A method for testing and adjusting flow characteristics of a high-pressure regulating valve of a steam turbine and a medium

Abstract

The application discloses a kind of on-line test and adjustment method and medium for flow characteristics of high-pressure regulating valve of steam turbine, belongs to the field of steam turbine control technology, comprising: screening working condition data set according to preset working condition reference point, and searching effective steady-state sample set, actual flow characteristic curve is obtained based on actual flow value fitting this time;Repeat the following steps until the deviation is less than the preset threshold: generate this time correction parameter based on the deviation between actual flow characteristic curve and preset flow characteristic curve and download to steam turbine control system;Actual flow value is recalculated with measured operation data;The deviation between actual flow value and this flow characteristic curve is calculated, and if greater than or equal to the preset threshold, then generate next correction parameter according to the deviation and download to steam turbine control system again.The application solves the problem that the existing method needs offline test, and the data screening efficiency is low, the classification is rough, there is no closed-loop iteration verification, and the closed-loop adjustment cannot be completed on-line.

Description

Technical Field

[0001] This invention relates to a method and medium for online testing and adjustment of the flow characteristics of a high-pressure regulating valve in a steam turbine, belonging to the field of steam turbine control technology. Background Technology

[0002] Discrepancies between the flow characteristics of the turbine's high-pressure regulating valve and its design specifications can lead to malfunctions such as unit load fluctuations, unqualified primary frequency regulation, poor quality of automatic power generation control, and oscillations in the regulating system. After a new unit is put into operation, after turbine A-level overhaul or turbine flow path modification, after regulating valve disassembly and repair, or after changes in the high-pressure regulating valve sequence or DEH modification, it is typically necessary to conduct flow characteristic testing and optimization adjustments of the turbine's high-pressure regulating valve. The purpose is to ensure that the actual flow characteristics of the turbine's high-pressure regulating valve match the set flow characteristics to meet the requirements of primary frequency regulation and automatic power generation control.

[0003] Traditional methods for adjusting the flow characteristics of steam turbines require specialized offline flow characteristic tests. Before the test, the AGC and primary frequency control of the DEH system must be deactivated, and a dedicated load dispatch must be requested. The high-pressure regulating valves are forced to operate according to specified rules, pausing at a fixed load point and recording data. Finally, the correction curve is determined based on the test data. This method has strict requirements on the range of main steam parameter variations, the rate of load change, and the dwell time at the load point. The test process is complex to control, parameter adjustment is difficult, and the unit is disconnected from the grid's automatic regulation during the test, affecting normal unit operation. Therefore, it is difficult to conduct these tests frequently as needed. In recent years, analysis methods based on historical operating data have emerged, but existing methods still have the following shortcomings: First, data screening uses fixed steady-state criteria and sampling points, directly discarding data from load points that do not meet the conditions, resulting in low sample utilization. Second, operating condition classification uses isolated data points for throttling / nozzle binary classification, failing to reflect the dynamic switching characteristics of valve regulation modes during load changes. Third, the correction parameters are generated and then downloaded only once, lacking a closed-loop verification and continuous optimization mechanism for the correction effect, and cannot complete closed-loop iterative tuning online under normal unit operation. Summary of the Invention

[0004] The purpose of this invention is to provide a method and medium for online testing and adjustment of the flow characteristics of a high-pressure regulating valve in a steam turbine. This method involves acquiring historical operating data under normal operating conditions of the steam turbine; classifying the data according to the distribution characteristics of the regulating valve command signals; dividing the data into regulating mode sub-segments based on variable load process segments; dynamically searching for effective steady-state samples in adjacent operating condition intervals with a preset operating condition reference point as the center and a set step size; and iterating through the measured data after correcting parameters and downloading the data, with the iterative loop terminating when the deviation is less than a preset threshold. This addresses the problems of existing methods requiring offline testing, low data screening efficiency, coarse classification, lack of closed-loop iterative verification, and inability to complete closed-loop tuning online.

[0005] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides a method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine, comprising:

[0007] Acquire historical operating data of the steam turbine under normal operating conditions;

[0008] The data is classified according to the distribution characteristics of the command signals of each control valve in the historical operation data to obtain the operating condition dataset under different valve control methods;

[0009] Based on the preset operating condition benchmark, the operating condition dataset is filtered using the fluctuation threshold of the operating parameters as the steady-state criterion, and the dataset is searched in the adjacent operating condition intervals with the preset operating condition benchmark as the center and a set step size is used to obtain the effective steady-state sample set under each operating condition benchmark.

