Water turbine operation optimization method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a water turbine operation optimization method and device, computer equipment, a readable storage medium and a program product, and relates to the technical field of water turbines. The method comprises the steps of obtaining working condition information of a target water turbine in response to an operation optimization instruction for the target water turbine; based on the working condition information, optimizing the servomotor diameter of a guide vane servomotor in the target water turbine to obtain a diameter optimization result of the guide vane servomotor; for each guide vane mechanism part except a guide vane servomotor in the target water turbine, reliability analysis is carried out on the guide vane mechanism parts based on the diameter optimization result, and the reliability analysis result of each guide vane mechanism part is obtained; according to the diameter optimization result and the reliability analysis result, the target water turbine is controlled to operate, and an operation result of the target water turbine is obtained. The method can improve the operation efficiency of the water turbine.

Description

Technical Field

[0001] The present application relates to the technical field of water turbines, and in particular to a method, device, computer equipment, readable storage medium and program product for optimizing water turbine operation. Background Art

[0002] In the field of hydropower, water turbines are the core equipment for energy conversion in hydropower stations. They are power machines that convert the energy of water flow into rotational mechanical energy. The operation of water turbines not only affects the stable operation of the power system, but also affects the efficiency of the hydropower station.

[0003] At present, in practical applications, there are usually various factors that affect the normal operation of the turbine, resulting in low turbine operation efficiency. Therefore, an optimization method for turbine operation is urgently needed. Summary of the invention

[0004] Based on this, it is necessary to provide a turbine operation optimization method, device, computer equipment, computer readable storage medium and computer program product that can improve the operating efficiency of the turbine in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for optimizing the operation of a water turbine, comprising: in response to an operation optimization instruction for a target water turbine, obtaining the operating condition information of the target water turbine; based on the operating condition information, optimizing the servo diameter of the guide vane servo in the target water turbine to obtain a diameter optimization result of the guide vane servo; for each guide vane mechanism part other than the guide vane servo in the target water turbine, based on the diameter optimization result, performing a reliability analysis on the guide vane mechanism part to obtain a reliability analysis result of each guide vane mechanism part; and controlling the operation of the target water turbine according to the diameter optimization result and the reliability analysis result to obtain the operation result of the target water turbine.

[0006] In one of the embodiments, based on the operating condition information, the servomotor diameter of the guide vane servomotor in the target turbine is optimized to obtain the diameter optimization result of the guide vane servomotor, including: based on the operating condition information, three-dimensional modeling of the target turbine is performed to obtain the three-dimensional turbine model of the target turbine; the three-dimensional turbine model is operated to obtain the guide vane water torque and the guide vane friction resistance torque output by the three-dimensional turbine model; based on the guide vane water torque and the guide vane friction resistance torque, the target operating force of the guide vane servomotor driving the target turbine to operate is determined; according to the target operating force, the servomotor diameter of the guide vane servomotor is optimized to obtain the diameter optimization result of the guide vane servomotor.

[0007] In one of the embodiments, the servomotor diameter of the guide vane servomotor is optimized according to the target operating force to obtain the diameter optimization result of the guide vane servomotor, including: determining the safe operating oil pressure of the guide vane servomotor according to the target operating oil pressure required for the target operating force and the rated oil pressure of the guide vane servomotor; and optimizing the servomotor diameter of the guide vane servomotor based on the safe operating oil pressure to obtain the diameter optimization result of the guide vane servomotor.

[0008] In one of the embodiments, the method also includes: acquiring part structure information of the guide vane mechanism parts, and based on the part structure information, performing complexity analysis on the guide vane mechanism parts to obtain complexity analysis results for each guide vane mechanism part; based on the diameter optimization results, performing reliability analysis on the guide vane mechanism parts to obtain reliability analysis results for each guide vane mechanism part, including: performing reliability analysis on the guide vane mechanism parts based on the complexity analysis results and the diameter optimization results to obtain reliability analysis results for each guide vane mechanism part.

[0009] In one of the embodiments, the diameter optimization result includes the safe operating space of the guide vane servomotor; the reliability analysis result includes the stiffness analysis result and the remaining operating life of the guide vane mechanism parts; based on the complexity analysis result and the diameter optimization result, the reliability analysis is performed on the guide vane mechanism parts to obtain the reliability analysis result of each guide vane mechanism part, including: when the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, a three-dimensional turbine model of the target turbine is operated to analyze the stiffness of the guide vane mechanism parts during operation to obtain the stiffness analysis result of each guide vane mechanism part; the stiffness analysis result is input into the part life prediction model to perform life prediction on the guide vane mechanism parts to obtain the remaining operating life of each guide vane mechanism part.

