Segmented closing control method and system for speed regulator of hydraulic power plant

Abstract

The invention provides a segmented closing control method and system for a speed regulator of a hydraulic power plant, and the method comprises the steps: obtaining the rotation speed data of a to-be-closed unit of the hydraulic power plant, and carrying out the preprocessing of the rotation speed data, and obtaining the preprocessed rotation speed data; according to the preprocessed rotating speed data, the rotating speed stage of the unit to be closed and the initial closing rate of the stage are determined, and the unit is controlled to be closed based on the initial closing rate; rotating speed data, water hammer pressure data and vibration amplitude data in the unit closing process are obtained in real time, the initial closing rate is corrected according to the rotating speed data, the water hammer pressure data and the vibration amplitude data in the unit closing process, and the corrected closing rate is obtained; and controlling the unit to be closed based on the corrected closing rate. According to the technical scheme, safe and stable shutdown of the unit can be ensured, and meanwhile the risks of secondary impact and pressure pipeline breakage can be avoided.

Description

Technical Field

[0001] The present application relates to the technical field of hydropower plant speed regulator control, and in particular to a hydropower plant speed regulator segmented shutdown control method and system. Background Art

[0002] The shutdown process of hydropower plant units is a critical step in plant operation. The governor's shutdown control during shutdown directly impacts the unit's safety and stability. Traditional governor shutdown control methods typically use a single shutdown rate, which cannot dynamically adjust to the unit's actual operating status. This can easily lead to excessive water hammer pressure or vibration during shutdown, compromising safe operation.

[0003] Existing governor shutdown control methods have the following problems: Single shutdown rate: Traditional governor shutdown control methods typically use a fixed shutdown rate and cannot dynamically adjust according to the actual operating status of the unit, which can easily lead to excessive water hammer pressure or vibration during the unit shutdown process; Lack of segmented control: Existing governor shutdown control methods lack segmented control capabilities and cannot perform segmented shutdown according to the unit's operating status (such as speed, head pressure, etc.), resulting in an unstable shutdown process; Low intelligence: Existing governor shutdown control methods mostly rely on manual operation and experience judgment, lack intelligent control methods, and have difficulty achieving accurate and efficient shutdown control. Therefore, there is an urgent need to propose a solution that can achieve accurate, safe, and efficient shutdown control. Summary of the Invention

[0004] The present application provides a hydropower plant speed regulator segmented shutdown control method and system to at least solve the technical problems of low safety, low control accuracy and low efficiency in the prior art.

[0005] The first embodiment of the present application provides a method for controlling the staged shutdown of a hydropower plant speed regulator, the method comprising:

[0006] Obtaining speed data of a unit to be shut down in a hydropower plant, and preprocessing the speed data to obtain preprocessed speed data;

[0007] Determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data, and controlling the shutdown of the unit based on the initial shutdown rate;

[0008] acquiring speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit in real time, and correcting the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate;

[0009] The unit is controlled to shut down based on the corrected closing rate.

[0010] Preferably, the process of determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data, and controlling the shutdown of the unit based on the initial shutdown rate further includes:

[0011] Acquiring water hammer pressure data of the unit to be shut down, and preprocessing the water hammer pressure data to obtain preprocessed water hammer pressure data;

[0012] Determine whether the pre-processed water hammer pressure data is greater than or equal to a preset first pressure threshold. If so, stop the shutdown control of the unit to be shut down, and control the guide vane opening of the unit to be shut down to retract and the bypass valve of the unit to be shut down to open until the pre-processed water hammer pressure data is less than or equal to a second pressure threshold.

[0013] Furthermore, determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data includes:

[0014] When the pre-processed speed data is greater than 70% of the rated speed of the unit, the unit to be shut down is in a high speed stage, and the initial shutdown rate of the high speed stage is less than 0.5% / s;

[0015] When the pre-processed speed data is less than or equal to 70% and greater than or equal to 30% of the rated speed of the unit, the unit to be shut down is in a medium speed stage, and the initial shutdown rate of the medium speed stage is greater than or equal to 1% / s and less than or equal to 1.5% / s;

[0016] When the pre-processed speed data is less than 30% of the rated speed of the unit, the unit to be shut down is in a low speed stage, and the initial shut-down rate of the low speed stage is greater than 2.0% / s.

