bias filtering mechanism based on the distribution of monitoring devices, resulting in errors in parameter correction results.

[0005] The state changes in different areas of the heating pipeline network often have a coupled relationship (for example, flow adjustment in a certain area will affect the pressure distribution of the adjacent pipeline network). However, existing technologies often divide the pipeline network into independent units for parameter correction, without considering the impact of joint scheduling between state-changing pipeline networks. As a result, the model cannot accurately reflect the actual operating status of the complex pipeline network.

[0006] To address the above issues, how to build a parameter correction method based on real-time monitoring data and historical scheduling data that can dynamically identify changes in pipeline network status, filter monitoring deviations, and quantify the impact of pipeline network correlation has become the key to improving the reliability of hydraulic simulation models. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to overcome the shortcomings of the hydraulic simulation model in the above-mentioned prior art, such as untimely parameter correction and low accuracy due to changes in pipeline network status, monitoring deviations and lack of correlation analysis, and to provide a method and system for identifying and correcting characteristic parameters of a hydraulic online simulation model. The method aims to accurately identify pipelines with changing status and quantify correlation coefficients between pipelines by dynamically analyzing the operating data of the heating pipeline network and the reliability of the monitoring device, and combine the distribution density verification of the monitoring device with the adaptive correction decision mechanism to achieve accurate identification and dynamic correction of the characteristic parameters of the hydraulic online simulation model, so as to improve the adaptability of the model to dynamic changes in the pipeline network, ensure data reliability, quantify correlation influences and optimize correction decisions, thereby improving the intelligence and reliability of load scheduling processing of the heating pipeline network.

[0008] To achieve the above objectives, the present invention provides, in a first aspect, a method for identifying and correcting characteristic parameters of a hydraulic online simulation model, comprising: Determine the state-changed pipe network in the heating pipe network based on the changes in monitoring data and original data of different heating pipe networks during the scheduling operation process; Determining the types and installation locations of the monitoring devices of the different state-changing pipe networks based on the distribution data of the monitoring devices of the different state-changing pipe networks, and proceeding to the next step when it is determined that no monitoring deviation pipe network exists in the state-changing pipe network based on the types and installation locations of the monitoring devices of the different state-changing pipe networks; Determining joint dispatch processing data for different state-changing pipe networks using historical dispatch data of the heating pipe network, determining dispatch impacts of the heating pipe network between thermal power stations of different state-changing pipe networks at different joint dispatch processing times, and determining correlation coefficients for the different state-changing pipe networks based on the dispatch impacts; Based on the correlation coefficients of different state-changing pipe networks, the correlation of the variable pipe network groups composed of different state-changing pipe networks is determined, and based on the correlation, a characteristic parameter identification and correction method of the hydraulic simulation model is determined.

[0009] Furthermore, the original data is the operating data of the heating network corresponding to the update of the characteristic parameters of the hydraulic simulation model.

[0010] Furthermore, the method for determining the state-changing pipe network in the heating pipe network is: Determining the deviation between the identification result of the hydraulic simulation model of the heating pipe network and the original data at different heating flow rates based on the changes in the monitoring data and the original data during the scheduling operation of the heating pipe network; Determining a variable heating pipeline at different heating flow rates based on the deviation; Whether the heating pipe network is a state-changing pipe network is determined based on the variable heating pipes under different heating flow rates.

[0011] Further, the variable heat supply pipeline is a heat supply pipeline in the heat supply pipeline network, a deviation amount of a recognition result of the hydraulic simulation model under the heat supply flow and original data is greater than a preset data deviation amount.

[0012] Further, when the state variable pipeline network does not exist in the heat supply pipeline network, the characteristic parameter identification correction processing of the hydraulic simulation model is not required.

[0013] Further, the variable pipeline network group is constructed by freely combining different state variable pipeline networks.

[0014] Further, the method for determining the characteristic parameter identification correction method of the hydraulic simulation model is: determining an average value of the correlation coefficients between the state variable pipeline networks of different variable pipeline network groups according to the correlation conditions of different state pipeline network groups; based on the average value of the correlation coefficients, regarding the variable pipeline network group with the average value of the correlation coefficients greater than a preset correlation coefficient threshold as a correlation pipeline network group; determining the characteristic parameter identification correction method of the hydraulic simulation model according to the number of the correlation pipeline network groups.

