CN116717420A - Water turbine set air supplementing quantity control method, device, control system and storage medium - Google Patents
Water turbine set air supplementing quantity control method, device, control system and storage medium Download PDFInfo
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- CN116717420A CN116717420A CN202310873901.0A CN202310873901A CN116717420A CN 116717420 A CN116717420 A CN 116717420A CN 202310873901 A CN202310873901 A CN 202310873901A CN 116717420 A CN116717420 A CN 116717420A
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- 230000001502 supplementing effect Effects 0.000 title claims abstract description 278
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 230
- 238000000034 method Methods 0.000 title claims abstract description 66
- 230000008569 process Effects 0.000 claims abstract description 10
- 238000004088 simulation Methods 0.000 claims description 47
- 238000012549 training Methods 0.000 claims description 29
- 238000012545 processing Methods 0.000 claims description 22
- 238000004364 calculation method Methods 0.000 claims description 20
- 239000003795 chemical substances by application Substances 0.000 claims description 19
- 230000035945 sensitivity Effects 0.000 claims description 19
- 238000007405 data analysis Methods 0.000 claims description 14
- 239000013589 supplement Substances 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 8
- ZZUFCTLCJUWOSV-UHFFFAOYSA-N furosemide Chemical compound C1=C(Cl)C(S(=O)(=O)N)=CC(C(O)=O)=C1NCC1=CC=CO1 ZZUFCTLCJUWOSV-UHFFFAOYSA-N 0.000 claims 2
- 230000001276 controlling effect Effects 0.000 abstract description 42
- 230000001105 regulatory effect Effects 0.000 abstract description 12
- 230000009471 action Effects 0.000 abstract description 9
- 230000005611 electricity Effects 0.000 abstract description 2
- 238000012795 verification Methods 0.000 description 11
- 238000004458 analytical method Methods 0.000 description 8
- 239000011800 void material Substances 0.000 description 6
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- 230000007423 decrease Effects 0.000 description 3
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- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005086 pumping Methods 0.000 description 2
- 238000011144 upstream manufacturing Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000006837 decompression Effects 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
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- 229920006395 saturated elastomer Polymers 0.000 description 1
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- 238000010977 unit operation Methods 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03B—MACHINES OR ENGINES FOR LIQUIDS
- F03B15/00—Controlling
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03B—MACHINES OR ENGINES FOR LIQUIDS
- F03B11/00—Parts or details not provided for in, or of interest apart from, the preceding groups, e.g. wear-protection couplings, between turbine and generator
- F03B11/04—Parts or details not provided for in, or of interest apart from, the preceding groups, e.g. wear-protection couplings, between turbine and generator for diminishing cavitation or vibration, e.g. balancing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/20—Hydro energy
Abstract
The invention relates to the technical field of water and electricity, and discloses a water turbine unit air supplementing quantity control method, a water turbine unit air supplementing quantity control device, a water turbine unit air supplementing quantity control system and a water turbine unit storage medium. According to the invention, the opening value of the second electric control device is regulated through the first electric control device, and further, the air supplementing quantity of the water turbine set under the actual running condition is regulated through the opening of the second electric control device, so that the problems of air supplementing quantity deviation and the like caused by slow action and clamping stagnation of the vacuum breaking valve spring according to pressure difference control are solved. Therefore, by implementing the invention, a basis is provided for more reliably and accurately controlling the air supplementing process in the practical engineering application, reducing the vibration of the unit and improving the running stability.
Description
Technical Field
The invention relates to the technical field of water and electricity, in particular to a method, a device, a control system and a storage medium for controlling the air supplementing quantity of a water turbine unit.
Background
In order to meet the purpose of flexibly serving the power grid, the hydropower and electricity-pumping and power-storage station unit is often required to run under a condition deviating from the optimal running condition. Cavitation of the draft tube generated during operation under the bias working condition is an important factor affecting the stable operation range of the hydropower station and the pumping and storing station unit. The cavitation generation and development degree depend on the design condition of the unit and are closely related to the actual operation condition of the power station. In order to reduce stability influence caused by cavitation, the power station usually eliminates vibration by supplementing air to the draft tube after cavitation is generated by the unit, and the adopted air supplementing measures comprise main shaft center hole air supplementing, draft tube cross air supplementing, short tube air supplementing, forced air supplementing and the like to eliminate the vibration. However, excessive make-up will result in reduced turbine efficiency. Because the air supplementing effect and the air supplementing amount are closely related, the reasonable air supplementing amount is necessary to be determined, and the optimal air supplementing effect is monitored, so that the power station is ensured not to reduce the vibration and simultaneously not to cause the efficiency reduction of the unit.
The existing widely adopted large-shaft central hole air supplementing method is characterized in that a vacuum breaking valve is arranged on a large shaft above a rotating wheel, an opening spring of an air valve is controlled according to the pressure difference formed by the vacuum of a central hole and the atmosphere, and then the opening degree of the vacuum breaking valve is controlled to supplement air for a water turbine. However, the optimal air supplementing requirement of each working condition of the water turbine is not considered, and the vacuum damage valve is immersed for a long time, contacts air during air supplementing, and the spring is easy to rust, so that deviation exists between displacement and stressed force, and the air supplementing effect is affected.
Disclosure of Invention
In view of the above, the invention provides a method, a device, a control system and a storage medium for controlling the air supplementing amount of a water turbine unit, so as to solve the problem that the existing air supplementing method does not consider the optimal air supplementing amount requirement of each working condition of the water turbine and has poor air supplementing effect.
In a first aspect, the invention provides a method for controlling the air make-up amount of a water turbine unit, which is used for a control system, wherein the control system is connected with the water turbine unit and comprises a first electrical control device and a second electrical control device; the method comprises the following steps: the second electric control device acquires an operation condition parameter data set of the water turbine unit; the second electrical control device judges whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set; when cavitation occurs in the water turbine unit, acquiring an operation condition cavitation parameter data set of the water turbine unit; when cavitation occurs in the water turbine unit, acquiring an operation condition cavitation parameter data set of the water turbine unit; the second electrical control device obtains the target air supply quantity of the water turbine unit based on the cavitation parameter data set of the operation condition through the processing of a preset air supply quantity prediction model; the second electric control device adjusts the opening value of the first electric control device based on the target air supplementing amount, so that the adjusted first electric control device controls the air supplementing amount of the water turbine unit.
According to the method for controlling the air supplementing quantity of the water turbine unit, the opening value of the second electric control device is regulated through the first electric control device, and the air supplementing quantity of the water turbine unit under the actual operation condition is regulated through the opening of the second electric control device, so that the problems of air supplementing quantity deviation and the like caused by slow action and clamping stagnation of the vacuum breaking valve spring according to pressure difference control are solved. Therefore, by implementing the invention, a basis is provided for more reliably and accurately controlling the air supplementing process in the practical engineering application, reducing the vibration of the unit and improving the running stability.
In an alternative embodiment, the second electrical control device determines, based on the operating condition parameter data set and through a preset cavitation proxy model, whether cavitation occurs in the turbine unit, and the method further includes: acquiring a historical operation condition parameter data set of a water turbine unit; and establishing a preset cavitation proxy model based on the historical operating condition parameter data set.
The invention establishes the preset cavitation proxy model by utilizing the historical operation condition parameter data set of the water turbine unit, and provides a basis for judging the cavitation condition of the subsequent water turbine unit.
In an alternative embodiment, establishing the preset cavitation proxy model based on the historical operating condition parameter dataset includes: determining a first sample data set and a second sample data set based on the historical operating condition parameter data set; performing simulation on the basis of the first sample data set to obtain cavitation numbers in an operation condition change range, wherein the operation condition change range is determined by the first sample data set; determining at least one cavitation volume based on each cavitation number via a first exponential relationship; constructing a second index relation between each historical operating condition parameter and each cavitation volume in the first sample data set; determining an initial cavitation proxy model based on the second exponential relationship; and verifying the initial cavitation proxy model by using the second sample data set to obtain a preset cavitation proxy model.