[0017] Furthermore, the real-time acquisition of the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit, and the correction of the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate, include:

[0018] Determining the water hammer pressure change trend, speed change trend, and vibration change trend of the unit based on the speed data, water hammer pressure data, and vibration amplitude data acquired in real time during the shutdown process of the unit;

[0019] Based on the water hammer pressure change trend, speed change trend, and vibration change trend of the unit, a fuzzy PID control algorithm is used to dynamically correct the closing rate of each stage.

[0020] Furthermore, the method further comprises:

[0021] Obtaining shutdown data of the unit to be shut down at each moment in a historical period, and building a fault prediction model based on the shutdown data at each moment in the historical period;

[0022] The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit to be shut down at the current moment are input into the fault prediction model to obtain whether the unit has a fault and the fault type.

[0023] Furthermore, the method further comprises:

[0024] Obtaining the water hammer pressure peak, total downtime, and vibration suppression coefficient of the unit to be shut down within a historical period;

[0025] The shutdown efficiency index of the unit to be shut down is determined according to the water hammer pressure peak, total shutdown time, and vibration suppression coefficient of the unit to be shut down in a historical period.

[0026] Furthermore, the method further comprises:

[0027] The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit are uploaded to the cloud server.

[0028] The second embodiment of the present application provides a hydropower plant speed governor staged shutdown control system, comprising:

[0029] An acquisition module is used to acquire the speed data of the units to be shut down in the hydropower plant, and preprocess the speed data to obtain preprocessed speed data;

[0030] a determination module, configured to determine the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the preprocessed speed data, and control the shutdown of the unit based on the initial shutdown rate;

[0031] a correction module, configured to obtain in real time the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit, and correct the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate;

[0032] A control module is configured to control the unit to shut down based on the corrected shut down rate.

[0033] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method described in the first aspect is implemented.

[0034] A fourth embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first embodiment.

[0035] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0036] The present application proposes a method and system for controlling the segmented shutdown of a hydropower plant speed regulator, the method comprising: obtaining the speed data of the unit to be shut down in the hydropower plant, and preprocessing the speed data to obtain preprocessed speed data; determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the preprocessed speed data, and controlling the shutdown of the unit based on the initial shutdown rate; obtaining the speed data, water hammer pressure data, and vibration amplitude data of the unit during the shutdown process in real time, and correcting the initial shutdown rate according to the speed data, water hammer pressure data, and vibration amplitude data of the unit during the shutdown process to obtain a corrected shutdown rate; and controlling the shutdown of the unit based on the corrected shutdown rate. The technical solution proposed in the present application can ensure the safe and smooth shutdown of the unit, while avoiding the risk of secondary impact and pressure pipe rupture.

[0037] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0039] Figure 1 This is a flow chart of a method for controlling segmented shutdown of a speed governor in a hydropower plant according to one embodiment of the present application;

[0040] Figure 2 A detailed flow chart of a method for controlling segmented shutdown of a hydropower plant speed governor according to one embodiment of the present application;

[0041] Figure 3 This is a first structural diagram of a hydropower plant governor segmented shutdown control system provided according to one embodiment of the present application;

[0042] Figure 4This is a second structural diagram of a hydropower plant speed governor segmented shutdown control system provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0044] The present application proposes a method and system for controlling the segmented shutdown of a hydropower plant speed regulator, the method comprising: obtaining the speed data of the unit to be shut down in the hydropower plant, and preprocessing the speed data to obtain preprocessed speed data; determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the preprocessed speed data, and controlling the shutdown of the unit based on the initial shutdown rate; obtaining the speed data, water hammer pressure data, and vibration amplitude data of the unit during the shutdown process in real time, and correcting the initial shutdown rate according to the speed data, water hammer pressure data, and vibration amplitude data of the unit during the shutdown process to obtain a corrected shutdown rate; and controlling the shutdown of the unit based on the corrected shutdown rate. The technical solution proposed in the present application can ensure the safe and smooth shutdown of the unit, while avoiding the risk of secondary impact and pressure pipe rupture.

[0045] The following describes a method and system for controlling segmented shutdown of a hydropower plant speed regulator according to an embodiment of the present application with reference to the accompanying drawings.