[0010] The actual flow rate values ​​at each operating condition reference point are calculated based on the effective steady-state sample set, and the actual flow rate characteristic curve is obtained by fitting the curve.

[0011] Repeat the following steps until the deviation is less than a preset threshold:

[0012] The correction parameters are generated based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and then downloaded to the turbine control system.

[0013] The actual flow rate value was recalculated based on the measured operating data after being installed in the turbine control system.

[0014] Calculate the deviation between the actual flow rate value and the output value corresponding to the current flow rate characteristic curve under the same operating condition. If the deviation is greater than or equal to a preset threshold, generate the next correction parameter based on the deviation and download it to the turbine control system again.

[0015] Furthermore, the historical operating data of the turbine under normal operating conditions includes at least the command signals of each regulating valve, the overall valve position command, the unit load, the main steam pressure, the main steam temperature, the regulating stage pressure, and the regulating stage temperature.

[0016] Furthermore, the step of classifying the data based on the distribution characteristics of the command signals of each regulating valve in the historical operating data to obtain operating condition datasets under different valve regulation modes includes:

[0017] Starting with the load change rate of the unit being greater than a preset change rate threshold, and ending with the load change rate being less than the preset change rate threshold, continuous load change process segments are extracted from the historical operating data.

[0018] Within each variable load process segment, the distribution characteristics of each control valve command signal are calculated in chronological order. The time points when the distribution characteristics of the control valve command signals change abruptly are identified, and the variable load process segment is divided into multiple control mode sub-segments using the abrupt change time points as boundaries.

[0019] Based on the distribution characteristics of the control valve command signals within each sub-segment, the valve control mode of each sub-segment is determined and assigned to the corresponding operating condition dataset, thus obtaining the operating condition dataset under different valve control modes.

[0020] Furthermore, based on a preset operating condition benchmark point, the operating condition dataset is filtered using the fluctuation threshold of the operating parameters as the steady-state criterion. Then, using the preset operating condition benchmark point as the center, a search is performed in adjacent operating condition intervals at a set step size to obtain an effective steady-state sample set under each operating condition benchmark point, including:

[0021] Multiple preset operating condition reference points are determined at set percentage intervals based on the rated load;

[0022] Each preset working condition reference point is used as the center, and the search is performed in the adjacent working condition range with a set step size;

[0023] Within each searched operating condition interval, the data within the operating condition interval is determined to be valid steady-state data, provided that the fluctuation amplitude of the operating parameters within the preset time window is less than their respective fluctuation thresholds.

[0024] If valid steady-state data is found at the current preset operating condition reference point, the search for the current preset operating condition reference point is stopped and the valid steady-state data is saved as the valid steady-state sample corresponding to the current preset operating condition reference point.

[0025] If no valid steady-state data is found at the current preset operating condition reference point, the set step size is increased and the search is repeated until valid steady-state data is obtained.

[0026] By summarizing the effective steady-state samples corresponding to each preset operating condition reference point, the effective steady-state sample set under each operating condition reference point is obtained.

[0027] Furthermore, based on the effective steady-state sample set, the actual flow rate values ​​at each operating condition reference point are calculated, and the actual flow rate characteristic curve for this operation is fitted, including:

[0028] Based on the regulating stage pressure in the effective steady-state sample set and the steam specific volume obtained from the regulating stage pressure and temperature, the actual relative flow rate value under each operating condition reference point is calculated using the relative flow rate calculation formula.

[0029] Using the load and the corresponding actual relative flow rate at each operating condition reference point as data points, a load-actual flow rate curve is obtained by fitting, which serves as the actual flow rate characteristic curve for this application.

[0030] Furthermore, the relative flow rate calculation formula is expressed as:

[0031] ;

[0032] In the formula, This indicates the relative main steam flow rate under varying load conditions. This indicates the relative main steam flow rate under rated load conditions. This indicates the absolute pressure of the regulating stage under varying load conditions. This indicates the absolute pressure of the regulating stage under rated load conditions. This indicates the specific volume of steam after the regulating stage under rated load conditions. This indicates the specific volume of steam after the regulating stage under varying load conditions.