[0015] Further, the method for determining the characteristic parameter identification correction method of the hydraulic simulation model according to the number of the correlation pipeline network groups, specifically includes: when the number of the correlation pipeline network groups is greater than a preset correlation pipeline network group number threshold, it is determined that the characteristic parameter identification correction processing of the hydraulic simulation model is required; when the number of the correlation pipeline network groups is not greater than the preset correlation pipeline network group number threshold, it is determined that the characteristic parameter identification correction processing of the hydraulic simulation model is not required.

[0016] The second aspect of the present application provides a characteristic parameter identification correction system of a hydraulic online simulation model, which is used to execute the characteristic parameter identification correction method of the hydraulic online simulation model, and includes: a pipeline network division module, used for dividing the heat supply pipeline network into different heat supply pipeline networks; a state identification module, used for determining the state variable pipeline network based on the variable conditions of the monitoring data and the original data; a monitoring verification module, used for determining whether the monitoring deviation pipeline network exists in the state variable pipeline network based on the monitoring device distribution data; a correlation analysis module, used for calculating the joint scheduling influence times of different state variable pipeline networks based on the historical scheduling data, determining the correlation coefficients according to the influence times proportion, and constructing the variable pipeline network group through the correlation coefficients; The parameter correction module is used to determine the characteristic parameter identification and correction method of the hydraulic simulation model based on the correlation of the variable pipe network group.

[0017] The present invention adopts the above technical solution, which has at least the following beneficial effects: Based on the types and installation locations of monitoring devices of different state-changing pipeline networks, it is determined whether there is a monitoring deviation pipeline network in the state-changing pipeline network, thereby realizing the determination of the monitoring reliability of the state-changing pipeline network from the setting data of the monitoring device. It also lays the foundation for generating a differentiated identification and correction method of the characteristic parameters of the hydraulic simulation model according to the differences in the monitoring reliability of the state-changing pipeline network, ensuring the reliability of the identification of the operating status of the heating pipeline network during the operation and scheduling process.

[0018] The characteristic parameter identification and correction method of the hydraulic simulation model is determined based on the correlation between the variable pipe network groups composed of different state-changing pipe networks, fully considering the correlation between the state-changing pipe networks due to the overlap of the heating pipe networks, and then considering the mutual influence between the different state-changing pipe networks during the load scheduling process due to the differences in the correlation, thereby realizing the determination of the characteristic parameter identification and correction method of the hydraulic simulation model from the perspective of load scheduling needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 It is a flow chart of a characteristic parameter identification and correction method of a hydraulic online simulation model; Figure 2 It is a flow chart of a method for determining a state-changing network in a heating network; Figure 3 is a flow chart of a method for determining that a monitoring deviation network does not exist in a state-changing network; Figure 4 It is a flow chart of a method for determining a characteristic parameter identification and correction method of a hydraulic simulation model. DETAILED DESCRIPTION

[0021] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many ways and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the figures represent like or similar structures, and thus their detailed description will be omitted.

[0022] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0023] In this application, based on the monitoring reliability of the monitoring device in the state-changing pipeline network and the correlation between different state-changing pipeline networks, a differentiated characteristic parameter identification and correction method of the hydraulic online simulation model is determined, thereby improving the timeliness of the update processing of the characteristic parameters of the hydraulic online simulation model of the heating pipeline network.

[0024] Example 1 To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a method for identifying and correcting characteristic parameters of a hydraulic online simulation model is provided, which specifically includes: S1 determines the state-changed pipe network in the heating pipe network based on the changes in the monitoring data and original data of different heating pipe networks during the scheduling operation process; Furthermore, the original data is the operating data of the heating network corresponding to the update of the characteristic parameters of the hydraulic simulation model.

[0025] It should be noted that if Figure 2 As shown, the method for determining the state-changing pipe network in the heating pipe network is: Determining the deviation between the identification result of the hydraulic simulation model of the heating pipe network and the original data at different heating flow rates based on the changes in the monitoring data and the original data during the scheduling operation of the heating pipe network; Determining a variable heating pipeline at different heating flow rates based on the deviation; Whether the heating pipe network is a state-changing pipe network is determined based on the variable heating pipes under different heating flow rates.

[0026] Furthermore, the variable heating pipeline is a heating pipeline in the heating network in which the deviation between the identification result of the hydraulic simulation model under the heating flow rate and the original data is greater than the preset data deviation.

[0027] It can be understood that when there is a heating flow rate where the number of variable heating pipes is greater than a preset threshold value for the number of variable pipes, the heating pipe network is determined to be a state-variable pipe network.

[0028] It should be noted that when there is no state-changing pipe network in the heating pipe network, there is no need to perform characteristic parameter identification and correction processing of the hydraulic simulation model.