The invention establishes the preset cavitation proxy model through the second index relation between the operation condition parameters and the cavitation volume, so that the established preset cavitation proxy model can reflect the relation between the operation condition and the cavitation volume.
In an alternative embodiment, the second electrical control device determines, based on the operating condition parameter data set, whether cavitation occurs in the turbine unit through a preset cavitation proxy model, including: inputting the operation condition parameter data set into a preset cavitation proxy model for simulation calculation to obtain cavitation volume corresponding to each operation condition parameter in the operation condition parameter data set; and judging whether cavitation occurs in the water turbine unit or not based on each cavitation volume.
According to the invention, through the combination of the actual operation condition parameter data and cavitation simulation calculation, the cavitation volume of the water turbine unit can be obtained based on the real-time operation condition parameter data through simulation analysis, and whether cavitation occurs in the water turbine unit or not is judged by utilizing the cavitation volume, so that the problem that the real sensor cannot monitor the cavitation condition in the water turbine runner is effectively solved.
In an optional embodiment, before the second electrical control device obtains the target air supply amount of the water turbine set through processing of the preset air supply amount prediction model based on the cavitation parameter data set of the operation working condition, the method further includes: acquiring a cavitation parameter data set of historical operation conditions of the water turbine unit; and establishing a preset air supplementing quantity prediction model based on the cavitation parameter data set of the historical operation working condition.
The invention establishes the preset air supplementing quantity prediction model by utilizing the historical operation condition cavitation parameter data set of the water turbine unit, and provides a basis for the air supplementing operation of the subsequent water turbine unit.
In an alternative embodiment, the method for establishing the preset air supplementing quantity prediction model based on the cavitation parameter data set of the historical operation condition comprises the following steps: determining a first training data set and a second training data set based on the historical operating condition cavitation parameter data set; establishing a first air supplement quantity prediction model based on the first training data set; determining a first air supplementing amount based on a first air supplementing amount prediction model through preset conditions; establishing a second air supplement prediction model based on the first air supplement and the first training data set; and verifying the second air supplementing quantity prediction model by using the second training data set to obtain a preset air supplementing quantity prediction model, wherein the preset air supplementing quantity prediction model reflects the relation among the air supplementing quantity, the cavitation parameters of the operation working condition, the cavitation volume and the efficiency of the water turbine unit.
The preset air supplementing quantity prediction model established by the invention can reflect the relation among the air quantity, cavitation parameters of the operation working condition, cavitation volume and efficiency of the hydro-turbine unit, and provides a basis for determining the air supplementing quantity of the hydro-turbine unit according to the operation working condition.
In an alternative embodiment, the second electrical control device obtains the target air supply amount of the water turbine set based on the cavitation parameter data set of the operation condition through the processing of a preset air supply amount prediction model, and the method comprises the following steps: respectively inputting the operation condition cavitation parameter data set into a preset cavitation agent model and a preset air supplementing quantity prediction model to obtain cavitation volumes and second air supplementing quantities corresponding to each operation condition cavitation parameter in the operation condition cavitation parameter data set; based on preset judgment conditions, establishing a sensitivity relation between the cavitation volume and the second air supplementing amount; and determining the target air supplementing quantity of the water turbine unit based on the sensitivity relational expression and a preset air supplementing quantity prediction model.
According to the invention, through the combination of the cavitation parameter data of the actual operation condition and the air supplementing simulation calculation, the cavitation parameter data of the real operation condition can be based on real time, the cavitation volume and the second air supplementing amount of the water turbine unit can be obtained through simulation, the problem that the real sensor cannot monitor the air supplementing effect in the water turbine runner is effectively solved, and a more effective basis is provided for reasonably and quickly determining the target air supplementing amount on site.
In an alternative embodiment, determining the target make-up amount for the water turbine set based on the sensitivity relationship and the preset make-up amount prediction model includes: when the void volume is zero, determining a third air supplement amount based on the sensitivity relationship; based on the third air supplementing quantity, judging whether the efficiency of the water turbine set is improved or not through a preset air supplementing quantity prediction model; when the efficiency of the water turbine unit is improved, determining the third air supplementing amount as a target air supplementing amount; and when the efficiency of the water turbine unit is reduced, adjusting the third air supplementing amount until the cavitation volume and the efficiency meet the preset requirements, and obtaining the target air supplementing amount.
According to the invention, the air supplementing quantity of the hydroelectric generating set is regulated by using a sensitivity relational expression reflecting the relation between the cavitation volume and the air supplementing quantity and a preset air supplementing quantity prediction model, and the air supplementing effect is judged in real time, so that the influence of insufficient air supplementing or excessive air supplementing on the stability and efficiency of the generating set is avoided.
In an optional embodiment, the second electrical control device is processed by a preset cavitation proxy model and a preset air supply quantity prediction model based on the cavitation parameter data set of the operation working condition, and after the target air supply quantity of the water turbine unit is obtained, the method further comprises: and judging whether the target air supplementing quantity meets the preset air supplementing quantity requirement or not based on the operation condition parameter data set.
The invention judges whether the target air supply quantity meets the preset air supply quantity requirement by utilizing the cavitation parameter data set of the real-time operation working condition, and solves the problem that the operation of the unit is influenced because the target air supply quantity does not meet the preset air supply quantity requirement.
In an alternative embodiment, based on the operating condition parameter data set, determining whether the target air supply meets a preset air supply requirement includes: cavitation simulation is carried out based on the operation condition parameter data set, so that the target efficiency of the water turbine unit corresponding to each operation condition parameter in the operation condition parameter data set is obtained; adjusting the target air supply quantity according to preset conditions, and performing air supply simulation calculation based on the adjusted target air supply quantity to obtain cavitation volume and efficiency corresponding to each adjusted target air supply quantity; judging whether the cavitation volume is zero; when the void volume is zero, comparing the efficiency with the target efficiency; when the efficiency is greater than or equal to the target efficiency, determining that the target air supplementing amount meets the preset air supplementing amount requirement; when the efficiency is smaller than the target efficiency, determining that the target air supplementing quantity does not meet the preset air supplementing quantity requirement.
According to the invention, the real-time operation condition cavitation parameter data set is utilized for on-site debugging and checking, and whether the target air supply quantity meets the preset air supply quantity requirement is determined based on the on-site debugging and checking result, so that the influence of insufficient air supply or excessive air supply on the stability and efficiency of the unit is avoided, and the air supply quantity control precision is improved.
In a second aspect, the invention provides a water turbine set air make-up control device, which is used for a control system, wherein the control system is connected with a water turbine set and comprises a first electrical control device and a second electrical control device; the device comprises: the first acquisition module is used for acquiring an operation condition parameter data set of the water turbine unit by the second electric control device; the judging module is used for judging whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set by the second electric control device; the second acquisition module is used for acquiring an operation condition cavitation parameter data set of the water turbine unit when cavitation occurs in the water turbine unit; the processing module is used for processing the cavitation parameter data set based on the operation working condition by the second electric control device through a preset air supplementing quantity prediction model to obtain the target air supplementing quantity of the water turbine unit; and the adjusting and controlling module is used for adjusting the opening value of the first electric control device by the second electric control device based on the target air supplementing amount, so that the adjusted first electric control device controls the air supplementing amount of the water turbine unit.
According to the hydraulic turbine set air supplementing quantity control device, the opening value of the second electric control device is adjusted through the first electric control device, and further, the air supplementing quantity of the hydraulic turbine set under the actual operation condition is adjusted through the opening of the second electric control device, so that the problems of air supplementing quantity deviation and the like caused by slow action and clamping stagnation of the vacuum breaking valve spring according to pressure difference control are solved. Therefore, by implementing the invention, a basis is provided for more reliably and accurately controlling the air supplementing process in the practical engineering application, reducing the vibration of the unit and improving the running stability.
