Cascade scheduling joint curve optimization control method and system

Abstract

The invention relates to the technical field of hydropower station water turbine joint optimization control, and discloses a cascade scheduling joint curve optimization control method and system, and the method comprises the steps: building a hydropower station water turbine full-flow-channel physical model through a field scanning method, and carrying out the construction of a model grid; calculating an optimal joint point and obtaining a double-regulation unit joint curve; the full-head and full-opening water turbine efficiency and output database of the hydropower station water turbine is studied, and the optimal operation efficiency characteristic of the unit is obtained; analyzing the design association relationship of the hydropower station water turbine, calculating the association relationship, comparing the association relationship with historical operation data, and proposing the optimal association relationship of the water turbine; and obtaining a hydropower station water turbine joint optimization control strategy and an operation scheme according to the optimal joint relation of the water turbine. Efficient operation of the water turbine under various working conditions is ensured, and the energy conversion efficiency is improved. The optimal combination curve is provided, and the optimal performance of the water turbine under different working conditions is ensured. And according to the real-time water regimen and load requirements, efficient scheduling of the cascade power stations is realized.

Description

Technical Field

[0001] The invention relates to the technical field of coordinated optimization control of water turbines in hydropower stations, and in particular to a coordinated curve optimization control method and system for cascade scheduling. Background Art

[0002] Since the operating characteristic curves of turbine units operating in various river waters are all derived from the comprehensive characteristic curves of the model characteristics of the manufacturer's test bench, the test bench does not take into account the problems of inlet column vortex, siltation, fence clogging, tailwater surge, etc., which makes the turbines that are relatively excellent in the design stage have relatively low comprehensive efficiency in actual operation, the cooperative relationship is far from the optimal working condition, and the stability is poor, especially the low head and large flow turbines of intensive cascade power stations. The implementation of this project will simulate the actual situation on site to obtain the energy characteristics and stability characteristics of the turbine unit, obtain the optimal comprehensive cooperative relationship of the unit, and provide effective data support for the operation control and cascade scheduling of the operators. Summary of the invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the present invention provides a cascade scheduling coordinated curve optimization control method, which can solve the problem that the turbine cannot maintain the highest efficiency operation under all working conditions, resulting in low overall energy conversion efficiency.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a coordination curve optimization control method for cascade scheduling, comprising: using a field scanning method to establish a physical model of the entire flow channel of a hydropower station turbine, and constructing a model grid; calculating the optimal coordination point and obtaining the coordination curve of the dual-regulation unit; studying the full water head, full-opening turbine efficiency, and output database of the hydropower station turbine to obtain the optimal operating efficiency characteristics of the unit; analyzing the design coordination relationship of the hydropower station turbine, calculating the coordination relationship and comparing it with the historical operation data, and proposing the optimal coordination relationship of the turbine; and obtaining the hydropower station turbine coordination optimization control strategy and operation plan based on the optimal coordination relationship of the turbine.

[0006] As a preferred solution of the cascade scheduling synergy curve optimization control method described in the present invention, wherein: the physical model of the whole flow path of the turbine includes: when the turbine is stopped, scanning stations are arranged at the front flow path, guide vanes, and tailwater pipe of the turbine, and the whole flow path of the turbine is scanned from different angles using a three-dimensional laser scanner to obtain spatial point cloud data, and the scanning data of each station is recorded, including point cloud data, color information, and reflectivity;

[0007] Unify the data from different sites into a predetermined reference coordinate system and build a model:

[0008]

[0009] Among them, F represents the physical model of the entire flow channel, ρ represents the density of water, Q represents the flow rate, R represents the runner radius, Z represents the blade surface coordinate, α represents the blade installation angle, and θ represents the blade angle.

[0010] As a preferred solution of the cascade scheduling synergy curve optimization control method described in the present invention, the model grid construction includes calculating the energy conversion efficiency of the blade twist angle and the energy conversion efficiency of the turbine speed and flow rate according to the constructed model, and determining the area where the runner blade twist angle and speed flow rate have the greatest impact on the energy conversion efficiency:

[0011]

[0012] Where G(β) represents the function of blade twist angle on energy conversion efficiency, H(N,Q) represents the function of turbine speed and flow on energy conversion efficiency, β represents the blade twist angle, β opt represents the optimal blade twist angle, σ represents the standard deviation of the blade twist angle, N represents the turbine speed, Q opt represents the optimal flow rate, N opt represents the optimal speed, λ and μ represent the adjustment parameters;

[0013] Based on the G(β) calculation results, identify the area where the blade twist angle β has the greatest impact on the energy conversion efficiency, set a high grid density, and apply local grid refinement technology on the blade surface in the area with the best blade twist angle. The degree of refinement is proportional to σ. Use adaptive grid refinement to ensure that the grid resolution in the area where the flow characteristics of the leading and trailing edges of the blade change dramatically meets the requirements.