[0029] In another possible embodiment, the method for determining the state-changing pipe network in the heating pipe network is: S11 determines the deviation between the identification result of the hydraulic simulation model of the heating pipe network and the original data at different heating flow rates based on the changes in the monitoring data and the original data during the scheduling operation of the heating pipe network, determines the changed heating pipes at different heating flow rates based on the deviation, and determines the data deviation coefficient at different heating flow rates based on the number of changed heating pipes at different heating flow rates; S12 determines distribution data of the variable heating pipes under different heating flow rates for different heating pipes, and determines identification anomaly coefficients of the different heating pipes based on the distribution data of the variable heating pipes under different heating flow rates; S13 determines the pipe network monitoring anomaly coefficient of the heating pipe network according to the data deviation coefficient under different heating flow rates and the identification anomaly coefficient of different heating pipes, and determines whether the heating pipe network is a state-changing pipe network based on the pipe network monitoring anomaly coefficient.

[0030] It should be further explained that the input and output quantities of the above-mentioned data deviation coefficient, identification anomaly coefficient and pipeline network monitoring anomaly coefficient are determined and can be determined using the mathematical model of hierarchical analysis method, expert scoring or neural network model.

[0031] Specifically, before entering step S12, it is necessary to further determine whether there are variable heating pipes, whether the number of variable heating pipes under different heating flow rates meets the requirements, and whether the mean of the data deviation coefficient under different heating flow rates meets the requirements.

[0032] Specifically, when there are no variable heating pipes, it can be directly determined that the heating pipe network does not belong to a state-changing pipe network. If and only if there are variable heating pipes, it is necessary to further determine whether the number of variable heating pipes under different heating flow rates meets the requirements. When there are heating flows with a number of variable heating pipes greater than a preset variable pipe number threshold, the heating pipe network is determined to be a state-changing pipe network.

[0033] Even if the number of variable heating pipes under different heating flow rates meets the requirements, if the mean of the data deviation coefficients under different heating flow rates is greater than a certain threshold, the heating network can still be directly determined as a state-changing network. Only when the above conditions are met will step S12 be entered.

[0034] It should be further explained that before entering step S13, it is necessary to further determine whether there are heating pipes whose number of variable heating pipes does not meet the requirements under different heating flow rates and whether the number of variable heating pipes with large identification abnormality coefficients meets the requirements. The specific judgment of whether the requirements are met can be determined by means of a threshold.

[0035] It can be understood that when there are heating pipes whose number is greater than a certain threshold value under different heating flow rates, the heating network is directly determined to be a state-changing network. Even if there are no heating pipes whose number is greater than a certain threshold value under different heating flow rates, if there is a large identification abnormality coefficient, that is, the number of changing heating pipes within the preset interval is greater than a certain threshold value, it can still be identified as a state-changing network.

[0036] In addition, only when there are no heating pipes whose number of variable heating pipes does not meet the requirements under different heating flow rates and the number of variable heating pipes with large identification abnormality coefficients meets the requirements, the process proceeds to step S13.

[0037] S2 determines the types and installation locations of the monitoring devices of the different state-changing pipe networks based on the distribution data of the monitoring devices of the different state-changing pipe networks. If it is determined based on the types and installation locations of the monitoring devices of the different state-changing pipe networks that there is no monitoring deviation pipe network in the state-changing pipe network, proceeds to the next step. Specifically, such as Figure 3 As shown, determining that there is no monitoring deviation pipeline network in the state-changing pipeline network specifically includes: Determining the number of monitoring devices to be installed in different heating pipelines in the state-changing pipe network based on the types and installation locations of the monitoring devices in different state-changing pipe networks; Determine the density of monitoring devices installed in different heating pipelines according to the ratio of the number of monitoring devices installed in different heating pipelines to the length of the heating pipelines; The heating pipelines whose monitoring device setting density is less than a preset setting density threshold are regarded as monitoring deviation pipelines, and whether the state-changing pipeline network belongs to the monitoring deviation pipeline network is determined based on the number of the monitoring deviation pipelines.

[0038] Further, when the number of the state variation pipe networks monitored is greater than a preset threshold of the number of the state variation pipe networks monitored, it is determined that the state variation pipe network belongs to the state variation pipe network monitored.

[0039] It should be noted that when the state variation pipe network data domain belongs to the state variation pipe network monitored, it is determined that the feature parameter identification correction processing of the hydraulic simulation model needs to be performed.