In a third aspect, the present invention provides a control system for executing the method for controlling the air make-up amount of the water turbine set according to the first aspect or any one of the embodiments corresponding to the first aspect; the system is connected with the water turbine unit; the system comprises: the first electric control device is used for acquiring an operation condition parameter data set of the water turbine unit, processing the operation condition parameter data set through a preset cavitation proxy model and a preset air supplementing quantity prediction model based on the operation condition parameter data set to obtain a target air supplementing quantity of the water turbine unit, and controlling an opening value of the second electric control device based on the target air supplementing quantity; and the second electric control device is used for controlling the air supplementing quantity of the water turbine unit.
According to the control system provided by the invention, the opening value of the second electric control device is regulated by using the first electric control device, and further, the air supplementing quantity of the water turbine set under the actual running condition is regulated by using the opening of the second electric control device, so that the problems of air supplementing quantity deviation and the like caused by slow action and clamping stagnation of the vacuum breaking valve spring according to pressure difference control are solved. Therefore, by implementing the invention, the air supplementing quantity control precision of the water turbine unit is improved.
In an alternative embodiment, the first electrical control device comprises: the data acquisition module is used for acquiring an operation condition parameter data set of the water turbine unit and sending the operation condition parameter data set to the data analysis module; the data analysis module is used for judging whether cavitation occurs in the water turbine unit or not based on the operation condition parameter data set through a preset cavitation proxy model, acquiring the operation condition cavitation parameter data set of the water turbine unit when cavitation occurs in the water turbine unit, and sending the operation condition cavitation parameter data set to the air supplementing quantity prediction module; the air supplementing quantity prediction module is used for obtaining the target air supplementing quantity of the water turbine unit based on the cavitation parameter data set of the operation working condition through the processing of a preset air supplementing quantity prediction model and sending the target air supplementing quantity to the control module; and the control module is used for adjusting the opening value of the first electric control device based on the target air supplementing amount.
According to the invention, the data acquisition module, the data analysis module, the air supplementing quantity prediction module and the control module are arranged in the first electric control device, so that the opening value of the second electric control device is adjusted, and a data basis is provided for the subsequent second electric control device to control the air supplementing quantity of the hydroelectric generating set.
In an alternative embodiment, the first electrical control device further comprises: the storage module is used for receiving and storing the operation condition cavitation parameter data set sent by the data analysis module and the target air supplementing quantity sent by the air supplementing quantity prediction module.
According to the invention, the cavitation parameter data set of the operation condition and the target air supplementing quantity are stored through the storage module, so that a basis is provided for air supplementing quantity control of a subsequent water turbine unit.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the method for controlling the air make-up amount of a hydraulic turbine unit according to the first aspect or any one of the embodiments corresponding thereto.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of a control system according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for controlling the make-up air quantity of a water turbine set according to an embodiment of the invention;
FIG. 3 is a flow chart of another method for controlling the make-up air supply of a hydraulic turbine according to an embodiment of the present invention;
FIG. 4 is a flow chart of a method for controlling the make-up air supply of a water turbine set according to an embodiment of the invention;
FIG. 5 is a flow chart of a method for controlling the make-up air supply of a water turbine set according to an embodiment of the invention;
fig. 6 is a schematic structural view of an air make-up control device according to an embodiment of the present invention;
fig. 7 is a block diagram of a configuration of a water turbine set air make-up control device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the most adopted mode of supplementing air to the central hole of the large shaft or supplementing air to the water outlet side of the blade on the top cover of the water turbine through the decompression hole is adopted by the power station. When the vacuum formed in the tail water taper pipe of the water turbine reaches a certain degree, the air compensating valve is automatically opened under the suction force of the vacuum, and the outside air directly enters the lower cavity of the rotating wheel through the valve channel and the central hole of the main shaft, so that the vortex belt in the tail water taper pipe is damaged, and the purposes of reducing the vibration and noise of a unit and reducing the cavitation of the water turbine are achieved. When the vacuum degree is weakened to a certain degree, the air supplementing valve is automatically closed, and air is not supplemented into the draft tube. However, in the field operation process, the problem that the air compensating valve is deformed due to larger impact in the opening and closing process, the air compensating noise is overlarge and the service life is shortened often occurs.
There are also methods in which researchers add an electric control regulating valve to the air intake pipe of the vacuum breaking valve, or separately install the electric control regulating valve to the air intake pipe, and control the air supply amount by means of an electric control regulating control cabinet. However, when the device is operated on site, the requirements of different working conditions on the air supplementing quantity are different, and the effect of air supplementing on eliminating vortex strips cannot be accurately monitored by adopting the existing vacuum breaking valve or the electric control valve. Therefore, a more reasonable method for controlling the air supplementing quantity is needed to be researched by combining the actual operation condition of the site, and an effective basis is provided for controlling the stability of the on-site operation unit.
According to an embodiment of the present invention, there is provided an embodiment of a method for controlling the make-up air quantity of a water turbine set, it being noted that the steps shown in the flowcharts of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that herein.
In the present embodiment, a method for controlling the air make-up amount of a water turbine unit is provided, which can be used for controlling a system 1, wherein, as shown in fig. 1, the control system 1 is connected with a water turbine unit 2, and the control system 1 comprises a first electrical control device 11 and a second electrical control device 12. Fig. 2 is a flowchart of a method for controlling the air make-up amount of a water turbine set according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes the steps of:
in step S201, the second electrical control device obtains an operating condition parameter data set of the hydraulic turbine unit.
Wherein the operation condition parameter data set represents the parameter set of the water turbine set under the real-time condition and can comprise the inlet and outlet pressure P of the water turbine set in And P out Upstream water level H up Tail water level H tail Parameters such as the operating load P and the flow Q.
Specifically, the second electrical control device 12 may be utilized to obtain the operating condition parameter data set of the hydraulic turbine unit in real time.
Step S202, the second electrical control device judges whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set.
The running condition parameter data set can reflect real-time running conditions of the hydropower station unit under different working conditions, further, the pre-established preset cavitation agent model is utilized to carry out simulation analysis on the running condition parameter data set, and whether cavitation of the hydropower station unit occurs under the current running condition can be judged according to simulation analysis results.
And step S203, when cavitation occurs in the water turbine unit, acquiring an operation condition cavitation parameter data set of the water turbine unit.
The operating condition cavitation parameter data set may include, among other things, the location at which cavitation occurs, the cavitation volume, and the like.
Specifically, if cavitation of the water turbine unit under the current operation working condition can be determined through judgment, an operation working condition cavitation parameter data set corresponding to the cavitation working condition of the water turbine unit is obtained.
Step S204, the second electrical control device obtains the target air supply quantity of the water turbine unit through the processing of a preset air supply quantity prediction model based on the cavitation parameter data set of the operation working condition.
Specifically, the working condition of cavitation of the water turbine unit is subjected to air supply simulation analysis by utilizing a pre-established preset air supply prediction model, so that the optimal air supply required by the cavitation water turbine unit, namely the target air supply, can be obtained.
In step S205, the second electrical control device adjusts the opening value of the first electrical control device based on the target air supply amount, so that the adjusted first electrical control device controls the air supply amount of the water turbine set.
Specifically, the first electrical control device 11 may control the air make-up of the water turbine set.
Further, in combination with the target air supply amount required by the water turbine unit, the second electrical control device 12 is used for controlling the opening value of the first electrical control device 11, so that the first electrical control device 11 can control the air supply amount of the water turbine unit in real time according to the target air supply amount required by the water turbine unit, for example, when the target air supply amount is greater than the air supply amount of the water turbine unit, the second electrical control device 12 controls the opening of the first electrical control device 11 to increase, and otherwise decrease.
Through the adjusting process, the problems of air supplementing quantity deviation and the like caused by slow action and clamping stagnation of the vacuum breaking valve spring according to pressure difference control are solved.
According to the method for controlling the air supplementing quantity of the water turbine unit, the opening value of the second electric control device is adjusted through the first electric control device, and further, the air supplementing quantity of the water turbine unit under the actual operation condition is adjusted through the opening of the second electric control device, so that the problems of air supplementing quantity deviation and the like caused by slow action and clamping stagnation of the vacuum breaking valve spring according to pressure difference control are solved. Therefore, by implementing the invention, a basis is provided for more reliably and accurately controlling the air supplementing process in the practical engineering application, reducing the vibration of the unit and improving the running stability.