[0014] According to the calculation results of H(N,Q), the influence of speed and flow rate on energy conversion efficiency is analyzed, and the grid density is adjusted at the inlet and outlet of the guide vane and the tailwater pipe. The grid size is proportional to the change of speed and flow rate, that is, when the speed or flow rate deviates from the optimal value, the grid density is increased;

[0015] Boundary layer meshes are constructed on the blade surface and the flow channel wall to simulate the flow characteristics near the wall. The thickness of the boundary layer mesh is determined according to the actual values ​​of the blade installation angle and the blade twist angle, so that y + <1.

[0016] As a preferred solution of the cascade scheduling coordination curve optimization control method described in the present invention, the calculation of the optimal coordination point includes discretizing all continuous blade strokes into certain points through a fixed blade variable guide vane method, and then calculating different combinations through a variable guide vane method to find the most efficient combination as the quasi-coordination relationship point:

[0017]

[0018] Where, P represents the turbine power;

[0019] When calculating for different runner blade angles, the calculated data obtained are first used to draw a single fixed-propeller turbine curve, that is, the turbine working characteristic curve, that is, when the turbine runner diameter is a constant, the speed and water head are constant, the turbine power and efficiency, flow rate, and guide vane opening parameters are obtained to obtain the power characteristic curve, flow characteristic curve, and opening characteristic curve under the current fixed-propeller working condition.

[0020] As a preferred solution of the cascade scheduling coordination curve optimization control method described in the present invention, wherein: the optimal operating efficiency characteristics include establishing an RNG k-ε turbulence model of the flow field inside the turbine, performing three-dimensional numerical calculations on the entire flow channel of the low-head turbine, selecting multiple operating points under three common water heads where the blades and guide vanes are in a coordinated state, calculating the external characteristics of the efficiency, flow rate and output of the unit, and drawing the external characteristic curve. The process is that when the unit is in the coordinated working condition, the blade opening is kept unchanged, and when the guide vane opening is increased, the highest efficiency is determined according to the increasing and decreasing trends of the flow rate and efficiency, and the unit coordination curve is obtained;

[0021] Perform three-dimensional numerical calculations on the selected multiple operating points to simulate the flow field in the turbine, use the RNG k-ε turbulence model to perform fluid dynamics simulation, and set the model parameters:

[0022]

[0023] Where k represents turbulent kinetic energy, u, v, w represent velocity components, x, y, z represent spatial coordinates, ∈ represents the turbulent kinetic energy dissipation rate, C 1-RNG represents the constant in the RNG k-ε turbulence model, s represents the turbulent mixing length, and l represents the turbulent characteristic length;

[0024] Through the turbulence model, the overall characteristics of the flow field are analyzed, including flow direction, flow velocity, and turbulence intensity; local characteristics are analyzed, including the flow near the leading and trailing edges of the blades, the flow in the guide vanes and the tailwater pipe; the flow separation, vortex, and backflow in the flow field are analyzed, and the area where the water flows most smoothly in the impeller and the tailwater pipe is obtained, that is, the high-efficiency area.

[0025] As a preferred solution of the cascade scheduling coordination curve optimization control method described in the present invention, wherein: the optimal coordination relationship includes performing unsteady numerical calculations on different flow coordination conditions of the turbine by establishing a turbine pressure pulsation calculation model and a turbine runner bidirectional fluid-solid coupling prediction model;

[0026] The turbine pressure pulsation calculation model:

[0027]

[0028] Among them, P pulsation Indicates the turbine pressure pulsation intensity, K i represents the pressure pulsation coefficient under the i-th working condition, ΔH i represents the head loss under the i-th working condition, Q i represents the reference flow rate under the i-th working condition, α i represents the adjustment parameter;