[0033] Furthermore, the correction parameters are generated based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, including:

[0034] Calculate the deviation between the actual flow characteristic curve and the preset flow characteristic curve at each operating condition reference point, and construct a deviation sequence according to the load from low to high.

[0035] Perform a difference operation on the deviation sequence to identify abrupt intervals in the deviation sequence where the rate of change of deviation between adjacent working condition reference points exceeds a preset rate of change threshold;

[0036] The entire operating condition reference point is divided into multiple correction segments using the abrupt change interval as the boundary. Within each correction segment, the statistical characteristic value of the deviation of each operating condition reference point is calculated. The statistical characteristic value is used as the correction basis for the correction segment to generate the corresponding comprehensive valve position command correction value. The correction parameters for this correction are composed of each correction segment and its corresponding comprehensive valve position command correction value.

[0037] Furthermore, the actual flow rate value is recalculated using the measured operating data after being installed in the turbine control system, including:

[0038] The measured operating data after being installed in the turbine control system is used as input, and multiple sets of measured operating data are continuously collected within the preset interval of each operating condition reference point with the preset time window length as the sliding step.

[0039] Using the measured operating data of each group as input, the regulating stage pressure and the steam specific volume obtained from the regulating stage pressure and temperature are extracted. The measured relative flow rate values ​​of each group are then converted using the relative flow rate calculation formula to form a measured flow rate time series.

[0040] Calculate the sliding window variance of the measured flow rate time series;

[0041] If the variance of the sliding window is less than a preset variance threshold, then the median or mean of the measured flow time series is used as the recalculated actual flow value.

[0042] If the variance of the sliding window is greater than or equal to the preset variance threshold, the acquisition time window is extended and acquisition is repeated until the variance of the sliding window is less than the preset variance threshold. The median or mean of the measured flow time series is then used as the recalculated actual flow value.

[0043] Further, the deviation between the actual flow rate value and the output value corresponding to the current flow characteristic curve under the same operating condition is calculated, including:

[0044] Get the iteration number of the current correction period;

[0045] Calculate the initial deviation between the actual flow rate value and the output value corresponding to the current flow characteristic curve under the same operating condition;

[0046] The correction amount decay coefficient is determined based on the number of iterations, and the correction amount decay coefficient decreases as the number of iterations increases;

[0047] The initial deviation value is attenuated using the correction attenuation coefficient to obtain the attenuated deviation value;

[0048] The attenuated deviation value is used as the deviation.

[0049] In a second aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the online testing and adjustment method for the flow characteristics of a steam turbine high-pressure regulating valve as described in the first aspect.

[0050] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0051] 1. This invention avoids the shortcomings of existing technologies that require disabling AGC and primary frequency control and applying for dedicated load scheduling for offline testing by acquiring historical operating data of the steam turbine under normal operating conditions, thus not affecting the normal operation of the unit. By searching for effective steady-state sample sets in adjacent operating condition intervals with a preset operating condition benchmark as the center and a set step size, the sample utilization rate of data screening is improved. By repeatedly executing the iterative steps of downloading correction parameters, recalculating the actual flow value and calculating the deviation based on the measured operating data after downloading, until the deviation is less than a preset threshold, the closed-loop verification and continuous optimization of the correction effect are realized, and the closed-loop iterative tuning of flow characteristics can be completed online under normal operating conditions of the unit.

[0052] 2. This invention obtains historical operating data of the steam turbine under normal operating conditions and classifies the data according to the distribution characteristics of the command signals of each regulating valve to obtain operating condition datasets under different valve regulation modes. This avoids the defects of the prior art that require the cancellation of AGC and primary frequency regulation control and the application for special load dispatch for offline testing. The flow characteristics can be adjusted during the normal participation of the unit in grid regulation without affecting the normal operation of the unit.

[0053] 3. This invention searches for adjacent operating condition intervals by taking a preset operating condition benchmark point as the center and setting a step size, and filters the operating condition dataset by using the fluctuation threshold of the operating parameters as the steady-state criterion. When no valid steady-state data is found, the set step size is increased and the search is repeated until valid steady-state data is obtained. This avoids the problem of low sample utilization caused by directly discarding data from fixed load points that do not meet the steady-state conditions in the prior art, and improves the efficiency of obtaining valid steady-state samples and data utilization, so that a valid steady-state sample set can be obtained under each operating condition benchmark point.