In this embodiment, a method for controlling the air make-up amount of a water turbine unit is provided, which can be used for controlling a system 1, wherein, as shown in fig. 1, the control system 1 is connected with the water turbine unit, and the control system 1 includes a first electrical control device 11 and a second electrical control device 12. FIG. 3 is a flowchart of a method for controlling the air make-up of a water turbine set according to an embodiment of the invention, as shown in FIG. 3, the flowchart including the steps of:
in step S301, the second electrical control device obtains an operating condition parameter data set of the hydraulic turbine unit. Please refer to step S201 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S302, acquiring a historical operation condition parameter data set of the water turbine unit.
Specifically, the historical operation condition parameter data set of the hydraulic turbine unit represents a parameter data set of the hydraulic turbine unit under the historical operation condition, and specific data refer to the operation condition parameter data set in step S101, which is not described herein.
Step S303, a preset cavitation proxy model is established based on the historical operating condition parameter data set.
Specifically, the step S303 includes:
step S3031, a first sample data set and a second sample data set are determined based on the historical operating condition parameter data set.
Specifically, an extreme value (e.g., inlet-outlet pressure P) is selected from the historical operating condition parameter dataset in And P out Upstream water level H up Tail water level H tail Maximum and minimum extreme values of parameters such as the running load P and the flow Q) as the number of learning samplesAccording to the first sample data set is generated based on the learning sample data. The generating method may be a method based on orthogonal design, full factor design, latin hypercube sampling design, etc., which is not specifically limited in the embodiment of the present invention, as long as the requirement is satisfied.
Further, the remaining operating condition parameter data is used as a second sample data set.
Step S3032, carrying out simulation based on the first sample data set to obtain the cavitation number in the operating condition variation range.
Wherein the operating condition variation range is determined by the first sample data set; cavitation numbers represent dimensionless parameters describing cavitation conditions, and may reflect the extent of cavitation.
Specifically, a first sample data set is utilized to carry out simulation, so that the cavitation number in the operating condition variation range can be obtained.
Step S3033, determining at least one cavitation volume based on each cavitation number via a first exponential relationship.
The first exponential relation reflects the corresponding relation between the cavitation number and the cavitation volume, namely, the relation between the cavitation number and the cavitation volume is an exponential relation under different flow rates.
Specifically, through the first exponential relationship, a cavitation volume corresponding to each cavitation number within the operating condition variation range may be obtained.
In step S3034, a second index relationship between each historical operating condition parameter and each cavitation volume in the first sample data set is constructed.
Specifically, the second index relation is shown in the following relation (1):
wherein: ρ represents the density of water; g represents gravitational acceleration; p (P) v Representing the saturated vapor pressure value at the current temperature; η represents the efficiency of the hydroelectric generating set.
Step S3035, an initial cavitation proxy model is determined based on the second index relationship.
Specifically, an initial cavitation proxy model may be constructed according to the above relation (1), as shown in the following relation (2):
V＝k 1 +k 2 *exp(-k 3 σ) (2)
wherein: v represents cavitation volume; k (k) 1 、k 2 、k 3 The representation coefficients may be determined from the turbine set.
Step S3036, the initial cavitation proxy model is verified by using the second sample data set, and the preset cavitation proxy model is obtained.
Specifically, the second sample dataset is used to verify the initial cavitation proxy model and to analyze and improve the accuracy and robustness of the initial cavitation proxy model. If the verification data error is large, the verification data is added to the first sample data set, and the step S201 is repeated to select calibration data.
Further, a preset cavitation proxy model v=f (P out ,H tail P, Q, eta), i.e., the preset cavitation proxy model may reflect the operating condition parameters (P out 、H tail P, Q), cavitation volume V and turbine group efficiency η.
Step S304, the second electrical control device judges whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set.
Specifically, the operation condition parameter data set is input into a preset cavitation proxy model, so that a corresponding cavitation simulation result can be obtained, and further, whether cavitation occurs in the water turbine unit under the current working condition can be judged according to the cavitation simulation result.
Specifically, the step S304 includes:
step S3041, inputting the operation condition parameter data set into a preset cavitation proxy model for simulation calculation, and obtaining the cavitation volume corresponding to each operation condition parameter in the operation condition parameter data set.
Specifically, the operating condition parameter data (P out 、H tail P, Q, etc.) to a preset cavitation proxy model v=f (P) out ,H tail P, Q, eta) to carry out cavitation simulation calculation, and the cavitation volume V of the water turbine unit under different operation conditions can be obtained.
And step S3042, judging whether cavitation occurs in the water turbine unit or not based on each cavitation volume.
Specifically, according to cavitation volumes V of the water turbine unit under different operation conditions, whether cavitation of the water turbine unit occurs under the current working condition can be judged. For example, when the cavitation volume V exceeds a certain range, cavitation of the water turbine unit is determined.
Step S305, when cavitation occurs in the water turbine unit, an operation condition cavitation parameter data set of the water turbine unit is obtained. Please refer to step S203 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S306, the second electrical control device obtains the target air supply quantity of the water turbine unit based on the cavitation parameter data set of the operation condition through the processing of a preset air supply quantity prediction model. Please refer to step S204 in the embodiment shown in fig. 2 in detail, which is not described herein.
In step S307, the second electrical control device adjusts the opening value of the first electrical control device based on the target air supply amount, so that the adjusted first electrical control device controls the air supply amount of the water turbine set. Please refer to step S205 in the embodiment shown in fig. 2 in detail, which is not described herein.
According to the method for controlling the air supplementing quantity of the water turbine unit, through the combination of the actual operation condition parameter data and the cavitation simulation calculation, the cavitation volume of the water turbine unit can be obtained based on the real-time operation condition parameter data through simulation analysis, and whether cavitation occurs in the water turbine unit or not is judged by utilizing the cavitation volume, so that the problem that a real sensor cannot monitor cavitation conditions in a water turbine runner is effectively solved.
In this embodiment, a method for controlling the air make-up amount of a water turbine unit is provided, which can be used for controlling a system 1, wherein, as shown in fig. 1, the control system 1 is connected with the water turbine unit, and the control system 1 includes a first electrical control device 11 and a second electrical control device 12. Fig. 4 is a flowchart of a method for controlling the air make-up amount of a water turbine set according to an embodiment of the present invention, as shown in fig. 4, the flowchart includes the steps of:
in step S401, the second electrical control device obtains an operating condition parameter data set of the hydraulic turbine unit. Please refer to step S201 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S402, the second electrical control device judges whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set. Please refer to step S304 in the embodiment shown in fig. 3 in detail, which is not described herein.
Step S403, when cavitation occurs in the water turbine unit, acquiring a cavitation parameter data set of the operation condition of the water turbine unit. Please refer to step S203 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S404, acquiring a cavitation parameter data set of historical operation conditions of the water turbine unit.
Specifically, the historical operating condition cavitation parameter data set of the water turbine unit represents a parameter data set of cavitation of the water turbine unit under the historical operating condition.
Step S405, a preset air supplementing quantity prediction model is established based on the cavitation parameter data set of the historical operation working condition.
Specifically, the step S405 includes:
step S4051, determining a first training data set and a second training data set based on the historical operating condition cavitation parameter data set.
Specifically, according to the difference of the requirements of different working conditions on the air supplementing amount, 60% -80% of working condition cavitation parameters are selected from the historical operation working condition cavitation parameter data set to serve as a first training data set, and further, the remaining working condition cavitation parameter data are taken as a second training data set.
Step S4052, a first air supply quantity prediction model is established based on the first training data set.
Specifically, a first air supply quantity prediction model is generated by training with a first training data set.
Step S4053, determining the first air supply amount based on the first air supply amount prediction model through a preset condition.
And determining the air supplementing quantity corresponding to the working condition that the cavitation volume is zero after air supplementing and the efficiency of the water turbine unit is highest as the optimal air supplementing quantity, namely the first air supplementing quantity.