[0029] Introduce solid domain into the runner model, simulate the elastic deformation of the runner, perform fluid-solid coupling calculation, simulate the deformation of the runner under the action of fluid and the reaction force of the fluid on the runner, and establish a two-way fluid-solid coupling prediction model for the turbine runner:

[0030]

[0031] Among them, F coupling represents the bidirectional fluid-solid coupling force of the runner, Γ represents the fluid-solid coupling coefficient, x1 and y1 represent the axial position and radial displacement of the runner blade, E represents the elastic modulus, L represents the length of the runner blade, I represents the moment of inertia of the cross section, β1 represents the parameter affecting the dynamic effect of the fluid, and V represents the fluid velocity;

[0032] Under different operating conditions, the vortex belt in the tailwater pipe of the unit is analyzed, the radial force of the runner, the pressure pulsation and the unit vibration are analyzed, and the unit stable zone is obtained within the unit high-efficiency stable zone. The most unstable areas of full head and full opening in the front flow channel, guide vanes, runner and tailwater pressure pulsation are proposed. The long-term stable operation area, short-term operation area and restricted operation area of ​​each unit under the complementary mode are proposed.

[0033] As a preferred solution of the cascade scheduling coordinated curve optimization control method described in the present invention, the coordinated optimization control strategy includes triggering the pressure pulsation intensity P when the turbine operating flow Q deviates from the reference flow by more than a set threshold value ΔQ pulsation Real-time monitoring, when P pulsation When the pressure pulsation exceeds the preset threshold of 0.1MPa, α is automatically adjusted. i Parameters, reduce pressure pulsation;

[0034] When the runner bidirectional fluid-solid coupling force F coupling When the preset stability force threshold of 100 kN is exceeded, it indicates that the elastic deformation of the runner will affect the stable operation. The fluid-structure coupling coefficient Γ is adjusted to reduce F coupling g to below 100 kN, taking into account the adjustment of E and I at the same time, optimizing the elastic deformation response of the runner;

[0035] Monitor the synchronization of the tailwater vortex frequency and the pressure pulsation frequency. When the ratio of the tailwater vortex frequency to the pressure pulsation frequency deviates from the preset synchronization ratio of 1.5, adjust the guide vane opening, change the vortex shape, and reduce the impact of synchronization; monitor the relationship between the radial force fluctuation amplitude of the runner and the fluid velocity. When the ratio of the two exceeds the preset fluctuation velocity ratio of 0.01N / (m / s), start the radial force balance adjustment mechanism and adjust the runner blade angle or speed; divide the stable operation area according to the front flow channel, guide vane, runner, and tailwater pressure pulsation at full water head and full opening. When it is monitored that the most unstable area of ​​pressure pulsation expands to more than 20% of the stable operation area, automatically adjust the turbine operating parameters to reduce the unstable area.

[0036] Another object of the present invention is to provide a coordinated curve optimization control system for cascade scheduling, which can achieve efficient scheduling of cascade hydropower station groups, automatically adjust the operating status of each power station according to water conditions and load demand, and improve the overall efficiency of the cascade power stations.

[0037] As a preferred solution of the cascade scheduling coordinated curve optimization control system described in the present invention, it includes: a data acquisition and preprocessing module, a working condition analysis and identification module, a coordinated curve optimization model module, a control strategy generation and execution module, and a monitoring and feedback adjustment module;

[0038] The data acquisition and preprocessing module collects real-time data from the monitoring systems of various cascade hydropower stations, including water head, flow, rotation speed, power, pressure pulsation, and tailwater tube vortex band frequency, and preprocesses the data to eliminate noise and abnormal values;

[0039] The operating condition analysis and identification module analyzes the collected data, identifies the current operating condition of the turbine, and determines whether the turbine is in a high-efficiency stable zone, a transition zone, or an unstable zone, thereby providing a basis for subsequent optimization control;

[0040] The synergy curve optimization model module adjusts and optimizes the synergy curve based on the working condition analysis and identification results;

[0041] The control strategy generation and execution module generates a specific control strategy according to the optimized synergy curve, including adjusting the guide vane opening, rotation speed, and flow distribution. The execution module converts the strategy into a control command and sends it to the control system of the turbine to achieve synergy optimization.

[0042] The monitoring and feedback adjustment module continuously tracks the performance of the turbine in actual operation and compares it with the results predicted by the optimization model.