[0040] S3 determines the joint scheduling processing data of different state variation pipe networks based on the historical scheduling data of the heating pipe network, determines the scheduling influence of the heating pipe network between the heat stations of different state variation pipe networks in different joint scheduling processing times, and determines the correlation coefficient of different state variation pipe networks based on the scheduling influence. Specifically, the scheduling influence of the heating pipe network includes the heating pipe networks that have an influence on the heating flow when the heating pipe networks are scheduled.

[0041] Specifically, the method for determining the correlation coefficient of the state variation pipe network is: Based on the scheduling influence, the scheduling processing times in which the heating flow of the heat exchange station of different state variation pipe networks has an influence when the heat exchange station is scheduled are determined, and the scheduling processing times are taken as the correlation scheduling processing times. According to the proportion of the correlation scheduling processing times in the historical scheduling processing times in the heating pipe network, the correlation coefficient between different state variation pipe networks is determined.

[0042] S4 determines the correlation of the variation pipe network group composed of different state variation pipe networks based on the correlation coefficient of different state variation pipe networks, and determines the feature parameter identification correction method of the hydraulic simulation model based on the correlation.

[0043] Further, the variation pipe network group is constructed by freely combining different state variation pipe networks.

[0044] Specifically, as shown in Figure 4 The method for determining the feature parameter identification correction method of the hydraulic simulation model is: Based on the correlation of different state pipe network groups, the average value of the correlation coefficient between the state variation pipe networks of different variation pipe network groups is determined. Based on the average value of the correlation coefficient, the variation pipe network group with an average value of the correlation coefficient greater than a preset correlation coefficient threshold is taken as the correlation pipe network group. According to the number of the correlation pipe network group, the feature parameter identification correction method of the hydraulic simulation model is determined.

[0045] Further, according to the number of the correlation pipe network group, the feature parameter identification correction method of the hydraulic simulation model is determined, specifically including: When the number of the associated pipe network groups is greater than a preset threshold number of associated pipe network groups, it is determined that identification and correction processing of characteristic parameters of the hydraulic simulation model is required; When the number of the associated pipe network groups is not greater than a preset threshold value of the number of associated pipe network groups, it is determined that there is no need to perform identification and correction processing on the characteristic parameters of the hydraulic simulation model.

[0046] In another possible embodiment, the method for determining the characteristic parameter identification and correction method of the hydraulic simulation model is: S41 determines the average value of correlation coefficients between state-changing pipe networks of different change pipe network groups based on the correlation conditions of the pipe network groups in different states, and based on the average value of the correlation coefficients, selects the change pipe network groups whose average value of the correlation coefficients is greater than a preset correlation coefficient threshold as the associated pipe network groups; S42 determines the change correlation coefficients of different associated pipe network groups based on the correlation coefficients between different state-changing pipe networks in different associated pipe network groups and the number of state-changing pipe networks in the associated pipe network groups; S43 determines the scheduling influence coefficient of the state-changing pipeline network according to the change correlation coefficients of different associated pipeline network groups, and determines the characteristic parameter identification and correction method of the hydraulic simulation model based on the scheduling influence coefficient.

[0047] Optionally, before entering step S42, it is also necessary to determine whether there are associated pipe network groups, whether the number of associated pipe network groups meets the requirement, and whether the number of state-changed pipe networks in different associated pipe network groups meets the requirement.

[0048] Specifically, when there are no associated pipe network groups, it is directly determined that there is no need to perform characteristic parameter identification and correction processing of the hydraulic simulation model. When there are associated pipe network groups, it is necessary to further determine whether the number of associated pipe network groups is too large. Specifically, when the number of associated pipe network groups is greater than a certain threshold, it means that during the scheduling process, since the operating status of the state-changing pipe network cannot be determined, it is necessary to perform characteristic parameter identification and correction processing of the hydraulic simulation model.

[0049] Even if the number of associated pipe network groups is small, it is still necessary to further determine whether there are associated pipe network groups with a large number of state-changing pipe networks. Specifically, for associated pipe network groups with a number of state-changing pipe networks greater than a fixed threshold, the accuracy of the entire scheduling process is more affected during scheduling. Therefore, it is necessary to identify and correct the characteristic parameters of the hydraulic simulation model.

[0050] If and only if there is no associated pipe network group in which the number of pipe networks with changed states is greater than a fixed threshold, the process proceeds to step S42 .