Specifically, the working condition parameters are input into the first air supplementing quantity prediction model, and when cavitation volume is zero and the efficiency of the water turbine unit is highest after air supplementing is carried out by using the air supplementing quantity output by the first air supplementing quantity prediction model, the air supplementing quantity output by the first air supplementing quantity prediction model is used as the first air supplementing quantity.
Step S4054, a second air supply prediction model is established based on the first air supply and the first training data set.
Specifically, a second air supplementing quantity prediction model is generated according to training by using the first training data set and the first air supplementing quantity, namely the second air supplementing quantity prediction model can reflect the relation among working condition cavitation parameters, cavitation volume and air supplementing quantity.
Step S4055, verifying the second air supplement quantity prediction model by using the second training data set to obtain a preset air supplement quantity prediction model.
Specifically, the accuracy and robustness of the second air make-up prediction model is analyzed using the remaining second training dataset. If the error of the verification data is too large, adding the verification data into the cavitation parameter data set of the historical operation working condition, and re-learning to generate a second air supplementing quantity prediction model, namely returning to the step S4051 until the accuracy and the robustness of the obtained second air supplementing quantity prediction model meet the requirements, and taking the second air supplementing quantity prediction model meeting the requirements as a preset air supplementing quantity prediction model Q air ～f(P in ,P out ,H tail P, Q, V, η). Further, the working condition cavitation parameter is an operation working condition parameter when cavitation occurs, so the preset air supplementing quantity prediction model can reflect the air supplementing quantity Q air And operating condition parameters (P) in 、P out 、H tail P, Q), cavitation volume V and turbine group efficiency η.
In step S406, the second electrical control device obtains the target air supply amount of the water turbine unit through processing by a preset air supply amount prediction model based on the cavitation parameter data set of the operation condition.
Specifically, the step S406 includes:
step S4061, the operation condition cavitation parameter data set is respectively input into a preset cavitation agent model and a preset air supplementing quantity prediction model, and a cavitation volume and a second air supplementing quantity corresponding to each operation condition cavitation parameter in the operation condition cavitation parameter data set are obtained.
Specifically, the cavitation parameter data set of the corresponding operation working condition when cavitation occurs is input into a preset cavitation proxy model V=f (P out ,H tail And P, Q, eta), namely according to the relation (2), the cavitation volume V corresponding to cavitation under different working conditions under which cavitation occurs can be obtained.
Further, the air supplementing simulation calculation is carried out on different cavitation working conditions, namely the cavitation parameter data set of the operation working conditions is input into a preset air supplementing quantity prediction model Q air ～f(P in ,P out ,H tail The air supplementing quantity required by the water turbine set under different working conditions when cavitation occurs, namely a second air supplementing quantity Q, can be obtained air 。
Step S4062, based on the preset judgment conditions, establishing a sensitivity relation between the cavitation volume and the second air supplementing amount.
Specifically, in general, the minimum air supplementing amount for reducing cavitation should be not less than 0.5% of the flow rate and should be less than 3% of the flow rate, so that the air supplementing amount Q is established by taking the cavitation volume of the operation condition as zero as a judgment standard air The sensitivity relationship with cavitation volume V is shown in the following relationship (3):
0.5％Q≤Q air ＝k 4 f(V)≤3％Q (3)
wherein: k (k) 4 The representation coefficients may be determined from the turbine set.
And step S4063, determining the target air supply quantity of the water turbine unit based on the sensitivity relation and a preset air supply quantity prediction model.
In some alternative embodiments, step S4063 includes:
and a step a1, when the void volume is zero, determining a third air supplementing amount based on the sensitivity relation.
And a step a2, based on the third air supplementing quantity, judging whether the efficiency of the water turbine unit is improved or not through a preset air supplementing quantity prediction model.
And a3, when the efficiency of the water turbine unit is improved, determining the third air supplementing amount as the target air supplementing amount.
And a4, when the efficiency of the water turbine unit is reduced, adjusting the third air supplementing amount until the cavitation volume and the efficiency meet the preset requirements, and obtaining the target air supplementing amount.
First, when the cavitation volume V decreases to zero, a third air supplementing amount Q is determined according to the above-mentioned relation (3) air 。
Next, determining the third air supplementing amount Q air Under the action of the water turbine unit, whether the efficiency eta of the water turbine unit is improved. Wherein, the air supplementing quantity Q can be reflected air And operating condition parameters (P) in 、P out 、H tail P, Q), the relation between the cavitation volume V and the efficiency eta of the water turbine unit, and determining a third air supplementing quantity Q by a preset air supplementing quantity prediction model air The efficiency eta of the corresponding water turbine set.
Finally, if the efficiency eta of the water turbine set is improved, the current third air supplementing quantity Q is represented air Is a recommended value, namely a target air supplementing amount; if the efficiency eta of the water turbine unit is reduced, the current third air supplementing quantity Q is represented air Is not the recommended value, at this time, the third air supplementing quantity Q is gradually reduced air Up to the reduced third air supplementing quantity Q air The corresponding cavitation volume V and the efficiency eta of the water turbine set meet the requirements, and the corresponding third air supplementing quantity Q air As a target make-up amount.
In step S407, the second electrical control device adjusts the opening value of the first electrical control device based on the target air supply amount, so that the adjusted first electrical control device controls the air supply amount of the water turbine unit. Please refer to step S205 in the embodiment shown in fig. 2 in detail, which is not described herein.
According to the method for controlling the air supplementing quantity of the water turbine unit, through the combination of the cavitation parameter data of the actual operation working condition and the air supplementing simulation calculation, the cavitation parameter data of the real operation working condition can be obtained in a simulation mode, the cavitation volume and the second air supplementing quantity of the water turbine unit can be obtained, the problem that a real sensor cannot monitor the air supplementing effect in a water turbine runner is effectively solved, and more effective basis is provided for reasonably and quickly determining the target air supplementing quantity on site. Meanwhile, the air supplementing quantity of the hydroelectric generating set is regulated by using a sensitivity relational expression reflecting the relation between the cavitation volume and the air supplementing quantity and a preset air supplementing quantity prediction model, and the air supplementing effect is judged in real time, so that the influence of insufficient air supplementing or excessive air supplementing on the stability and efficiency of the generating set is avoided, and the air supplementing quantity control precision is improved.
In this embodiment, a method for controlling the air make-up amount of a water turbine unit is provided, which can be used for controlling a system 1, wherein, as shown in fig. 1, the control system 1 is connected with the water turbine unit, and the control system 1 includes a first electrical control device 11 and a second electrical control device 12. FIG. 5 is a flowchart of a method for controlling the air make-up of a water turbine set according to an embodiment of the invention, as shown in FIG. 5, the flowchart including the steps of:
in step S501, the second electrical control device obtains an operating condition parameter data set of the hydraulic turbine unit. Please refer to step S201 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S502, the second electrical control device judges whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set. Please refer to step S304 in the embodiment shown in fig. 3 in detail, which is not described herein.
Step S503, when cavitation occurs in the water turbine unit, acquiring a cavitation parameter data set of the operation condition of the water turbine unit. Please refer to step S203 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S504, the second electrical control device obtains the target air supply quantity of the water turbine unit based on the cavitation parameter data set of the operation condition through the processing of a preset air supply quantity prediction model. Please refer to step S406 in the embodiment shown in fig. 4 in detail, which is not described herein.
In step S505, the second electrical control device adjusts the opening value of the first electrical control device based on the target air supply amount, so that the adjusted first electrical control device controls the air supply amount of the water turbine set. Please refer to step S205 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S506, based on the operation condition parameter data set, judging whether the target air supplementing quantity meets the preset air supplementing quantity requirement.
Specifically, the step S506 includes:
step S5061, cavitation simulation is performed based on the operation condition parameter data set, and the target efficiency of the water turbine unit corresponding to each operation condition parameter in the operation condition parameter data set is obtained.