[0043] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, it implements the steps of a cascade scheduling coordination curve optimization control method.

[0044] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a cascade scheduling coordination curve optimization control method are implemented.

[0045] The beneficial effects of the present invention are as follows: the optimal coordination relationship of the hydropower station units is obtained through the method, and the optimal operation plan of the hydropower station is established. After on-site implementation, the comprehensive efficiency of the hydropower station units is improved by 0.5%-1.5%; the operation stability of the hydropower station units is continuously improved, the pressure pulsation and vibration of the hydropower units are reduced, the fatigue damage of the units is reduced, the life of the key components of the units is extended by 1.2 times, and the operation and maintenance costs are reduced; the energy and stability database of the units in the whole flow channel and all working conditions is established, which provides effective data support for the future intelligentization and wisdom of the hydropower station and the health management of the power station equipment; the formed optimal operation plan effectively provides a reference for the operation shift leader, helps the shift leader to accurately predict the load, and provides support for the planned adjustment of the units, effectively avoids the provincial adjustment assessment, and reduces the number of assessments by 3-5 times. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0047] Figure 1 A schematic flow chart of a coordinated curve optimization control method for step scheduling provided by an embodiment of the present invention.

[0048] Figure 2 A schematic diagram of working modules of a coordinated curve optimization control system for step scheduling provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0052] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0053] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0054] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0055] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a coordinated curve optimization control method for step scheduling, comprising:

[0056] S1: Use the on-site scanning method to establish the physical model of the entire flow channel of the hydropower station turbine and construct the model mesh.

[0057] Furthermore, the physical model of the whole flow channel of the turbine includes: when the turbine is stopped, scanning stations are arranged at the front flow channel, guide vanes, and tailwater pipe of the turbine, and the whole flow channel of the turbine is scanned from different angles using a three-dimensional laser scanner to obtain spatial point cloud data, and the scanning data of each station is recorded, including point cloud data, color information, and reflectivity;

[0058] Unify the data from different sites into a predetermined reference coordinate system and build a model:

[0059]

[0060] Among them, F represents the physical model of the entire flow channel, ρ represents the density of water, Q represents the flow rate, R represents the runner radius, Z represents the blade surface coordinate, α represents the blade installation angle, and θ represents the blade angle.

[0061] It should be noted that the model grid construction includes calculating the energy conversion efficiency of the blade twist angle and the energy conversion efficiency of the turbine speed and flow rate according to the constructed model, and determining the area where the runner blade twist angle and speed and flow rate have the greatest impact on the energy conversion efficiency:

[0062]

[0063] Where G(β) represents the function of blade twist angle on energy conversion efficiency, H(N,Q) represents the function of turbine speed and flow on energy conversion efficiency, β represents the blade twist angle, β opt represents the optimal blade twist angle, σ represents the standard deviation of the blade twist angle, N represents the turbine speed, Q opt represents the optimal flow rate, N opt represents the optimal speed, λ and μ represent the adjustment parameters;

[0064] Based on the G(β) calculation results, identify the area where the blade twist angle β has the greatest impact on the energy conversion efficiency, set a high grid density, and apply local grid refinement technology on the blade surface in the area with the best blade twist angle. The degree of refinement is proportional to σ. Use adaptive grid refinement to ensure that the grid resolution in the area where the flow characteristics of the leading and trailing edges of the blade change dramatically meets the requirements.

[0065] According to the calculation results of H(N,Q), the influence of speed and flow rate on energy conversion efficiency is analyzed, and the grid density is adjusted at the inlet and outlet of the guide vane and the tailwater pipe. The grid size is proportional to the change of speed and flow rate, that is, when the speed or flow rate deviates from the optimal value, the grid density is increased;

[0066] Boundary layer meshes are constructed on the blade surface and the flow channel wall to simulate the flow characteristics near the wall. The thickness of the boundary layer mesh is determined according to the actual values ​​of the blade installation angle and the blade twist angle, so that y + <1.

[0067] S2: Calculate the optimal coordination point and obtain the coordination curve of the dual-regulation units.