[0046] Example 1

[0047] Figure 1 Flowchart of a hydropower plant governor segmented shutdown control method according to one embodiment of the present application, as shown in FIG. Figure 1 As shown, the method includes:

[0048] Step 1: Obtaining speed data of the units to be shut down in the hydropower plant, and preprocessing the speed data to obtain preprocessed speed data;

[0049] In the embodiment of the present disclosure, before step 2, the following steps are further included:

[0050] Acquiring water hammer pressure data of the unit to be shut down, and preprocessing the water hammer pressure data to obtain preprocessed water hammer pressure data;

[0051] Determine whether the pre-processed water hammer pressure data is greater than or equal to a preset first pressure threshold. If so, stop the shutdown control of the unit to be shut down, and control the guide vane opening of the unit to be shut down to retract and the bypass valve of the unit to be shut down to open until the pre-processed water hammer pressure data is less than or equal to a second pressure threshold.

[0052] Step 2: determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data, and controlling the shutdown of the unit based on the initial shutdown rate;

[0053] In the embodiment of the present disclosure, determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the preprocessed speed data includes:

[0054] When the pre-processed speed data is greater than 70% of the rated speed of the unit, the unit to be shut down is in a high speed stage, and the initial shutdown rate of the high speed stage is less than 0.5% / s;

[0055] When the pre-processed speed data is less than or equal to 70% and greater than or equal to 30% of the rated speed of the unit, the unit to be shut down is in a medium speed stage, and the initial shutdown rate of the medium speed stage is greater than or equal to 1% / s and less than or equal to 1.5% / s;

[0056] When the pre-processed speed data is less than 30% of the rated speed of the unit, the unit to be shut down is in a low speed stage, and the initial shut-down rate of the low speed stage is greater than 2.0% / s.

[0057] Step 3: acquiring speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit in real time, and correcting the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate;

[0058] In the embodiment of the present disclosure, step 3 specifically includes:

[0059] Determining the water hammer pressure change trend, speed change trend, and vibration change trend of the unit based on the speed data, water hammer pressure data, and vibration amplitude data acquired in real time during the shutdown process of the unit;

[0060] Based on the water hammer pressure change trend, speed change trend, and vibration change trend of the unit, a fuzzy PID control algorithm is used to dynamically correct the closing rate of each stage.

[0061] Step 4: Controlling the unit to shut down based on the corrected shut down rate.

[0062] In an embodiment of the present disclosure, the method further includes:

[0063] Obtaining shutdown data of the unit to be shut down at each moment in a historical period, and building a fault prediction model based on the shutdown data at each moment in the historical period;

[0064] The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit to be shut down at the current moment are input into the fault prediction model to obtain whether the unit has a fault and the fault type.

[0065] In an embodiment of the present disclosure, the method further includes:

[0066] Obtaining the water hammer pressure peak, total downtime, and vibration suppression coefficient of the unit to be shut down within a historical period;

[0067] The shutdown efficiency index of the unit to be shut down is determined according to the water hammer pressure peak, total shutdown time, and vibration suppression coefficient of the unit to be shut down in a historical period.

[0068] In an embodiment of the present disclosure, the method further includes:

[0069] The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit are uploaded to the cloud server.

[0070] It should be noted that the detailed process of the hydropower plant governor segmented shutdown control method provided in this embodiment is as follows: Figure 2 As shown:

[0071] S1. Multi-sensor fusion status monitoring can be performed, and the data of the unit can be collected in real time through multiple sensors, and signal preprocessing can be performed. Among them, the multiple sensors include but are not limited to speed sensors, pressure sensors, vibration sensors and guide vane opening sensors. The data collected from the unit include but are not limited to speed, head pressure, vibration amplitude and guide vane opening.

[0072] During the operation of a hydropower plant's turbine units, speed sensors monitor the unit's rotational speed in real time, accurately capturing every change in speed. Pressure sensors closely monitor fluctuations in head pressure and provide timely feedback. Vibration sensors comprehensively monitor vibrations generated during operation, capturing key data such as vibration amplitude. Guide vane position sensors constantly track the guide vane opening status. These sensors act as the unit's "senses," continuously collecting data and transmitting the signals to the data processing unit. The data processing unit immediately pre-processes these signals, employing filtering and denoising techniques to remove noise caused by environmental interference, electromagnetic interference from equipment, and other factors, ensuring data accuracy and reliability.