Specifically, cavitation simulation is carried out in real time based on an operation condition parameter data set, and target efficiency eta of the water turbine unit when the current operation condition is not supplemented with air is recorded 0 。
Step S5062, adjusting the target air supply amount according to preset conditions, and performing air supply simulation calculation based on the adjusted target air supply amount to obtain the cavitation volume and the cavitation efficiency corresponding to each adjusted target air supply amount.
Specifically, the target air supplementing amount is taken as a reference, the air supplementing amount is increased or reduced by 10% every 5 minutes, and cavitation simulation calculation is carried out, so that the cavitation volume and the cavitation efficiency corresponding to the adjusted target air supplementing amount can be obtained.
In step S5063, it is determined whether the cavitation volume is zero.
Specifically, whether the cavitation volume corresponding to the adjusted target air supply amount is zero is judged.
In step S5064, when the void volume is zero, the efficiency is compared with the target efficiency.
Specifically, if the cavitation volume corresponding to the adjusted target air supplementing amount is zero, the current efficiency and the target efficiency eta of the water turbine unit are further compared 0 。
Further, if the cavitation volume corresponding to the adjusted target air supply is not zero, the target air supply is continuously adjusted according to the preset condition until the cavitation volume corresponding to the adjusted target air supply is zero.
In step S5065, when the efficiency is greater than or equal to the target efficiency, it is determined that the target air supply meets the preset air supply requirement.
Specifically, if the current efficiency of the water turbine set is greater than or equal to the target efficiency η 0 The target air supplementing amount is the optimal air supplementing amount Q after the calibration of the current working condition airopt I.e. the target air supply meets the requirement of the preset air supply.
Further, the current operating condition and the target air supplementing data are stored.
In step S5066, when the efficiency is less than the target efficiency, it is determined that the target air supply does not meet the preset air supply requirement.
Specifically, if the current efficiency of the water turbine set is less than the target efficiency η 0 Indicating that the current target air supply is not the optimal air supply Q after the current working condition calibration airopt I.e. the target air supply does not meet the preset air supply requirement. Further, the step S401 is returned until the obtained target air supply meets the preset air supply requirement.
According to the method for controlling the air supply quantity of the water turbine unit, the real-time operation condition cavitation parameter data set is utilized for on-site debugging and checking, whether the target air supply quantity meets the preset air supply quantity requirement is determined based on the on-site debugging and checking result, the influence of insufficient air supply or excessive air supply on the stability and efficiency of the unit is avoided, and the air supply quantity control precision is improved.
In an example, a method for controlling the opening of an electrical control valve based on real-time cavitation simulation to adjust the air make-up amount according to the operation condition is provided, which is used in an air make-up control device as shown in fig. 6, and includes:
1. as shown in fig. 6, an electric control valve is installed in the main shaft center hole air supplementing pipeline of the on-site water turbine of the power station, and the electric control valve increases or decreases the opening degree according to the instruction to adjust the air supplementing amount.
2. The electric control cabinet sends out instructions to operate the opening degree of the electric control valve. As shown in fig. 6, the electrical control cabinet includes five modules, wherein the first module is an on-site acquisition module, and unit operation condition data is obtained. And the second module is a data analysis and cavitation simulation visualization module, which adopts a cavitation proxy model to carry out simulation analysis and judges whether cavitation occurs in the current working condition. And the third module is a gas supplementing quantity prediction module, and if cavitation occurs, the working condition data are transmitted to the module for gas supplementing quantity prediction analysis. And the fourth module is an electric control valve action module, wherein an electric control air compensating valve opening signal is from air compensating quantity prediction model data, and the air compensating valve opening is controlled according to the air compensating quantity data. And the fifth module is a memory module for storing the operation condition, the corresponding cavitation volume and the optimal air supplementing amount.
3. The construction of the cavitation proxy model comprises the following steps:
3.1, acquiring operation condition parameters: and acquiring field operation condition information data of the unit based on a sensor, a monitoring system and the like, and establishing an actual operation condition database.
3.2, simulating and analyzing cavitation development according to different operation condition parameters: according to the actual operation working condition database, working condition data including extreme values in the database are selected as learning sample data, and training data for cavitation simulation calculation is generated. And carrying out cavitation simulation calculation and analyzing the sensitivity relation of cavitation volume change of each operation condition.
3.3, constructing a cavitation agent model: and obtaining cavitation volume within the range of the operating condition based on the learning sample data, and constructing a proxy reduced-order response model of the unit operating condition parameters and cavitation development degree.
3.4, verifying cavitation prediction agent model: and verifying the cavitation model by adopting residual training data, and analyzing and improving the accuracy and the robustness of the simulation model. If the verification data has larger error, adding the verification data into the learning sample, returning to the work of constructing the learning scene to generate the cavitation proxy model in step 3 again, and selecting the calibration data. And after calibration, preserving a cavitation proxy model, and establishing a working condition database for generating cavitation.
4. The construction of the air supplementing prediction model comprises the following steps:
and 4.1, establishing a relation between cavitation and air supplementing quantity of the operation working condition. And (3) based on the cavitation-generating working condition database and the cavitation proxy model generated in the step (4), developing cavitation simulation calculation under the action of the change of the air supplementing quantity of different working conditions, and analyzing the sensitivity relation between the air supplementing quantity and the operating working condition parameters, the cavitation volume and the efficiency.
4.2, constructing a cavitation and operation condition air supplementing quantity prediction model: according to the difference of the requirements of different working conditions on the air supplementing quantity, the air supplementing quantity when the cavitation volume of each working condition is zero and the efficiency is highest is obtained based on simulation analysis to be the recommended air supplementing quantity.
4.3, preliminarily checking a cavitation and operation condition air supplementing quantity prediction model: and analyzing the accuracy and the robustness of the air supplementing quantity prediction model by adopting the residual cavitation working condition database data. If the error of the verification data is too large, the verification data is added into a learning sample, and the work of generating the air supplement quantity prediction model through learning is performed again. And establishing and storing a preliminary prediction model of the relation between the cavitation volume and the air supplementing quantity of the operation working condition.
4.4 on-site verification cavitation and operation condition air supplementing quantity prediction model: performing operation condition cavitation real-time simulation based on the cavitation prediction agent model obtained in the step 4 to obtain an operation condition cavitation volume; and obtaining recommended air supplementing quantity required by eliminating cavitation of the current working condition based on the air supplementing quantity prediction model. And (3) on-site setting recommended air supplementing quantity to judge whether the cavitation volume is zero, and if the cavitation volume is zero and the efficiency is not lower than that before air supplementing, recording the air supplementing quantity as the optimal air supplementing quantity after the current working condition calibration. And (5) saving working condition data and air supplementing quantity.
5. And (3) regulating the electric control valve to the corresponding opening degree according to the optimal air supplementing amount obtained in the step (4).
In this embodiment, a control system is provided to execute the method for controlling the air make-up amount of the turbine set in the above embodiment; as shown in fig. 1, the control system 1 includes a first electrical control device 11 and a second electrical control device 12.
One end of the first electric control device 11 is connected to the second electric control device 12, and the other end is connected to the turbine unit 2. In this embodiment, the first electrical control device 11 may be an electrical control valve, and the second electrical control device 12 may be an electrical control cabinet, as shown in fig. 5.
Further, the second electrical control device 12 includes a data acquisition module 121, a data analysis module 122, a ventilation prediction module 123, a control module 124, and a storage module 125.
One end of the data analysis module 122 is connected with the data acquisition module 121, and the other end of the data analysis module is connected with the air supplementing quantity prediction module 123 and the storage module 125 respectively; the other end of the air supplementing quantity prediction module 123 is respectively connected with the control module 124 and the storage module 125.
Further, the functions of the respective devices in the above system are described.
The first electrical control device 11 is used for controlling the air supplementing quantity of the water turbine set 2.
The second electrical control device 12 is configured to obtain an operation condition parameter data set of the water turbine unit, and obtain a target air supply amount of the water turbine unit based on the operation condition parameter data set through processing of a preset cavitation agent model and a preset air supply amount prediction model, and control an opening value of the first electrical control device 11 based on the target air supply amount.