[0010] In one of the embodiments, the method also includes: determining the part type of each part in the guide vane mechanism parts; the part type includes a weak part part and a stable part part; inputting the stiffness analysis results into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of the guide vane mechanism parts, including: inputting the stiffness analysis results of the weak part parts and the stiffness analysis results of the stable part parts into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of each guide vane mechanism part.

[0011] In the second aspect, the present application also provides a turbine operation optimization device, including: an information acquisition module, which is used to obtain the operating condition information of the target turbine in response to the operation optimization instruction for the target turbine; a diameter selection module, which is used to optimize the relay diameter of the guide vane relay in the target turbine based on the operating condition information, and obtain the diameter optimization result of the guide vane relay; a part optimization module, which is used to perform reliability analysis on the guide vane mechanism parts of each guide vane mechanism part other than the guide vane relay in the target turbine based on the diameter optimization result, and obtain the reliability analysis result of each guide vane mechanism part; an operation module, which is used to control the operation of the target turbine according to the diameter optimization result and the reliability analysis result, and obtain the operation result of the target turbine.

[0012] In a third aspect, the present application also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the following steps when executing the computer program: in response to an operation optimization instruction for a target water turbine, obtaining the operating condition information of the target water turbine; based on the operating condition information, optimizing the servo diameter of the guide vane servo in the target water turbine to obtain a diameter optimization result of the guide vane servo; for each guide vane mechanism part other than the guide vane servo in the target water turbine, performing reliability analysis on the guide vane mechanism parts based on the diameter optimization result to obtain a reliability analysis result of each guide vane mechanism part; and controlling the operation of the target water turbine according to the diameter optimization result and the reliability analysis result to obtain the operation result of the target water turbine.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the following steps when executed by a processor: in response to an operation optimization instruction for a target water turbine, obtaining the operating condition information of the target water turbine; based on the operating condition information, optimizing the servo diameter of the guide vane servo in the target water turbine to obtain a diameter optimization result of the guide vane servo; for each guide vane mechanism part other than the guide vane servo in the target water turbine, performing a reliability analysis on the guide vane mechanism part based on the diameter optimization result to obtain a reliability analysis result of each guide vane mechanism part; and controlling the operation of the target water turbine according to the diameter optimization result and the reliability analysis result to obtain the operation result of the target water turbine.

[0014] In a fifth aspect, the present application also provides a computer program product, comprising a computer program, which implements the following steps when executed by a processor: in response to an operation optimization instruction for a target water turbine, obtain the operating condition information of the target water turbine; based on the operating condition information, optimize the servo diameter of the guide vane servo in the target water turbine to obtain a diameter optimization result of the guide vane servo; for each guide vane mechanism part other than the guide vane servo in the target water turbine, based on the diameter optimization result, perform reliability analysis on the guide vane mechanism part to obtain a reliability analysis result of each guide vane mechanism part; according to the diameter optimization result and the reliability analysis result, control the operation of the target water turbine to obtain the operation result of the target water turbine.

[0015] The above-mentioned turbine operation optimization method, device, computer equipment, computer-readable storage medium and computer program product, in response to the operation optimization instruction for the target turbine, first obtain the operating condition information of the target turbine, and then optimize the servomotor diameter of the guide vane servomotor in the target turbine according to the operating condition information, so as to obtain accurate and reliable diameter optimization results. It can be understood that the guide vane servomotor is one of the core mechanisms for driving the operation of the turbine, and for the guide vane servomotor, the servomotor diameter affects the driving efficiency of the guide vane servomotor by affecting the operating space of the guide vane servomotor. Therefore, the diameter of the guide vane servomotor is one of the important factors affecting the operation of the turbine. The present application optimizes from the perspective of the diameter of the guide vane servomotor, and by selecting a suitable servomotor diameter, the guide vane servomotor has a reasonable and safe operating space, thereby improving the driving efficiency of the guide vane servomotor and thus improving the operation efficiency of the turbine. In addition, the present application also takes into account that other guide vane mechanism parts in the turbine will also have a certain impact on the operation of the turbine. Therefore, for each guide vane mechanism part except the guide vane servomotor in the target turbine, on the basis of the diameter optimization result of the guide vane servomotor, the guide vane mechanism parts are further subjected to reliability analysis, that is, the rigidity and remaining life of the guide vane mechanism parts are analyzed. Finally, according to the diameter optimization result and the reliability analysis result, the operation of the target turbine is controlled, thereby effectively improving the operation efficiency of the turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0017] FIG1 is an application environment diagram of a method for optimizing operation of a water turbine in one embodiment;