[0073] By integrating multiple sensors to collect multi-dimensional data such as speed, pressure, vibration, and guide vane opening, the system can comprehensively reflect the unit's operating status from multiple perspectives, avoiding the limitations of relying solely on single-parameter monitoring. This preprocessed data provides a precise and reliable basis for subsequent control strategy development, enabling the speed governor to make informed decisions, thereby achieving precise control of the unit and ensuring stable operation.

[0074] S2. Divide the shutdown process into high-speed, medium-speed, and low-speed stages based on the unit's rated speed and head pressure, and set the initial shutdown rate for each stage;

[0075] The high-speed stage is greater than 70% of the rated speed, the medium-speed stage is 30%-70% of the rated speed, and the low-speed stage is less than 30% of the rated speed. The initial closing rate of the high-speed stage is less than 0.5% / s, the initial closing rate of the medium-speed stage is 0% / s-5% / s, and the initial closing rate of the low-speed stage is greater than 2.0% / s.

[0076] The 0.5% / s mentioned above means that when the guide vane opening is closed at high speed, it should not decrease by more than 0.5% per second. Guide vane opening is typically expressed as a percentage, ranging from 0% (fully closed) to 100% (fully open). For example, if the guide vane is currently 80% open and the closing rate is 0.5% / s, the guide vane will close by 0.5% per second, decreasing from 80% to 79.5% per second, and so on. 0.5% / s means the guide vane opening decreases by 0.5% per second.

[0077] 0% / s-5% / s and 2.0% / s have the same meaning as above.

[0078] The speed governor scientifically divides the shutdown process based on the unit's rated speed and real-time head pressure. When the unit speed exceeds 70% of the rated speed, it enters the high-speed stage, with the initial shutdown rate set at less than 0.5% / s. When the speed is between 30% and 70% of the rated speed, it enters the medium-speed stage, with the initial shutdown rate controlled between 1.0% and 1.5% of the rated speed. When the speed is less than 30% of the rated speed, it enters the low-speed stage, with the initial shutdown rate set at greater than 2.0% / s. The speed governor automatically adjusts the shutdown rate according to the different speed stages of the unit, achieving precise control.

[0079] Setting different initial closing rates based on the unit's operating status effectively avoids a range of problems caused by closing too quickly or too slowly. At high speeds, a lower closing rate prevents excessive water hammer pressure and intense vibration caused by a sudden interruption of water flow. At medium speeds, a moderate closing rate ensures a smooth transition during the closing process. At low speeds, a higher closing rate allows for a quicker closing action before the unit is about to stop, improving shutdown efficiency. This not only ensures a smooth and efficient closing process, but also reduces equipment wear and tear, extending its service life.

[0080] S3. Based on real-time data, the closing rate of each stage is dynamically modified through the fuzzy PID control algorithm;

[0081] The PID controller parameters are dynamically adjusted through a fuzzy inference mechanism to correct the closing rate at each stage. When an upward trend in water hammer pressure is detected, the closing rate is appropriately reduced.

[0082] Based on the real-time data collected by multiple sensors in S1, the fuzzy PID control algorithm comes into play. This algorithm uses a fuzzy inference mechanism to dynamically adjust the parameters of the PID controller based on the current operating conditions of the unit, such as real-time water hammer pressure, speed changes, and vibration. For example, when an upward trend in water hammer pressure is detected, the fuzzy PID control algorithm automatically adjusts the parameters (dynamically adjusting one or more of the PID controller's proportional coefficient (Kp), integral time (Ki), and differential time (Kd) to achieve precise control of the guide vane closing rate) to appropriately reduce the closing rate. If the speed changes abnormally, the closing rate will also be adjusted accordingly to maintain stable operation of the unit.

[0083] Adaptive rate adjustment allows for flexible adjustments to shutdown strategies based on the unit's real-time operating conditions. This effectively suppresses water hammer pressure, reduces the impact of pressure fluctuations on equipment, and prevents damage to penstocks, turbines, and other equipment caused by excessive pressure, ensuring safe and stable equipment operation.