[0068] Furthermore, the calculation of the optimal coordination point includes discretizing all continuous blade strokes into certain points by means of fixed blade variable guide vane, and then calculating different combinations by means of variable guide vane to find the most efficient combination as the quasi-coordination relationship point:

[0069]

[0070] Where, P represents the turbine power;

[0071] When calculating for different runner blade angles, the calculated data obtained are first used to draw a single fixed-propeller turbine curve, that is, the turbine working characteristic curve, that is, when the turbine runner diameter is a constant, the speed and water head are constant, the turbine power and efficiency, flow rate, and guide vane opening parameters are obtained to obtain the power characteristic curve, flow characteristic curve, and opening characteristic curve under the current fixed-propeller working condition.

[0072] S3: Study the full head, full opening turbine efficiency and output database of the hydropower station turbine to obtain the optimal operating efficiency characteristics of the unit.

[0073] Furthermore, the optimal operating efficiency characteristics include establishing an RNG k-ε turbulence model of the flow field inside the turbine, performing three-dimensional numerical calculations on the entire flow channel of the low-head turbine, selecting multiple operating points under three common water heads where the blades and guide vanes are in a coordinated state, calculating the external characteristics of the efficiency, flow rate and output of the unit, and drawing an external characteristic curve. The process is that when the unit is in a coordinated working condition, the blade opening is kept unchanged, and when the guide vane opening is increased, the highest efficiency is determined based on the increasing and decreasing trends of the flow rate and efficiency, and the unit coordination curve is obtained;

[0074] Perform three-dimensional numerical calculations on the selected multiple operating points to simulate the flow field in the turbine, use the RNG k-ε turbulence model to perform fluid dynamics simulation, and set the model parameters:

[0075]

[0076] Where k represents turbulent kinetic energy, u, v, w represent velocity components, x, y, z represent spatial coordinates, ∈ represents the turbulent kinetic energy dissipation rate, C 1-RNG represents the constant in the RNG k-ε turbulence model, s represents the turbulent mixing length, and l represents the turbulent characteristic length;

[0077] Through the turbulence model, the overall characteristics of the flow field are analyzed, including flow direction, flow velocity, and turbulence intensity; local characteristics are analyzed, including the flow near the leading and trailing edges of the blades, the flow in the guide vanes and the tailwater pipe; the flow separation, vortex, and backflow in the flow field are analyzed, and the area where the water flows most smoothly in the impeller and the tailwater pipe is obtained, that is, the high-efficiency area.

[0078] S4: Analyze the design coordination relationship of the hydropower station turbine, calculate the coordination relationship and compare it with the historical operation data, and propose the optimal coordination relationship of the turbine.

[0079] Furthermore, the optimal synergistic relationship includes performing unsteady numerical calculations on different flow synergistic working conditions of the turbine by establishing a turbine pressure pulsation calculation model and a turbine runner bidirectional fluid-solid coupling prediction model;

[0080] The turbine pressure pulsation calculation model:

[0081]

[0082] Among them, P pulsation Indicates the turbine pressure pulsation intensity, K i represents the pressure pulsation coefficient under the i-th working condition, ΔH i represents the head loss under the i-th working condition, Q i represents the reference flow rate under the i-th working condition, α i represents the adjustment parameter;

[0083] Introduce solid domain into the runner model, simulate the elastic deformation of the runner, perform fluid-solid coupling calculation, simulate the deformation of the runner under the action of fluid and the reaction force of the fluid on the runner, and establish a two-way fluid-solid coupling prediction model for the turbine runner:

[0084]

[0085] Among them, F coupling represents the bidirectional fluid-solid coupling force of the runner, Γ represents the fluid-solid coupling coefficient, x1 and y1 represent the axial position and radial displacement of the runner blade, E represents the elastic modulus, L represents the length of the runner blade, I represents the moment of inertia of the cross section, β1 represents the parameter affecting the dynamic effect of the fluid, and V represents the fluid velocity;

[0086] Under different operating conditions, the vortex belt in the tailwater pipe of the unit is analyzed, the radial force of the runner, the pressure pulsation and the unit vibration are analyzed, and the unit stable zone is obtained within the unit high-efficiency stable zone. The most unstable areas of full head and full opening in the front flow channel, guide vanes, runner and tailwater pressure pulsation are proposed. The long-term stable operation area, short-term operation area and restricted operation area of ​​each unit under the complementary mode are proposed.

[0087] S5: According to the optimal coupling relationship of the turbines, the optimal control strategy and operation plan of the turbine coupling of the hydropower station are obtained.