[0018] FIG2 is a schematic diagram of a flow chart of a method for optimizing operation of a water turbine in one embodiment;

[0019] FIG3 is a schematic structural diagram of a water turbine in one embodiment;

[0020] FIG4 is a schematic diagram of a flow chart of guide vane servomotor diameter selection in one embodiment;

[0021] FIG5 is a schematic structural diagram of a water turbine in another embodiment;

[0022] FIG6 is a schematic diagram of a flow chart of guide vane servomotor diameter selection in another embodiment;

[0023] FIG7 is a schematic diagram of a reliability analysis process of guide vane mechanism parts in one embodiment;

[0024] FIG8 is a structural block diagram of a water turbine operation optimization device in one embodiment;

[0025] FIG. 9 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0026] In the field of hydropower, the turbine is one of the core equipment for energy conversion in a hydropower station. It can convert the energy of water flow into rotational mechanical energy, and then drive the motor to generate electricity. The stable operation of the turbine not only affects the stable operation of the power system, but also affects the efficiency of the hydropower station. At present, in the actual operation of the turbine, the operating conditions of the turbine are relatively complex. There are usually various factors that affect the normal operation of the turbine, such as the impact of water flow or damage to the guide vane seal. The turbine is susceptible to cavitation and sand wear, resulting in fatigue cracks, which affects the operating efficiency at the least and causes component damage at the worst, affecting the safety of the generator set. For example, the performance of the guide vane operating mechanism parts in the turbine is also one of the important factors affecting the operating efficiency of the turbine. Therefore, there is an urgent need for an optimization method for the operation of the turbine to improve the operating efficiency of the turbine, thereby ensuring the stable operation of the power system and improving the efficiency of the hydropower station.

[0027] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0028] The turbine operation optimization method provided by the embodiment of the present application can be applied to the application environment shown in Figure 1. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. In response to the operation optimization instruction for the target turbine sent by the terminal 102, the server 104 first obtains the operating condition information of the target turbine; based on the operating condition information, the servo diameter of the guide vane servo in the target turbine is optimized to obtain the diameter optimization result of the guide vane servo; for each guide vane mechanism part other than the guide vane servo in the target turbine, based on the diameter optimization result, the guide vane mechanism part is reliability analyzed to obtain the reliability analysis result of each guide vane mechanism part; according to the diameter optimization result and the reliability analysis result, the target turbine is controlled to operate to obtain the operating result of the target turbine. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers and Internet of Things devices. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0029] In an exemplary embodiment, as shown in FIG2 , a method for optimizing the operation of a hydraulic turbine is provided, which is described by taking the method applied to the server 104 in FIG1 as an example, and includes:

[0030] Step S202: in response to the operation optimization instruction for the target water turbine, obtaining the operating condition information of the target water turbine.

[0031] Among them, the target turbine refers to the turbine that needs to be optimized for operation. It can be understood that the turbine is mainly composed of a rotating part and a fixed part, and includes a guide vane mechanism. The rotating part includes a runner, a main shaft, a main shaft seal, etc. The runner is the core component of the turbine and is responsible for converting the power of the water flow into rotational mechanical energy. The main shaft connects the runner and the generator to transmit rotational power, and the main shaft seal is used to prevent water leakage and affect the efficiency of the turbine. The fixed part includes a volute, a top cover, a bottom ring, a seat ring, a support ring, etc. The volute is used to guide the water flow to the runner, the top cover and the bottom ring fix the position of the runner, and the bottom ring and the support ring are used to support the structure of the entire turbine. The water guide mechanism is composed of guide vanes, guide vane servomotors and other guide vane mechanism parts, and other guide vane mechanism parts include control rings, connecting rods, piston rods, etc. The guide vanes are used to control the flow and direction of the water flow, and the guide vane servomotors are used to drive the guide vanes to rotate to adjust the opening of the guide vanes. As shown in FIG3 , a piston rod is connected to the guide vane servomotor, one end of the connecting rod is connected to the connecting plate of the guide vane, and the other end is connected to the control ring. The piston rod can be pushed and pulled under the action of hydraulic pressure to drive the control ring to rotate left and right. When the control ring rotates, it drives the connecting rod, and the connecting rod drives the guide vane to rotate. In this embodiment, the guide vane servomotor and the guide vane mechanism parts are optimized, and the reliability of the guide vane mechanism parts is analyzed within the optimal diameter range of the guide vane servomotor to optimize them. In this way, the operating space of the guide vane servomotor can be sufficient, and the stable operation of the guide vane mechanism parts can be ensured. In this way, the operation of the turbine is optimized, which can not only effectively improve the operation efficiency of the turbine, but also reduce the production cost.