[0084] S4. Multi-threshold linkage safety protection: When the water hammer pressure exceeds the set value, the shutdown process is suspended and the bypass valve pressure relief and guide vane opening are triggered;

[0085] When water hammer pressure reaches a set value of 1.5 times the rated pressure, the entire shutdown process is immediately suspended. At this point, the system prioritizes opening the bypass valve to release excess pressure within the pipeline, reducing the threat of water hammer pressure to the equipment. Simultaneously, the guide vanes retract, gradually restoring the water flow to a stable state and preventing abnormal water flow shock. Only when the water hammer pressure drops below 90% of the rated value will the shutdown process resume, and subsequent closing operations will continue.

[0086] When water hammer pressure exceeds the limit, prompt measures such as temporary shutdown, bypass valve pressure relief, and guide vane opening retraction are implemented to effectively prevent severe damage to the equipment caused by excessive pressure and ensure that the equipment always operates in a safe state. This multi-threshold coordinated safety protection mechanism significantly improves equipment reliability, reduces the risk of equipment failure due to excessive water hammer pressure, and ensures the normal production and operation of the hydropower plant.

[0087] S5. Fault prediction: By modeling historical downtime data, bearing wear and guide vane jamming failures can be predicted, and maintenance warnings can be issued in advance.

[0088] Model historical downtime data and output data (such as sensor data, downtime process parameters, environment and equipment status, label data, etc.). Based on the built model, the following data can be output:

[0089] Fault type: predict the type of fault that may occur (such as bearing wear, guide vane jam);

[0090] Failure probability: the probability of a failure occurring or the remaining useful life;

[0091] Maintenance recommendations: thresholds for triggering warnings and recommended maintenance times.

[0092] Using models, faults such as bearing wear and guide vane sticking can be predicted and issued in advance. This helps operations personnel plan maintenance in advance and perform repairs before a fault occurs, avoiding downtime caused by sudden failures, reducing equipment maintenance costs and production losses, and improving the continuity and stability of hydropower plant operations.

[0093] S6. Post-shutdown performance evaluation: Analyze the water hammer pressure peak, vibration suppression efficiency, and total shutdown time during the shutdown process. The water hammer pressure peak indicates the impact of the shutdown process on the equipment, the vibration suppression efficiency reflects the control method's effectiveness in controlling unit vibration, and the total shutdown time reflects the efficiency of the shutdown. By analyzing these indicators, an economic report is generated to evaluate the costs and benefits of the shutdown.

[0094] The calculation formula for the above economic report is:

[0095]

[0096] Among them, E is the shutdown efficiency index, P peak is the peak water hammer pressure, T stop is the total downtime, C vib is the vibration suppression coefficient.

[0097] P peak To monitor pipeline pressure in real time during shutdown through pressure sensors and record the maximum value of transient pressure;

[0098] Tstop Record the start and end time of the shutdown process for the timer and calculate the total time consumed;

[0099] C vib是 The vibration amplitude data during the shutdown process is collected by vibration sensors and calculated based on the historical data model.

[0100] By analyzing various shutdown process indicators and generating economic performance reports, we can clearly understand the impact of the shutdown. Comparing historical data can accurately identify inefficiencies during the shutdown process, such as an inappropriate shutdown rate setting at a certain stage leading to excessive water hammer pressure or prolonged shutdown time. Based on these analysis results, control parameters can be iteratively improved, providing a scientific basis for optimizing subsequent control strategies, thereby continuously improving the hydropower plant's operational efficiency and economic benefits.

[0101] S7. Cloud data synchronization and remote maintenance uploads operating data to the cloud server in real time. Operation and maintenance personnel can access cloud data through remote terminals, conduct remote diagnosis, and promptly identify potential equipment problems. At the same time, they can also dynamically update control parameters based on actual conditions to achieve remote optimization control of the speed regulator.

[0102] Cloud-based data synchronization allows operators to access real-time equipment operating data without having to visit the site, enabling convenient and rapid remote diagnosis and improving the timeliness of fault detection. The remote control parameter update function allows for timely adjustment of control strategies based on the actual operating conditions of the equipment, enabling remote optimization of the speed regulator, reducing the workload and time costs of on-site operations and improving the operation and maintenance efficiency of the hydropower plant.