[0051] It is understandable that before entering step S43, it is necessary to further determine whether there are associated pipe network groups whose change correlation coefficients do not meet the requirements and whether the number of associated pipe network groups with large change correlation coefficients meets the requirements. Only when the above conditions are met will step S43 be entered. In addition, the change correlation coefficient and the scheduling influence coefficient can be constructed using the hierarchical analysis method or the trained neural network model.

[0052] Specifically, when there is an associated pipe network group whose variable correlation coefficient does not meet the requirements, that is, when there is an associated pipe network group whose variable correlation coefficient is greater than a certain threshold, it is directly determined that the characteristic parameters of the hydraulic simulation model need to be identified and corrected. When there is no associated pipe network group whose variable correlation coefficient does not meet the requirements, it is necessary to further determine whether the number of associated pipe network groups with relatively large variable correlation coefficients meets the requirements. Specifically, it can be determined whether the number of associated pipe network groups with variable correlation coefficients within the preset variable correlation coefficient range is greater than a fixed threshold. When the number of associated pipe network groups with relatively large variable correlation coefficients does not meet the requirements, it is directly determined that the characteristic parameters of the hydraulic simulation model need to be identified and corrected.

[0053] Example 2 This embodiment provides a characteristic parameter identification and correction system for a hydraulic online simulation model. The system is used to execute the characteristic parameter identification and correction method for the hydraulic online simulation model, including: The pipe network division module is used to divide the heating pipe network into different heating pipe networks; based on the thermal power station, the corresponding heating pipe network is divided into independent sub-pipeline network units. The division results form the heating pipe network topology structure data for subsequent state change analysis.

[0054] The state identification module is used to determine the state-changing pipeline network based on the changes in the monitoring data and the original data; obtain the monitoring data and original data of the heating pipeline network during scheduling operation (the operating data when the characteristic parameters of the hydraulic simulation model are updated), and by analyzing the changes in the two, determine the deviation between the hydraulic simulation model identification results and the original data under different heating flow rates, and then identify the changing heating pipelines and the state-changing pipeline network.

[0055] The monitoring verification module is used to determine whether there is a monitoring deviation pipeline network in the state-changing pipeline network based on the monitoring device distribution data; based on the monitoring device distribution data (type and setting location) of the state-changing pipeline network, calculate the monitoring device setting density, mark the heating pipelines with a density less than a preset threshold as monitoring deviation pipelines, and judge whether the state-changing pipeline network belongs to the monitoring deviation pipeline network based on the number of monitoring deviation pipelines.

[0056] The correlation analysis module calculates the impact of joint dispatch for networks with different state changes based on historical dispatch data, determines the correlation coefficient based on the percentage of impacts, and constructs groups of networks with different state changes using this correlation coefficient. It also extracts joint dispatch processing data for networks with different state changes from historical heating network dispatch data, analyzes the impact of each state-changing network on heating network dispatch between heating stations, and determines the correlation coefficient based on the proportion of the number of associated dispatch processing times to the total number of historical dispatches. Based on the correlation coefficient, networks with different state changes are freely combined to form groups of networks with different state changes, and the correlation between these groups is analyzed.

[0057] The parameter correction module determines the identification and correction method for the hydraulic simulation model's characteristic parameters based on the association of the changed pipe network groups. The module calculates the average correlation coefficient of the changed pipe network groups and identifies the groups with an average value greater than a preset threshold as the associated pipe network groups. The module then determines whether to trigger the identification and correction of the hydraulic simulation model's characteristic parameters based on the number of associated pipe network groups. (If the number of associated pipe network groups exceeds the preset threshold, the correction is executed; otherwise, no correction is performed.)

[0058] The pipe network division module outputs the sub-pipe network division results to the state identification module; after the state identification module determines the state-changed pipe network, it transmits the data to the monitoring and verification module; after the monitoring and verification module completes the reliability verification, the qualified data enters the correlation analysis module; the correlation analysis module generates the correlation coefficient and the correlation status of the changed pipe network group, and transmits it to the parameter correction module; the parameter correction module performs characteristic parameter identification and correction based on the correlation status, and feeds back to the hydraulic simulation model.

[0059] Example 3

[0060] On the other hand, an embodiment of the present application provides a computer system having a computer program stored thereon. When the computer program is executed in a computer, the computer is caused to execute the above-mentioned method for identifying and correcting characteristic parameters of a hydraulic online simulation model.

[0061] Example 4

[0062] On the other hand, a computer program product is provided in an embodiment of the present application, characterized in that the computer program product stores instructions, and when the instructions are executed by a computer, the computer implements the above-mentioned characteristic parameter identification and correction method of a hydraulic online simulation model.