[0032] The operation optimization instruction refers to an instruction for optimizing the operation strategy of the target turbine, and the operating condition information refers to the operating condition information of the target turbine, which may include turbine operating condition information and pump operating condition information. The turbine operating condition information refers to the operating condition information when the turbine generates electricity, and the pump operating condition information refers to the operating condition information when the turbine pumps water. The operating condition information can be used to establish a three-dimensional simulation model of the target turbine.

[0033] For example, when the server receives an instruction from the terminal to optimize the operating strategy of the target turbine, it can first obtain the turbine operating condition information and pump operating condition information corresponding to the target turbine, so as to subsequently establish a three-dimensional simulation model of the target turbine, thereby performing stress analysis on the target turbine.

[0034] Step S204: Based on the operating condition information, the servomotor diameter of the guide vane servomotor in the target turbine is optimized to obtain a diameter optimization result of the guide vane servomotor.

[0035] Among them, the servomotor diameter refers to the diameter of the guide vane servomotor. It can be understood that the guide vane servomotor diameter directly affects the operating space of the guide vane servomotor. The larger the servomotor diameter, the larger the required operating space, which will not only lead to crowded guide vane mechanism space, but also generate higher production costs. Therefore, in this embodiment, by optimizing the diameter of the guide vane servomotor to select a suitable servomotor diameter, not only can the efficiency of the guide vane drive be improved, thereby improving the operating efficiency of the turbine, but also can ensure the stability and safety of the entire generator set. The diameter optimization result refers to the result obtained after optimizing the servomotor diameter, which can include the target diameter of the guide vane servomotor and the safe operating space of the guide vane servomotor.

[0036] Exemplarily, after the server obtains the turbine operating condition information and pump operating condition information corresponding to the target turbine, it can establish a three-dimensional model of the target turbine and obtain the stress condition of the target turbine output during the operation of the three-dimensional model, so as to optimize the servomotor diameter of the guide vane servomotor according to the stress condition and obtain the target diameter of the guide vane servomotor and the safe operating space of the guide vane servomotor.

[0037] Step S206: for each guide vane mechanism part except the guide vane servomotor in the target turbine, reliability analysis is performed on the guide vane mechanism part based on the diameter optimization result to obtain the reliability analysis result of each guide vane mechanism part.

[0038] The reliability analysis may refer to the strength analysis of the guide vane mechanism parts and the life prediction of the guide vane mechanism parts. The reliability analysis results include the strength analysis results of the guide vane mechanism parts and the remaining operating life of the guide vane mechanism parts.

[0039] For example, based on the diameter optimization result of the guide vane servomotor, the server further performs a stiffness analysis and life prediction on other guide vane mechanism parts in the target turbine to improve the reliability and stability of the turbine operation, and obtains the stiffness analysis result and remaining operating life of each guide vane mechanism part.

[0040] Step S208, controlling the operation of the target water turbine according to the diameter optimization result and the reliability analysis result, and obtaining the operation result of the target water turbine.

[0041] The operation result may refer to the optimized operation status of the target turbine, such as the operation rate of the target turbine after optimization, the rate increase rate compared to before optimization, the current operation cost, the cost reduction degree compared to before optimization, etc.

[0042] Exemplarily, after the server obtains the diameter optimization results and reliability analysis results of the target turbine, it can generate an operation strategy for the target turbine based on the diameter optimization results and the reliability analysis results, thereby controlling the operation of the target turbine based on the operation strategy to obtain results such as the current operating speed of the target turbine, the rate increase compared to before optimization, the current operating cost, and the degree of cost reduction compared to before optimization.