First, the data acquisition module 121 acquires the operating condition parameter data set of the hydraulic turbine unit, and sends the operating condition parameter data set to the data analysis module 122.
Next, the data analysis module 122 determines, based on the operation condition parameter data set, whether cavitation occurs in the turbine unit through the preset cavitation proxy model, and when cavitation occurs in the turbine unit, obtains the operation condition cavitation parameter data set of the turbine unit, and sends the operation condition cavitation parameter data set to the air supply amount prediction module 123.
Then, the air supply prediction module 123 obtains the target air supply of the water turbine set through processing of a preset air supply prediction model based on the cavitation parameter data set of the operation condition, and sends the target air supply to the control module 124.
Finally, the control module 124 adjusts the opening value of the first electrical control device 11 based on the target air make-up amount.
Further, the storage module 125 may also receive and store the operating condition cavitation parameter data set sent by the data analysis module 122 and the target make-up sent by the make-up prediction module 123.
The specific functional description of each module is the same as that of the corresponding embodiment, and is not repeated here.
In this embodiment, a device for controlling the air supply amount of a water turbine unit is further provided, and the device is used for implementing the foregoing embodiments and preferred embodiments, and is not described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The embodiment provides a water turbine set air make-up control device, as shown in fig. 7, includes:
the first obtaining module 701 is configured to obtain an operation condition parameter data set of the water turbine set by using the second electrical control device.
The judging module 702 is configured to judge whether cavitation occurs in the hydraulic turbine unit by using the second electrical control device through a preset cavitation proxy model based on the operating condition parameter data set.
The second acquiring module 703 is configured to acquire a cavitation parameter data set of an operation condition of the water turbine unit when cavitation occurs in the water turbine unit.
And the processing module 704 is used for processing the cavitation parameter data set of the second electrical control device through a preset air supplementing quantity prediction model based on the operation working condition to obtain the target air supplementing quantity of the water turbine unit.
And the adjusting and controlling module 705 is configured to adjust, based on the target air supply amount, the opening value of the first electrical control device by using the second electrical control device, so that the adjusted first electrical control device controls the air supply amount of the water turbine unit.
In some optional embodiments, the above-mentioned water turbine set air make-up control device further includes:
and the third acquisition module is used for acquiring a historical operation condition parameter data set of the water turbine unit.
The first establishing module is used for establishing a preset cavitation agent model based on the historical operating condition parameter data set.
In some alternative embodiments, the first establishing module includes:
and the first determining unit is used for determining a first sample data set and a second sample data set based on the historical operation condition parameter data set.
And the simulation unit is used for performing simulation on the basis of the first sample data set to obtain cavitation numbers in the operating condition change range, wherein the operating condition change range is determined by the first sample data set.
And the second determining unit is used for determining at least one cavitation volume through the first exponential relation based on each cavitation number.
And the construction unit is used for constructing a second index relation between each historical operation condition parameter and each cavitation volume in the first sample data set.
And a third determining unit for determining an initial cavitation proxy model based on the second index relation.
The first verification unit is used for verifying the initial cavitation proxy model by using the second sample data set to obtain a preset cavitation proxy model.
In some alternative embodiments, the determining module 702 includes:
the first simulation calculation unit is used for inputting the operation condition parameter data set into a preset cavitation proxy model for simulation calculation, and obtaining the cavitation volume corresponding to each operation condition parameter in the operation condition parameter data set.
And the first judging unit is used for judging whether cavitation occurs in the water turbine unit or not based on each cavitation volume.
In some optional embodiments, the above-mentioned water turbine set air make-up control device further includes:
and the fourth acquisition module is used for acquiring a cavitation parameter data set of the historical operation working condition of the water turbine unit.
The second building module is used for building a preset air supplementing quantity prediction model based on the cavitation parameter data set of the historical operation working condition.
In some alternative embodiments, the second setup module includes:
and the fourth determining unit is used for determining the first training data set and the second training data set based on the historical operation condition cavitation parameter data set.
The first building unit is used for building a first air supplementing quantity prediction model based on the first training data set.
And a fifth determining unit, configured to determine the first air supply amount based on the first air supply amount prediction model through a preset condition.
The second building unit is used for building a second air supplementing quantity prediction model based on the first air supplementing quantity and the first training data set.
The second verification unit is used for verifying the second air supplementing quantity prediction model by utilizing the second training data set to obtain a preset air supplementing quantity prediction model, and the preset air supplementing quantity prediction model reflects the relation among the air supplementing quantity, the cavitation parameters of the operation working condition, the cavitation volume and the efficiency of the water turbine unit.
In some alternative embodiments, the processing module 704 includes:
the input unit is used for respectively inputting the operation condition cavitation parameter data set into a preset cavitation agent model and a preset air supplementing quantity prediction model to obtain cavitation volumes and second air supplementing quantities corresponding to each operation condition cavitation parameter in the operation condition cavitation parameter data set.
The third establishing unit is used for establishing a sensitivity relation between the cavitation volume and the second air supplementing amount based on a preset judging condition.
And the sixth determining unit is used for determining the target air supplementing quantity of the water turbine unit based on the sensitivity relation and a preset air supplementing quantity prediction model.
In some alternative embodiments, the sixth determining unit includes:
the first determination subunit is configured to determine a third air supplementing amount based on the sensitivity relational expression when the void volume is zero.
And the judging subunit is used for judging whether the efficiency of the water turbine unit is improved.
And the second determination subunit is used for determining the third air supplementing amount as the target air supplementing amount when the efficiency of the water turbine unit is improved.
And the adjusting subunit is used for adjusting the third air supplementing amount until the cavitation volume and the efficiency meet preset requirements when the efficiency of the water turbine unit is reduced, so as to obtain the target air supplementing amount.
In some optional embodiments, the above-mentioned water turbine set air make-up control device further includes:
the first judging module is used for judging whether the target air supplementing quantity meets the preset air supplementing quantity requirement or not based on the operation condition parameter data set.
In some alternative embodiments, the first determining module includes:
the cavitation simulation unit is used for carrying out cavitation simulation based on the operation condition parameter data set to obtain the target efficiency of the water turbine unit corresponding to each operation condition parameter in the operation condition parameter data set.
And the second simulation calculation unit is used for adjusting the target air supply quantity according to preset conditions, and carrying out air supply simulation calculation based on the adjusted target air supply quantity to obtain the cavitation volume and the cavitation efficiency corresponding to each adjusted target air supply quantity.
And the second judging unit is used for judging whether the cavitation volume is zero.
And the comparison unit is used for comparing the efficiency with the target efficiency when the void volume is zero.
And a seventh determining unit, configured to determine that the target air supply amount meets a preset air supply amount requirement when the efficiency is greater than or equal to the target efficiency.
And the eighth determining unit is used for determining that the target air supplementing quantity does not meet the preset air supplementing quantity requirement when the efficiency is smaller than the target efficiency.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The water turbine set air make-up control device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit ) circuit, a processor and a memory executing one or more software or fixed programs, and/or other devices that can provide the above functions.
The embodiment of the invention also provides computer equipment, which is provided with the water turbine set air supplementing quantity control device shown in the figure 7.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (15)
1. The control system is connected with the water turbine unit and comprises a first electrical control device and a second electrical control device; the method comprises the following steps:
the second electric control device acquires an operation condition parameter data set of the water turbine unit;
the second electrical control device judges whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set;
when cavitation occurs in the water turbine unit, acquiring an operation condition cavitation parameter data set of the water turbine unit;
the second electrical control device obtains the target air supply quantity of the water turbine unit through processing of a preset air supply quantity prediction model based on the cavitation parameter data set of the operation working condition;
the second electrical control device adjusts the opening value of the first electrical control device based on the target air supplementing amount, so that the adjusted first electrical control device controls the air supplementing amount of the water turbine set.