[0063] With the above-described preferred embodiments of the present invention as a guide, and with reference to the above description, relevant personnel are fully capable of making various changes and modifications without departing from the technical scope of this invention. The technical scope of this invention is not limited to the contents of the specification and must be determined according to the scope of the claims.

Claims

1. A method for identifying and correcting characteristic parameters of a hydraulic online simulation model, characterized in that: include: Determine the state-changed pipe network in the heating pipe network based on the changes in monitoring data and original data of different heating pipe networks during the scheduling operation process; Determining the types and installation locations of the monitoring devices of the different state-changing pipe networks based on the distribution data of the monitoring devices of the different state-changing pipe networks, and proceeding to the next step when it is determined that no monitoring deviation pipe network exists in the state-changing pipe network based on the types and installation locations of the monitoring devices of the different state-changing pipe networks; Determining joint dispatch processing data for different state-changing pipe networks using historical dispatch data of the heating pipe network, determining dispatch impacts of the heating pipe network between thermal power stations of different state-changing pipe networks at different joint dispatch processing times, and determining correlation coefficients for the different state-changing pipe networks based on the dispatch impacts; Based on the correlation coefficients of different state-changing pipe networks, the correlation of the variable pipe network groups composed of different state-changing pipe networks is determined, and based on the correlation, a characteristic parameter identification and correction method of the hydraulic simulation model is determined.

2. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 1, characterized in that: The original data is the operating data of the heating network corresponding to when the characteristic parameters of the hydraulic simulation model are updated.

3. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 1 is characterized in that: The method for determining the state-changing pipe network in the heating pipe network is: Determining the deviation between the identification result of the hydraulic simulation model of the heating pipe network and the original data at different heating flow rates based on the changes in the monitoring data and the original data during the scheduling operation of the heating pipe network; Determining a variable heating pipeline at different heating flow rates based on the deviation; Whether the heating pipe network is a state-changing pipe network is determined based on the variable heating pipes under different heating flow rates.

4. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 3 is characterized in that: The variable heating pipeline is a heating pipeline in the heating network where the deviation between the identification result of the hydraulic simulation model under the heating flow rate and the original data is greater than the preset data deviation.

5. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 1 is characterized in that: When there is no state-changing pipe network in the heating pipe network, there is no need to perform characteristic parameter identification and correction processing of the hydraulic simulation model.

6. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 1, characterized in that: The variable pipe network group is constructed by freely combining pipe networks with different state changes.

7. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 1 is characterized in that: The method for determining the characteristic parameter identification and correction method of the hydraulic simulation model is: Determine the average value of the correlation coefficients between the state-changing pipe networks of different change pipe network groups based on the correlation conditions of the pipe network groups in different states; Based on the average value of the correlation coefficient, the variable pipe network group whose average value of the correlation coefficient is greater than a preset correlation coefficient threshold is taken as the associated pipe network group; A characteristic parameter identification and correction method of the hydraulic simulation model is determined according to the number of the associated pipe network groups.

8. The characteristic parameter identification and correction method of the hydraulic online simulation model according to claim 7, characterized in that: Determining a method for identifying and correcting characteristic parameters of the hydraulic simulation model based on the number of associated pipe network groups specifically includes: When the number of the associated pipe network groups is greater than a preset threshold number of associated pipe network groups, it is determined that identification and correction processing of characteristic parameters of the hydraulic simulation model is required; When the number of the associated pipe network groups is not greater than a preset threshold value of the number of associated pipe network groups, it is determined that there is no need to perform identification and correction processing on the characteristic parameters of the hydraulic simulation model.

9. A characteristic parameter identification and correction system for a hydraulic online simulation model, characterized in that: The system is used to execute the characteristic parameter identification and correction method of the hydraulic online simulation model according to any one of claims 1 to 8, comprising: The pipe network division module is used to divide the heating pipe network into different heating pipe networks; A state identification module is used to determine the state-changed pipe network based on the changes between the monitoring data and the original data; A monitoring verification module is used to determine whether there is a monitoring deviation pipeline network in the state change pipeline network based on the distribution data of the monitoring device; The correlation analysis module is used to calculate the number of joint scheduling impacts of pipeline networks with different status changes based on historical scheduling data, determine the correlation coefficient based on the proportion of the impact times, and construct the changed pipeline network group based on the correlation coefficient; The parameter correction module is used to determine the characteristic parameter identification and correction method of the hydraulic simulation model based on the correlation of the variable pipe network group.

Images