[0054] 4. The invention generates correction parameters based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and downloads them to the turbine control system. It also recalculates the actual flow value and the deviation based on the measured operating data after downloading the parameters. If the deviation is greater than or equal to a preset threshold, the next correction parameter is generated based on the deviation and downloaded to the turbine control system again. This iterative process continues until the deviation is less than the preset threshold. During the iteration process, the correction amount attenuation coefficient is determined based on the number of iterations, and the attenuation coefficient decreases as the number of iterations increases. The attenuated deviation value is used as the deviation, which can verify the correction effect. Multiple corrections can be implemented based on the verification results, so that the correction parameters gradually approach the target value. Attached Figure Description

[0055] Figure 1 This is a schematic flowchart of an online testing and adjustment method for the flow characteristics of a high-pressure regulating valve in a steam turbine, provided by an embodiment of the present invention. Detailed Implementation

[0056] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0057] Example 1

[0058] like Figure 1 As shown in the figure, this embodiment introduces a method for online testing and adjustment of the flow characteristics of a steam turbine high-pressure regulating valve, including:

[0059] Step 1: Obtain historical operating data of the steam turbine under normal operating conditions.

[0060] This embodiment acquires historical operating data of the steam turbine under normal operating conditions, enabling the acquisition of a data foundation for flow characteristic analysis without disabling AGC and primary frequency control or requesting special load scheduling. This avoids the impact on normal unit operation caused by the need for offline special tests in the prior art.

[0061] Step 2: Classify the data according to the distribution characteristics of the command signals of each regulating valve in the historical operation data to obtain the operating condition dataset under different valve regulation methods.

[0062] This embodiment classifies the data according to the distribution characteristics of the command signals of each regulating valve to obtain the operating condition dataset under different valve regulation modes. It can identify the valve regulation mode of the unit under different operating conditions based on actual operating data, and provide a classification basis for the subsequent flow characteristic analysis under each regulation mode.

[0063] Step 3: Based on the preset operating condition benchmark, the operating condition dataset is filtered using the fluctuation threshold of the operating parameters as the steady-state criterion. Then, the dataset is searched in the adjacent operating condition intervals with the preset operating condition benchmark as the center and a set step size is used to obtain the effective steady-state sample set under each operating condition benchmark.

[0064] This embodiment filters the operating condition dataset based on a preset operating condition benchmark point and uses the fluctuation threshold of the operating parameters as a steady-state criterion. It then searches for adjacent operating condition intervals with a set step size centered on the preset operating condition benchmark point to obtain an effective steady-state sample set under each operating condition benchmark point. This allows for the acquisition of effective data at load points that do not meet steady-state conditions by searching for adjacent operating condition intervals, avoiding the problem of low sample utilization caused by directly discarding data from fixed sampling points that do not meet steady-state conditions in the prior art.

[0065] Step 4: Calculate the actual flow rate at each operating condition reference point based on the effective steady-state sample set, and fit the actual flow rate characteristic curve for this operation.

[0066] This embodiment calculates the actual flow rate at each operating condition reference point based on the effective steady-state sample set, and fits the actual flow rate characteristic curve to obtain the actual flow rate characteristic curve. It can convert the actual flow rate value based on the regulating stage pressure and steam specific volume in the effective steady-state sample, so that the fitted flow rate characteristic curve reflects the current actual operating status of the unit.

[0067] Step 5: Repeat the following steps until the deviation is less than a preset threshold:

[0068] The corrected parameters are generated based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and then downloaded to the turbine control system.

[0069] This embodiment generates the current correction parameter based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and downloads it to the turbine control system. Then, it recalculates the actual flow value and the deviation based on the measured operating data after downloading. If the deviation is greater than or equal to a preset threshold, it generates the next correction parameter based on the deviation and downloads it to the turbine control system again. This process continues until the deviation is less than the preset threshold. This allows for verification of the actual effect of the downloaded correction parameter and enables multiple corrections based on the verification results until the deviation meets the requirements. This avoids the problems of the prior art where the correction parameter is downloaded only once and then terminated, and there is a lack of verification of the correction effect.

[0070] The actual flow rate value is recalculated based on the measured operating data after being installed in the turbine control system.