[0088] Furthermore, the coordinated optimization control strategy includes triggering the pressure pulsation intensity P when the turbine operating flow Q deviates from the reference flow by more than a set threshold value ΔQ pulsation Real-time monitoring, when P pulsation When the pressure pulsation exceeds the preset threshold of 0.1MPa, α is automatically adjusted. i Parameters, reduce pressure pulsation;

[0089] When the runner bidirectional fluid-solid coupling force F coupling When the preset stability force threshold value of 100 kN is exceeded, it indicates that the elastic deformation of the runner will affect the stable operation. The fluid-structure coupling coefficient Γ is adjusted to reduce F coupling g to below 100 kN, taking into account the adjustment of E and I at the same time, optimizing the elastic deformation response of the runner;

[0090] Monitor the synchronization of the tailwater tube vortex frequency and the pressure pulsation frequency. When the ratio of the tailwater tube vortex frequency to the pressure pulsation frequency deviates from the preset synchronization ratio of 1.5, adjust the guide vane opening, change the vortex shape, and reduce the impact of synchronization; monitor the relationship between the radial force fluctuation amplitude of the runner and the fluid velocity. When the ratio of the two exceeds the preset fluctuation velocity ratio of 0.01N / (m / s), start the radial force balance adjustment mechanism to adjust the runner blade angle or speed; divide the stable operation area according to the front flow channel, guide vane, runner, and tailwater pressure pulsation at full water head and full opening. When it is monitored that the most unstable area of ​​pressure pulsation expands to more than 20% of the stable operation area, automatically adjust the turbine operating parameters to reduce the unstable area.

[0091] Embodiment 2, the second embodiment of the present invention, is different from the previous embodiment in that:

[0092] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0093] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0094] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0095] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0096] Example 3, reference Figure 2 , which is an embodiment of the present invention, provides a cascade scheduling coordinated curve optimization control system, characterized in that it includes a data acquisition and preprocessing module, a working condition analysis and identification module, a coordinated curve optimization model module, a control strategy generation and execution module, and a monitoring and feedback adjustment module;

[0097] The data acquisition and preprocessing module collects real-time data from the monitoring systems of various cascade hydropower stations, including head, flow, speed, power, pressure pulsation, and tailwater vortex frequency, and preprocesses the data to eliminate noise and outliers.

[0098] The operating condition analysis and identification module analyzes the collected data, identifies the current operating condition of the turbine, and determines whether the turbine is in the high-efficiency stable zone, transition zone or unstable zone, providing a basis for subsequent optimization control.

[0099] The synergy curve optimization model module adjusts and optimizes the synergy curve based on the working condition analysis and identification results.

[0100] The control strategy generation and execution module generates a specific control strategy based on the optimized synergy curve, including adjusting the guide vane opening, speed, and flow distribution. The execution module converts the strategy into a control command and sends it to the turbine control system to achieve synergy optimization.

[0101] Monitoring and Feedback Adjustment Module,The monitoring module continuously tracks the performance of the turbine in actual operation, and compares it with the results predicted by the optimization model.

[0102] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A cascade scheduling coordination curve optimization control method, Features: include, Use the on-site scanning method to establish the physical model of the entire flow channel of the hydropower station turbine and construct the model mesh; Calculate the optimal coordination point and obtain the coordination curve of the dual-regulation units; Study the full head, full opening turbine efficiency and output database of the hydropower station turbine to obtain the optimal operating efficiency characteristics of the unit; Analyze the design coordination relationship of the hydropower station turbine, calculate the coordination relationship and compare it with the historical operation data, and propose the optimal coordination relationship of the turbine; According to the optimal turbine coupling relationship, the optimal control strategy and operation plan of the turbine coupling of the hydropower station are obtained.

2. A cascade scheduling coordination curve optimization control method as claimed in claim 1, Features: The physical model of the whole flow channel of the turbine includes: when the turbine is stopped, scanning stations are arranged at the front flow channel, guide vanes and tailwater pipe of the turbine, and the whole flow channel of the turbine is scanned from different angles using a three-dimensional laser scanner to obtain spatial point cloud data, and the scanning data of each station is recorded, including point cloud data, color information and reflectivity; Unify the data from different sites into a predetermined reference coordinate system and build a model: Among them, F represents the physical model of the entire flow channel, ρ represents the density of water, Q represents the flow rate, R represents the runner radius, Z represents the blade surface coordinate, α represents the blade installation angle, and θ represents the blade angle.