[0103] During operation, this embodiment prioritizes bypass valve pressure relief through multi-threshold linkage safety protection, sets post-pressure relief recovery conditions, and avoids secondary shocks. A dynamic segmentation strategy provides an initial rate setting for the fuzzy PID controller, effectively suppressing water inertial shock and preventing the risk of penstock rupture. Segmented shutdown control and dynamic adjustment of the shutdown rate effectively prevent excessive water hammer pressure or vibration during unit shutdown, ensuring safe and smooth shutdown. Furthermore, intelligent fault prediction and maintenance can detect potential faults in advance, reduce equipment downtime, and improve the unit's operational efficiency and reliability.

[0104] In summary, the hydropower plant governor staged shutdown control method proposed in this embodiment can ensure the safe and smooth shutdown of the unit, while avoiding the risks of secondary shock and pressure pipe rupture.

[0105] Example 2

[0106] Figure 3 This is a structural diagram of a hydropower plant governor segmented shutdown control system provided according to one embodiment of the present application, such as Figure 3 As shown, the system includes:

[0107] An acquisition module 100 is used to acquire the speed data of the units to be shut down in the hydropower plant, and pre-process the speed data to obtain pre-processed speed data;

[0108] a determination module 200 for determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the preprocessed speed data, and controlling the shutdown of the unit based on the initial shutdown rate;

[0109] a correction module 300 for acquiring in real time the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit, and correcting the initial shutdown rate based on the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected shutdown rate;

[0110] The control module 400 is configured to control the unit to shut down based on the corrected shutdown rate.

[0111] In the embodiment of the present disclosure, the acquisition module 100 is further configured to:

[0112] Before determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage based on the preprocessed speed data, and controlling the shutdown of the unit based on the initial shutdown rate, obtaining water hammer pressure data of the unit to be shut down, and preprocessing the water hammer pressure data to obtain preprocessed water hammer pressure data;

[0113] Determine whether the pre-processed water hammer pressure data is greater than or equal to a preset first pressure threshold. If so, stop the shutdown control of the unit to be shut down, and control the guide vane opening of the unit to be shut down to retract and the bypass valve of the unit to be shut down to open until the pre-processed water hammer pressure data is less than or equal to a second pressure threshold.

[0114] Furthermore, the determining module 200 is further configured to:

[0115] When the pre-processed speed data is greater than 70% of the rated speed of the unit, the unit to be shut down is in a high speed stage, and the initial shutdown rate of the high speed stage is less than 0.5% / s;

[0116] When the pre-processed speed data is less than or equal to 70% and greater than or equal to 30% of the rated speed of the unit, the unit to be shut down is in a medium speed stage, and the initial shutdown rate of the medium speed stage is greater than or equal to 1% / s and less than or equal to 1.5% / s;

[0117] When the pre-processed speed data is less than 30% of the rated speed of the unit, the unit to be shut down is in a low speed stage, and the initial shut-down rate of the low speed stage is greater than 2.0% / s.

[0118] In the embodiment of the present disclosure, the correction module 300 is further configured to:

[0119] Determining the water hammer pressure change trend, speed change trend, and vibration change trend of the unit based on the speed data, water hammer pressure data, and vibration amplitude data acquired in real time during the shutdown process of the unit;

[0120] Based on the water hammer pressure change trend, speed change trend, and vibration change trend of the unit, a fuzzy PID control algorithm is used to dynamically correct the closing rate of each stage.

[0121] In the embodiment of the present disclosure, Figure 4 As shown, the system further includes: a fault prediction module 500;

[0122] The fault prediction module 500 is used to:

[0123] Obtaining shutdown data of the unit to be shut down at each moment in a historical period, and building a fault prediction model based on the shutdown data at each moment in the historical period;

[0124] The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit to be shut down at the current moment are input into the fault prediction model to obtain whether the unit has a fault and the fault type.

[0125] In the embodiment of the present disclosure, Figure 4 As shown, the system further includes: an index determination module 600;

[0126] The index determination module 600 is configured to:

[0127] Obtaining the water hammer pressure peak, total downtime, and vibration suppression coefficient of the unit to be shut down within a historical period;

[0128] The shutdown efficiency index of the unit to be shut down is determined according to the water hammer pressure peak, total shutdown time, and vibration suppression coefficient of the unit to be shut down in a historical period.