[0071] This embodiment also uses the measured operating data after it is installed in the turbine control system as input, and continuously collects multiple sets of measured operating data within a preset interval of each operating condition reference point with a preset time window length as the sliding step size. The measured relative flow values ​​are then converted to form a measured flow time series. The variance of the sliding window is calculated and compared with the variance threshold. If it is less than the threshold, the median or mean is used as the recalculated actual flow value. If it is greater than or equal to the threshold, the collection time window is extended and the data is collected again until the condition is met. This ensures that the measured flow values ​​used for deviation calculation are stable and representative, and avoids distortion of recalculation results caused by instantaneous disturbances.

[0072] Calculate the deviation between the actual flow rate value and the output value corresponding to the current flow rate characteristic curve under the same operating condition. If the deviation is greater than or equal to a preset threshold, generate the next correction parameter based on the deviation and download it to the turbine control system again.

[0073] This embodiment also obtains the number of iterations and determines the correction amount decay coefficient that decreases as the number of iterations increases. The initial deviation value is decayed using this decay coefficient to obtain the decayed deviation value. This allows the deviation correction amount to be larger in the early stage of iteration to accelerate the convergence speed and smaller in the later stage of iteration to avoid correction oscillation, so that the correction parameter gradually approaches the target value.

[0074] Example 2

[0075] Based on the same inventive concept as Embodiment 1, this embodiment introduces a method for online testing and adjustment of the flow characteristics of a steam turbine high-pressure regulating valve, including:

[0076] Step 1: Obtain historical operating data of the steam turbine under normal operating conditions.

[0077] In this embodiment, the historical operating data of the steam turbine under normal operating conditions includes at least the command signals of each regulating valve, the overall valve position command, the unit load, the main steam pressure, the main steam temperature, the regulating stage pressure, and the regulating stage temperature.

[0078] Step 2: Classify the data according to the distribution characteristics of the command signals of each regulating valve in the historical operation data to obtain the operating condition dataset under different valve regulation methods.

[0079] Step 2.1: Extract continuous load change process segments from the historical operating data, starting with the load change rate being greater than the preset change rate threshold and ending with the load change rate being less than the preset change rate threshold.

[0080] Step 2.2: Within each variable load process segment, calculate the distribution characteristics of each control valve command signal in chronological order, identify the time point when the distribution characteristics of the control valve command signal change abruptly, and divide the variable load process segment into multiple control mode sub-segments using the abrupt change time point as the boundary.

[0081] Step 2.3: Based on the distribution characteristics of the control valve command signals in each sub-segment, determine the valve control mode of each sub-segment and classify it into the corresponding operating condition dataset to obtain the operating condition dataset under different valve control modes.

[0082] Step 3: Based on the preset operating condition benchmark, the operating condition dataset is filtered using the fluctuation threshold of the operating parameters as the steady-state criterion. Then, the dataset is searched in the adjacent operating condition intervals with the preset operating condition benchmark as the center and a set step size is used to obtain the effective steady-state sample set under each operating condition benchmark.

[0083] Step 3.1: Determine multiple preset operating condition reference points based on the rated load at set percentage intervals.

[0084] Step 3.2: Using each preset working condition reference point as the center, search for adjacent working condition intervals with a set step size.

[0085] Step 3.3: Within each searched operating condition interval, the data within the interval is determined to be valid steady-state data, provided that the fluctuation amplitude of the operating parameters within the preset time window is less than the corresponding fluctuation threshold.

[0086] If valid steady-state data is found at the current preset operating condition reference point, the search for the current preset operating condition reference point is stopped and the valid steady-state data is saved as the valid steady-state sample corresponding to the current preset operating condition reference point.

[0087] If no valid steady-state data is found at the current preset operating condition reference point, the set step size is increased and the search is repeated until valid steady-state data is obtained.

[0088] Step 3.4: Summarize the effective steady-state samples corresponding to each preset operating condition reference point to obtain the effective steady-state sample set under each operating condition reference point.

[0089] Step 4: Calculate the actual flow rate at each operating condition reference point based on the effective steady-state sample set, and fit the actual flow rate characteristic curve for this operation.

[0090] Step 4.1: Based on the regulating stage pressure in the effective steady-state sample set and the steam specific volume obtained from the regulating stage pressure and temperature, calculate the actual relative flow rate value at each operating condition reference point using the relative flow rate calculation formula.