2. The method of claim 1, wherein the second electrical control device determines whether cavitation has occurred in the hydro-turbine group based on the operating condition parameter dataset through a preset cavitation proxy model, the method further comprising:
Acquiring a historical operation condition parameter data set of the water turbine unit;
and establishing the preset cavitation proxy model based on the historical operating condition parameter data set.
3. The method of claim 2, wherein establishing the preset cavitation proxy model based on the historical operating condition parameter dataset comprises:
determining a first sample data set and a second sample data set based on the historical operating condition parameter data set;
performing simulation on the basis of the first sample data set to obtain cavitation numbers in an operation condition change range, wherein the operation condition change range is determined by the first sample data set;
determining at least one cavitation volume based on each of the cavitation numbers via a first exponential relationship;
constructing a second index relation between each historical operating condition parameter and each cavitation volume in the first sample data set;
determining an initial cavitation proxy model based on the second index relationship;
and verifying the initial cavitation proxy model by using the second sample data set to obtain the preset cavitation proxy model.
4. A method according to claim 3, wherein the second electrical control device determines whether cavitation of the water turbine assembly occurs via a preset cavitation proxy model based on the operating condition parameter dataset, comprising:
Inputting the operation condition parameter data set into the preset cavitation proxy model for simulation calculation to obtain the cavitation volume corresponding to each operation condition parameter in the operation condition parameter data set;
judging whether cavitation occurs in the water turbine unit or not based on each cavitation volume.
5. The method of claim 1, wherein the second electrical control device is configured to, based on the set of operating condition cavitation parameters, perform a pre-set air make-up prediction model process to obtain the target air make-up for the water turbine unit, the method further comprising:
acquiring a cavitation parameter data set of the historical operation working condition of the water turbine unit;
and establishing the preset air supplementing quantity prediction model based on the cavitation parameter data set of the historical operation working condition.
6. The method of claim 5, wherein establishing the pre-set air make-up prediction model based on the historical operating condition cavitation parameter dataset comprises:
determining a first training data set and a second training data set based on the historical operating condition cavitation parameter data set;
establishing a first air supplement quantity prediction model based on the first training data set;
Determining a first air supplementing amount based on the first air supplementing amount prediction model through preset conditions;
establishing a second air supplement quantity prediction model based on the first air supplement quantity and the first training data set;
and verifying the second air supplementing quantity prediction model by using the second training data set to obtain the preset air supplementing quantity prediction model, wherein the preset air supplementing quantity prediction model reflects the relation among the air supplementing quantity, the cavitation parameters of the operation working condition, the cavitation and the efficiency of the water turbine unit.
7. The method of claim 6, wherein the second electrical control device obtains the target air make-up of the water turbine set based on the set of operating condition cavitation parameter data through a preset air make-up prediction model process, comprising:
respectively inputting the operation condition cavitation parameter data set into the preset cavitation agent model and the preset air supplementing quantity prediction model to obtain the cavitation volume and the second air supplementing quantity corresponding to each operation condition cavitation parameter in the operation condition cavitation parameter data set;
based on a preset judgment condition, establishing a sensitivity relation between the cavitation volume and the second air supplementing amount;
And determining the target air supplementing quantity of the water turbine set based on the sensitivity relational expression and the preset air supplementing quantity prediction model.
8. The method of claim 7, wherein determining the target make-up amount for the hydro-turbine group based on the sensitivity relationship and the preset make-up amount prediction model comprises:
determining a third air make-up based on the sensitivity relationship when the cavitation volume is zero;
based on the third air supplementing quantity, judging whether the efficiency of the water turbine set is improved or not through the preset air supplementing quantity prediction model;
when the efficiency of the water turbine unit is improved, determining the third air supplementing amount as the target air supplementing amount;
and when the efficiency of the water turbine unit is reduced, adjusting the third air supplementing amount until the cavitation volume and the efficiency meet preset requirements, and obtaining the target air supplementing amount.
9. The method of claim 8, wherein the second electrical control device is configured to, based on the operating condition cavitation parameter data set, obtain a target air make-up for the water turbine set after processing by the preset cavitation proxy model and a preset air make-up prediction model, and further comprising:
And judging whether the target air supplementing quantity meets the preset air supplementing quantity requirement or not based on the operation condition parameter data set.
10. The method of claim 9, wherein determining whether the target air make-up meets a preset air make-up requirement based on the operating condition parameter dataset comprises:
cavitation simulation is carried out based on the operation condition parameter data set, so that the target efficiency of the water turbine unit corresponding to each operation condition parameter in the operation condition parameter data set is obtained;
adjusting the target air supplementing quantity according to preset conditions, and performing air supplementing simulation calculation based on the adjusted target air supplementing quantity to obtain the cavitation volume and the efficiency corresponding to each adjusted target air supplementing quantity;
judging whether the cavitation volume is zero;
when the cavitation volume is zero, comparing the efficiency to the target efficiency;
when the efficiency is greater than or equal to the target efficiency, determining that the target air supplementing amount meets the preset air supplementing amount requirement;
and when the efficiency is smaller than the target efficiency, determining that the target air supplementing amount does not meet the preset air supplementing amount requirement.
11. The water turbine set air supplementing quantity control device is characterized by being used for a control system, wherein the control system is connected with the water turbine set and comprises a first electric control device and a second electric control device; the device comprises:
The first acquisition module is used for acquiring an operation condition parameter data set of the water turbine unit by the second electric control device;
the judging module is used for judging whether cavitation occurs in the water turbine unit or not through a preset cavitation agent model based on the operation condition parameter data set by the second electric control device;
the second acquisition module is used for acquiring an operation condition cavitation parameter data set of the water turbine unit when cavitation occurs in the water turbine unit;
the processing module is used for processing the cavitation parameter data set of the second electrical control device through a preset air supplementing quantity prediction model based on the operation working condition to obtain the target air supplementing quantity of the water turbine unit;
the adjusting and controlling module is used for adjusting the opening value of the first electric control device based on the target air supplementing amount by the second electric control device, so that the adjusted first electric control device controls the air supplementing amount of the water turbine set.
12. A control system for performing the hydro turbine set air make-up control method of any one of claims 1 to 10; the system is characterized in that the system is connected with a water turbine unit; the system comprises:
the first electric control device is used for controlling the air supplementing quantity of the water turbine unit;
The second electrical control device is used for acquiring an operation condition parameter data set of the water turbine unit, processing the operation condition parameter data set through a preset cavitation agent model and a preset air supplementing quantity prediction model based on the operation condition parameter data set to obtain a target air supplementing quantity of the water turbine unit, and controlling an opening value of the first electrical control device based on the target air supplementing quantity.
13. The system of claim 12, wherein the second electrical control device comprises:
the data acquisition module is used for acquiring the operation condition parameter data set of the water turbine unit and sending the operation condition parameter data set to the data analysis module;
the data analysis module is used for judging whether cavitation occurs in the water turbine unit or not based on the operation condition parameter data set through the preset cavitation proxy model, acquiring the operation condition cavitation parameter data set of the water turbine unit when cavitation occurs in the water turbine unit, and sending the operation condition cavitation parameter data set to the air supplementing quantity prediction module;
the air supply prediction module is used for obtaining the target air supply of the water turbine unit based on the cavitation parameter data set of the operation working condition through the processing of the preset air supply prediction model, and sending the target air supply to the control module;
The control module is used for adjusting the opening value of the first electric control device based on the target air supplementing amount.
14. The system of claim 13, wherein the second electrical control device further comprises:
the storage module is used for receiving and storing the operation condition cavitation parameter data set sent by the data analysis module and the target air supplementing quantity sent by the air supplementing quantity prediction module.
15. A computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the hydro turbine group air make-up control method according to any one of claims 1 to 10.
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|---|---|---|---|
| CN202310873901.0A CN116717420A (en) | 2023-07-14 | 2023-07-14 | Water turbine set air supplementing quantity control method, device, control system and storage medium |
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| CN202310873901.0A CN116717420A (en) | 2023-07-14 | 2023-07-14 | Water turbine set air supplementing quantity control method, device, control system and storage medium |
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