3. A cascade scheduling coordination curve optimization control method as claimed in claim 2, Features: The model grid construction includes calculating the energy conversion efficiency of the blade twist angle and the energy conversion efficiency of the turbine speed and flow rate according to the constructed model, and determining the area where the runner blade twist angle and speed and flow rate have the greatest influence on the energy conversion efficiency: Where G(β) represents the function of blade twist angle on energy conversion efficiency, H(N,Q) represents the function of turbine speed and flow on energy conversion efficiency, β represents the blade twist angle, β opt represents the optimal blade twist angle, σ represents the standard deviation of the blade twist angle, N represents the turbine speed, Q opt represents the optimal flow rate, N opt represents the optimal speed, λ and μ represent the adjustment parameters; Based on the G(β) calculation results, identify the area where the blade twist angle β has the greatest impact on the energy conversion efficiency, set a high grid density, and apply local grid refinement technology on the blade surface in the area with the best blade twist angle. The degree of refinement is proportional to σ. Use adaptive grid refinement to ensure that the grid resolution in the area where the flow characteristics of the leading and trailing edges of the blade change dramatically meets the requirements. According to the calculation results of H(N,Q), the influence of speed and flow rate on energy conversion efficiency is analyzed, and the grid density is adjusted at the inlet and outlet of the guide vane and the tailwater pipe. The grid size is proportional to the change of speed and flow rate, that is, when the speed or flow rate deviates from the optimal value, the grid density is increased; Boundary layer meshes are constructed on the blade surface and the flow channel wall to simulate the flow characteristics near the wall. The thickness of the boundary layer mesh is determined according to the actual values ​​of the blade installation angle and the blade twist angle, so that y + <1.

4. A cascade scheduling coordination curve optimization control method as claimed in claim 3, Features: The calculation of the optimal coordination point includes discretizing all continuous blade strokes into certain points by means of fixed blade variable guide vane, and then calculating different combinations by means of variable guide vane to find the most efficient combination as the quasi-coordination relationship point: Where, P represents the turbine power; When calculating for different runner blade angles, the calculated data obtained are first used to draw a single fixed-propeller turbine curve, that is, the turbine working characteristic curve, that is, when the turbine runner diameter is a constant, the speed and water head are constant, the turbine power and efficiency, flow rate, and guide vane opening parameters are obtained to obtain the power characteristic curve, flow characteristic curve, and opening characteristic curve under the current fixed-propeller working condition.

5. A cascade scheduling coordination curve optimization control method as claimed in claim 4, Features: The optimal operating efficiency characteristics include establishing an RNG k-ε turbulence model of the flow field inside the turbine, performing three-dimensional numerical calculations on the entire flow channel of the low-head turbine, selecting multiple operating points under three common water heads where the blades and guide vanes are in a coordinated state, calculating the external characteristics of the efficiency, flow rate and output of the unit, and drawing an external characteristic curve. The process is that when the unit is in a coordinated working condition, the blade opening is kept unchanged, and when the guide vane opening is increased, the highest efficiency is determined according to the increasing and decreasing trends of the flow rate and efficiency, and the unit coordination curve is obtained; Perform three-dimensional numerical calculations on the selected multiple operating points to simulate the flow field in the turbine, use the RNG k-ε turbulence model to perform fluid dynamics simulation, and set the model parameters: Where k represents turbulent kinetic energy, u, v, w represent velocity components, x, y, z represent spatial coordinates, ∈ represents the turbulent kinetic energy dissipation rate, C 1-RNG represents the constant in the RNG k-ε turbulence model, s represents the turbulent mixing length, and l represents the turbulent characteristic length; Through the turbulence model, the overall characteristics of the flow field are analyzed, including flow direction, flow velocity, and turbulence intensity; local characteristics are analyzed, including the flow near the leading and trailing edges of the blades, the flow in the guide vanes and the tailwater pipe; the flow separation, vortex, and backflow in the flow field are analyzed, and the area where the water flows most smoothly in the impeller and the tailwater pipe is obtained, that is, the high-efficiency area.