[0129] In the embodiment of the present disclosure, Figure 4 As shown, the system further includes: a cloud server module 700;

[0130] The cloud server module 700 is used to:

[0131] The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit are uploaded to the cloud server.

[0132] In summary, the hydropower plant governor staged shutdown control system proposed in this embodiment can ensure safe and smooth shutdown of the unit while avoiding the risks of secondary shock and pressure pipe rupture.

[0133] Example 3

[0134] To implement the above embodiments, the present disclosure further proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first embodiment is implemented.

[0135] Example 4

[0136] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.

[0137] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0138] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0139] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A hydropower plant speed governor segmented shutdown control method, characterized in that: The method comprises: Obtaining speed data of a unit to be shut down in a hydropower plant, and preprocessing the speed data to obtain preprocessed speed data; Determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data, and controlling the shutdown of the unit based on the initial shutdown rate; acquiring speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit in real time, and correcting the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate; The unit is controlled to shut down based on the corrected closing rate.

2. The method according to claim 1, wherein The method further includes determining the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data, and controlling the shutdown of the unit based on the initial shutdown rate: Acquiring water hammer pressure data of the unit to be shut down, and preprocessing the water hammer pressure data to obtain preprocessed water hammer pressure data; Determine whether the pre-processed water hammer pressure data is greater than or equal to a preset first pressure threshold. If so, stop the shutdown control of the unit to be shut down, and control the guide vane opening of the unit to be shut down to retract and the bypass valve of the unit to be shut down to open until the pre-processed water hammer pressure data is less than or equal to a second pressure threshold.

3. The method according to claim 2, wherein The determining of the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the pre-processed speed data includes: When the pre-processed speed data is greater than 70% of the rated speed of the unit, the unit to be shut down is in a high speed stage, and the initial shutdown rate of the high speed stage is less than 0.5% / s; When the pre-processed speed data is less than or equal to 70% and greater than or equal to 30% of the rated speed of the unit, the unit to be shut down is in a medium speed stage, and the initial shutdown rate of the medium speed stage is greater than or equal to 1% / s and less than or equal to 1.5% / s; When the pre-processed speed data is less than 30% of the rated speed of the unit, the unit to be shut down is in a low speed stage, and the initial shut-down rate of the low speed stage is greater than 2.0% / s.

4. The method according to claim 3, wherein The real-time acquisition of the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit, and correction of the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate, include: Determining the water hammer pressure change trend, speed change trend, and vibration change trend of the unit based on the speed data, water hammer pressure data, and vibration amplitude data acquired in real time during the shutdown process of the unit; Based on the water hammer pressure change trend, speed change trend, and vibration change trend of the unit, a fuzzy PID control algorithm is used to dynamically correct the closing rate of each stage.

5. The method according to claim 4, wherein The method further comprises: Obtaining shutdown data of the unit to be shut down at each moment in a historical period, and building a fault prediction model based on the shutdown data at each moment in the historical period; The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit to be shut down at the current moment are input into the fault prediction model to obtain whether the unit has a fault and the fault type.

6. The method according to claim 4, wherein The method further comprises: Obtaining the water hammer pressure peak, total downtime, and vibration suppression coefficient of the unit to be shut down within a historical period; The shutdown efficiency index of the unit to be shut down is determined according to the water hammer pressure peak, total shutdown time, and vibration suppression coefficient of the unit to be shut down in a historical period.

7. The method according to claim 4, wherein The method further comprises: The speed data, water hammer pressure data, vibration amplitude data and guide vane opening data of the unit are uploaded to the cloud server.

8. A hydropower plant speed governor segmented shutdown control system, characterized in that: The system comprises: An acquisition module is used to acquire the speed data of the units to be shut down in the hydropower plant, and preprocess the speed data to obtain preprocessed speed data; a determination module, configured to determine the speed stage of the unit to be shut down and the initial shutdown rate of the stage according to the preprocessed speed data, and control the shutdown of the unit based on the initial shutdown rate; a correction module, configured to obtain in real time the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit, and correct the initial closing rate according to the speed data, water hammer pressure data, and vibration amplitude data during the shutdown process of the unit to obtain a corrected closing rate; A control module is configured to control the unit to shut down based on the corrected shut down rate.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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