[0091] In this embodiment, the relative flow rate calculation formula is expressed as:

[0092] ;

[0093] In the formula, This indicates the relative main steam flow rate under varying load conditions. This indicates the relative main steam flow rate under rated load conditions. This indicates the absolute pressure of the regulating stage under varying load conditions. This indicates the absolute pressure of the regulating stage under rated load conditions. This indicates the specific volume of steam after the regulating stage under rated load conditions. This indicates the specific volume of steam after the regulating stage under varying load conditions.

[0094] Step 4.2: Using the load and the corresponding actual relative flow rate at each operating condition reference point as data points, obtain the load-actual flow rate curve by fitting, and use it as the actual flow rate characteristic curve for this operation.

[0095] Step 5: Repeat the following steps until the deviation is less than a preset threshold:

[0096] Step 5.1: Generate the correction parameters based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and download the correction parameters to the turbine control system.

[0097] Step 5.1.1: Calculate the deviation between the actual flow characteristic curve and the preset flow characteristic curve at each operating condition reference point, and construct the deviation sequence according to the load from low to high.

[0098] Step 5.1.2: Perform differential operation on the deviation sequence to identify abrupt intervals in the deviation sequence where the rate of change of deviation between adjacent working condition reference points exceeds a preset rate of change threshold.

[0099] Step 5.1.3: Divide all operating condition reference points into multiple correction segments using the abrupt change interval as the boundary. Calculate the statistical characteristic value of the deviation of each operating condition reference point within each correction segment. Use the statistical characteristic value as the correction basis for the correction segment to generate the corresponding comprehensive valve position command correction value. The correction parameters for this correction are composed of each correction segment and its corresponding comprehensive valve position command correction value.

[0100] Step 5.2: Recalculate the actual flow rate value using the measured operating data after it is installed in the turbine control system.

[0101] Step 5.2.1: Using the measured operating data after it is installed in the turbine control system as input, and with the preset time window length as the sliding step, continuously collect multiple sets of measured operating data within the preset interval of each operating condition reference point;

[0102] Step 5.2.2: Using the measured operating data of each group as input, extract the regulating stage pressure and the steam specific volume obtained from the regulating stage pressure and temperature, and calculate the measured relative flow rate value of each group using the relative flow rate calculation formula to form a measured flow rate time series;

[0103] Step 5.2.3: Calculate the sliding window variance of the measured flow rate time series;

[0104] If the variance of the sliding window is less than a preset variance threshold, then the median or mean of the measured flow time series is used as the recalculated actual flow value.

[0105] If the variance of the sliding window is greater than or equal to the preset variance threshold, the acquisition time window is extended and acquisition is repeated until the variance of the sliding window is less than the preset variance threshold. The median or mean of the measured flow time series is then used as the recalculated actual flow value.

[0106] Step 5.3: Calculate the deviation between the actual flow rate value and the output value corresponding to the current flow rate characteristic curve under the same operating condition. If the deviation is greater than or equal to a preset threshold, generate the next correction parameter based on the deviation and download it to the turbine control system again.

[0107] In this embodiment, calculating the deviation between the actual flow rate value and the output value corresponding to the current flow characteristic curve under the same operating condition includes: obtaining the iteration number of the current correction cycle; calculating the initial deviation value between the actual flow rate value and the output value corresponding to the current flow characteristic curve under the same operating condition; determining a correction amount attenuation coefficient based on the iteration number, wherein the correction amount attenuation coefficient decreases as the iteration number increases; applying the correction amount attenuation coefficient to the initial deviation value to obtain an attenuated deviation value; and using the attenuated deviation value as the deviation.

[0108] Example 3

[0109] Based on the same inventive concept as other embodiments, this embodiment describes a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the methods of Embodiment 1 or 2 described above.

[0110] In summary, this invention, by acquiring historical operating data of the steam turbine under normal operating conditions, avoids the shortcomings of existing technologies that require disabling AGC and primary frequency control and applying for dedicated load scheduling for offline testing, thus not affecting the normal operation of the unit. By searching for effective steady-state sample sets in adjacent operating condition intervals with a preset operating condition benchmark as the center and a set step size, the sample utilization rate of data screening is improved. By repeatedly executing the iterative steps of downloading correction parameters, recalculating the actual flow value and calculating the deviation based on the measured operating data after downloading, until the deviation is less than a preset threshold, closed-loop verification and continuous optimization of the correction effect are achieved, enabling closed-loop iterative tuning of flow characteristics to be completed online under normal operating conditions of the unit.