6. A cascade scheduling coordination curve optimization control method as claimed in claim 5, Features: The optimal coordination relationship includes establishing a turbine pressure pulsation calculation model and a turbine runner bidirectional fluid-solid coupling prediction model to perform unsteady numerical calculations on different flow coordination conditions of the turbine; The turbine pressure pulsation calculation model: Among them, P pulsation Indicates the turbine pressure pulsation intensity, K i represents the pressure pulsation coefficient under the i-th working condition, ΔH i represents the head loss under the i-th working condition, Q i represents the reference flow rate under the i-th working condition, α i represents the adjustment parameter; Introduce solid domain into the runner model, simulate the elastic deformation of the runner, perform fluid-solid coupling calculation, simulate the deformation of the runner under the action of fluid and the reaction force of the fluid on the runner, and establish a two-way fluid-solid coupling prediction model for the turbine runner: Among them, F coupling represents the bidirectional fluid-structure coupling force of the runner, Γ represents the fluid-structure coupling coefficient, x 1 ,y 1 They represent the axial position and radial displacement of the runner blades, E represents the elastic modulus, L represents the length of the runner blades, I represents the moment of inertia of the section, β 1 It represents the parameter that affects the dynamic effect of the fluid, V represents the fluid velocity; Under different operating conditions, the vortex belt in the tailwater pipe of the unit is analyzed, the radial force of the runner, the pressure pulsation and the unit vibration are analyzed, and the unit stable zone is obtained within the unit high-efficiency stable zone. The most unstable areas of full head and full opening in the front flow channel, guide vanes, runner and tailwater pressure pulsation are proposed. The long-term stable operation area, short-term operation area and restricted operation area of ​​each unit under the complementary mode are proposed.

7. A cascade scheduling coordination curve optimization control method as claimed in claim 6, Features: The coordinated optimization control strategy includes triggering the pressure pulsation intensity P when the turbine operating flow Q deviates from the reference flow by more than a set threshold value ΔQ pulsation Real-time monitoring, when P pulsation When the pressure pulsation exceeds the preset threshold of 0.1MPa, α is automatically adjusted. i Parameters, reduce pressure pulsation; When the runner bidirectional fluid-solid coupling force F coupling When the preset stability force threshold of 100 kN is exceeded, it indicates that the elastic deformation of the runner will affect the stable operation. The fluid-structure coupling coefficient Γ is adjusted to reduce F coupling g to below 100 kN, taking into account the adjustment of E and I at the same time, optimizing the elastic deformation response of the runner; Monitor the synchronization of the tailwater vortex frequency and the pressure pulsation frequency. When the ratio of the tailwater vortex frequency to the pressure pulsation frequency deviates from the preset synchronization ratio of 1.5, adjust the guide vane opening, change the vortex shape, and reduce the impact of synchronization; monitor the relationship between the radial force fluctuation amplitude of the runner and the fluid velocity. When the ratio of the two exceeds the preset fluctuation velocity ratio of 0.01N / (m / s), start the radial force balance adjustment mechanism and adjust the runner blade angle or speed; divide the stable operation area according to the front flow channel, guide vane, runner, and tailwater pressure pulsation at full water head and full opening. When it is monitored that the most unstable area of ​​pressure pulsation expands to more than 20% of the stable operation area, automatically adjust the turbine operating parameters to reduce the unstable area.

8. A system using a coordinated curve optimization control method for step scheduling as claimed in any one of claims 1 to 7, Features: It includes data acquisition and preprocessing module, working condition analysis and identification module, synergy curve optimization model module, control strategy generation and execution module, monitoring and feedback adjustment module; The data acquisition and preprocessing module collects real-time data from the monitoring systems of various cascade hydropower stations, including water head, flow, rotation speed, power, pressure pulsation, and tailwater tube vortex band frequency, and preprocesses the data to eliminate noise and abnormal values; The operating condition analysis and identification module analyzes the collected data, identifies the current operating condition of the turbine, and determines whether the turbine is in a high-efficiency stable zone, a transition zone, or an unstable zone, thereby providing a basis for subsequent optimization control; The synergy curve optimization model module adjusts and optimizes the synergy curve based on the working condition analysis and identification results; The control strategy generation and execution module generates a specific control strategy according to the optimized synergy curve, including adjusting the guide vane opening, rotation speed, and flow distribution. The execution module converts the strategy into a control command and sends it to the control system of the turbine to achieve synergy optimization. The monitoring and feedback adjustment module continuously tracks the performance of the turbine in actual operation and compares it with the results predicted by the optimization model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program. It is characterized in that When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

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