[0111] This invention obtains historical operating data of the steam turbine under normal operating conditions and classifies the data according to the distribution characteristics of the command signals of each regulating valve to obtain operating condition datasets under different valve regulation modes. This avoids the defects of the prior art that require the cancellation of AGC and primary frequency regulation control and the application for special load dispatch for offline testing. The flow characteristics can be adjusted during the normal participation of the unit in grid regulation without affecting the normal operation of the unit.

[0112] This invention searches for adjacent operating condition intervals by centering on a preset operating condition benchmark point and using a set step size. It filters the operating condition dataset using the fluctuation threshold of operating parameters as a steady-state criterion. When no valid steady-state data is found, the set step size is increased and the search is repeated until valid steady-state data is obtained. This avoids the problem of low sample utilization caused by directly discarding data from fixed load points that do not meet steady-state conditions in the prior art. It improves the efficiency of obtaining valid steady-state samples and the data utilization rate, so that a valid steady-state sample set can be obtained under each operating condition benchmark point.

[0113] The invention iteratively generates correction parameters based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and downloads them to the turbine control system. It then recalculates the actual flow value and the deviation based on the measured operating data after downloading the parameters. If the deviation is greater than or equal to a preset threshold, the next correction parameter is generated based on the deviation and downloaded to the turbine control system again. This iterative process continues until the deviation is less than the preset threshold. During the iteration process, the correction amount attenuation coefficient is determined based on the number of iterations, and the attenuation coefficient decreases as the number of iterations increases. The attenuated deviation value is used as the deviation, which can verify the correction effect. Multiple corrections can be implemented based on the verification results, allowing the correction parameters to gradually approach the target value.

[0114] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0116] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0117] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0118] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve in a steam turbine, characterized in that, include: Acquire historical operating data of the steam turbine under normal operating conditions; The data is classified according to the distribution characteristics of the command signals of each control valve in the historical operation data to obtain the operating condition dataset under different valve control methods; Based on the preset operating condition benchmark, the operating condition dataset is filtered using the fluctuation threshold of the operating parameters as the steady-state criterion, and the dataset is searched in the adjacent operating condition intervals with the preset operating condition benchmark as the center and a set step size is used to obtain the effective steady-state sample set under each operating condition benchmark. The actual flow rate values ​​at each operating condition reference point are calculated based on the effective steady-state sample set, and the actual flow rate characteristic curve is obtained by fitting the curve. Repeat the following steps until the deviation is less than a preset threshold: The correction parameters are generated based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, and then downloaded to the turbine control system. The actual flow rate value was recalculated based on the measured operating data after being installed in the turbine control system. Calculate the deviation between the actual flow rate value and the output value corresponding to the current flow rate characteristic curve under the same operating condition. If the deviation is greater than or equal to a preset threshold, generate the next correction parameter based on the deviation and download it to the turbine control system again.

2. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 1, characterized in that, The historical operating data of the turbine under normal operating conditions includes at least the command signals of each regulating valve, the overall valve position command, the unit load, the main steam pressure, the main steam temperature, the regulating stage pressure, and the regulating stage temperature.

3. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 2, characterized in that, The process of classifying the data based on the distribution characteristics of the command signals of each regulating valve in the historical operating data to obtain operating condition datasets under different valve regulation modes includes: Starting with the load change rate of the unit being greater than a preset change rate threshold, and ending with the load change rate being less than the preset change rate threshold, continuous load change process segments are extracted from the historical operating data. Within each variable load process segment, the distribution characteristics of each control valve command signal are calculated in chronological order. The time points when the distribution characteristics of the control valve command signals change abruptly are identified, and the variable load process segment is divided into multiple control mode sub-segments using the abrupt change time points as boundaries. Based on the distribution characteristics of the control valve command signals within each sub-segment, the valve control mode of each sub-segment is determined and assigned to the corresponding operating condition dataset, thus obtaining the operating condition dataset under different valve control modes.

4. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 3, characterized in that, Based on a preset operating condition benchmark, the operating condition dataset is filtered using the fluctuation threshold of operating parameters as the steady-state criterion. Then, using the preset operating condition benchmark as the center, a search is performed in adjacent operating condition intervals at a set step size to obtain an effective steady-state sample set under each operating condition benchmark, including: Multiple preset operating condition reference points are determined at set percentage intervals based on the rated load; Each preset working condition reference point is used as the center, and the search is performed in the adjacent working condition range with a set step size; Within each searched operating condition interval, the data within the operating condition interval is determined to be valid steady-state data, provided that the fluctuation amplitude of the operating parameters within the preset time window is less than their respective fluctuation thresholds. If valid steady-state data is found at the current preset operating condition reference point, the search for the current preset operating condition reference point is stopped and the valid steady-state data is saved as the valid steady-state sample corresponding to the current preset operating condition reference point. If no valid steady-state data is found at the current preset operating condition reference point, the set step size is increased and the search is repeated until valid steady-state data is obtained. By summarizing the effective steady-state samples corresponding to each preset operating condition reference point, the effective steady-state sample set under each operating condition reference point is obtained.

5. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 4, characterized in that, The actual flow rate values ​​at each operating condition reference point are calculated based on the effective steady-state sample set, and the actual flow rate characteristic curve for this operation is obtained by fitting the curve, including: Based on the regulating stage pressure in the effective steady-state sample set and the steam specific volume obtained from the regulating stage pressure and temperature, the actual relative flow rate value under each operating condition reference point is calculated using the relative flow rate calculation formula. Using the load and the corresponding actual relative flow rate at each operating condition reference point as data points, a load-actual flow rate curve is obtained by fitting, which serves as the actual flow rate characteristic curve for this application.

6. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 5, characterized in that, The relative flow rate calculation formula is expressed as follows: ； In the formula, This indicates the relative main steam flow rate under varying load conditions. This indicates the relative main steam flow rate under rated load conditions. This indicates the absolute pressure of the regulating stage under varying load conditions. This indicates the absolute pressure of the regulating stage under rated load conditions. This indicates the specific volume of steam after the regulating stage under rated load conditions. This indicates the specific volume of steam after the regulating stage under varying load conditions.

7. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 5, characterized in that, The corrected parameters for this test are generated based on the deviation between the actual flow characteristic curve and the preset flow characteristic curve, including: Calculate the deviation between the actual flow characteristic curve and the preset flow characteristic curve at each operating condition reference point, and construct a deviation sequence according to the load from low to high. Perform a difference operation on the deviation sequence to identify abrupt intervals in the deviation sequence where the rate of change of deviation between adjacent working condition reference points exceeds a preset rate of change threshold; The entire operating condition reference point is divided into multiple correction segments using the abrupt change interval as the boundary. Within each correction segment, the statistical characteristic value of the deviation of each operating condition reference point is calculated. The statistical characteristic value is used as the correction basis for the correction segment to generate the corresponding comprehensive valve position command correction value. The correction parameters for this correction are composed of each correction segment and its corresponding comprehensive valve position command correction value.

8. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 7, characterized in that, The actual flow rate value was recalculated based on the measured operating data after being installed in the turbine control system, including: The measured operating data after being installed in the turbine control system is used as input, and multiple sets of measured operating data are continuously collected within the preset interval of each operating condition reference point with the preset time window length as the sliding step. Using the measured operating data of each group as input, the regulating stage pressure and the steam specific volume obtained from the regulating stage pressure and temperature are extracted. The measured relative flow rate values ​​of each group are then converted using the relative flow rate calculation formula to form a measured flow rate time series. Calculate the sliding window variance of the measured flow rate time series; If the variance of the sliding window is less than a preset variance threshold, then the median or mean of the measured flow time series is used as the recalculated actual flow value. If the variance of the sliding window is greater than or equal to the preset variance threshold, the acquisition time window is extended and acquisition is repeated until the variance of the sliding window is less than the preset variance threshold. The median or mean of the measured flow time series is then used as the recalculated actual flow value.

9. The method for online testing and adjustment of the flow characteristics of a high-pressure regulating valve for a steam turbine according to claim 8, characterized in that, Calculating the deviation between the actual flow rate value and the output value corresponding to the current flow rate characteristic curve under the same operating condition includes: Get the iteration number of the current correction period; Calculate the initial deviation between the actual flow rate value and the output value corresponding to the current flow characteristic curve under the same operating condition; The correction amount decay coefficient is determined based on the number of iterations, and the correction amount decay coefficient decreases as the number of iterations increases; The initial deviation value is attenuated using the correction attenuation coefficient to obtain the attenuated deviation value; The attenuated deviation value is used as the deviation.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for online testing and adjustment of the flow characteristics of the high-pressure regulating valve of a steam turbine as described in any one of claims 1 to 9.

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