[0043] In this embodiment, the server responds to the operation optimization instruction for the target turbine sent by the terminal, and first obtains the operating condition information of the target turbine, and then optimizes the servomotor diameter of the guide vane servomotor in the target turbine according to the operating condition information, so as to obtain accurate and reliable diameter optimization results. It can be understood that the guide vane servomotor is one of the core mechanisms for driving the operation of the turbine, and for the guide vane servomotor, the servomotor diameter affects the driving efficiency of the guide vane servomotor by affecting the operating space of the guide vane servomotor. Therefore, the diameter of the guide vane servomotor is one of the important factors affecting the operation of the turbine. The present application optimizes from the perspective of the diameter of the guide vane servomotor, and by selecting a suitable servomotor diameter, the guide vane servomotor has a reasonable and safe operating space, thereby improving the driving efficiency of the guide vane servomotor and thus improving the operation efficiency of the turbine. In addition, the present application also takes into account that other guide vane mechanism parts in the turbine will also have a certain impact on the operation of the turbine. Therefore, for each guide vane mechanism part except the guide vane servomotor in the target turbine, on the basis of the diameter optimization result of the guide vane servomotor, the guide vane mechanism parts are further subjected to reliability analysis, that is, the rigidity and remaining life of the guide vane mechanism parts are analyzed. Finally, according to the diameter optimization result and the reliability analysis result, the operation of the target turbine is controlled, thereby effectively improving the operation efficiency of the turbine.

[0044] In an exemplary embodiment, as shown in FIG4 , based on the operating condition information, the servomotor diameter of the guide vane servomotor in the target turbine is optimized to obtain the diameter optimization result of the guide vane servomotor, including:

[0045] Step S402: Based on the operating condition information, three-dimensional modeling is performed on the target water turbine to obtain a three-dimensional water turbine model of the target water turbine.

[0046] Step S404, running the three-dimensional water turbine model to obtain the guide vane water torque and guide vane friction resistance torque output by the three-dimensional water turbine model.

[0047] Among them, the three-dimensional turbine model refers to the three-dimensional simulation model of the target turbine. The guide vane water torque refers to the torque of the water flow acting on the turbine guide vane. As shown in Figure 5, the connecting plate is connected to the guide vane arm, and the guide vane arm is covered with a friction bushing. The guide vane friction resistance torque refers to the relative motion trend between the connecting plate and the friction bushing when the guide vane relay pushes the connecting plate to move, and the friction torque generated between the two drives the guide vane to rotate.

[0048] Exemplarily, CFD (Computational Fluid Dynamics) can be used to calculate various stresses of the target turbine. CFD is a method of using numerical methods to solve fluid dynamics equations. By numerically simulating the fluid motion process, the stress values ​​at various positions in the flow field can be obtained, thereby analyzing the fluid behavior. Therefore, in this embodiment, ANSYS CFD fluid simulation software can be used to perform three-dimensional simulation modeling on the overall structure of the target turbine to obtain a three-dimensional simulation model of the target turbine. ANSYS CFD is a fluid mechanics analysis software that provides a wealth of analysis tools and solvers to achieve various types of simulations including structure, dynamics, fluid, etc., based on the finite volume method and the finite element method to solve various flow problems. The finite element method and the finite volume method are numerical methods based on the spatial discretization of the model equation. The finite element method is to divide a large structure into a finite number of small areas called units. In each small area, it is assumed that the deformation and stress of the structure are simple, and the deformation and stress in the small area are easy to solve, and then the deformation and stress of the entire structure can be obtained. The finite volume method divides the calculation area into a series of non-repeating control volumes, and makes each grid point have a control volume around it. The differential equation to be solved is integrated for each control volume to obtain a set of discrete equations. The server can obtain the guide vane water torque and guide vane friction resistance torque of the three-dimensional turbine model through CFD calculation.

[0049] In one example, for the calculation of the guide vane friction torque, since the water pressure acting on the guide vane is the largest when the guide vane is in the closed position, the friction torque is the largest at this time. Therefore, the support reaction forces corresponding to the upper, middle and lower shaft diameters of the guide vane can be calculated through theoretical force analysis based on the water pressure on the guide vane when the guide vane is fully closed, and the friction resistance can be calculated based on the friction coefficient between the guide vane sleeve and the guide vane shaft diameter. Finally, the guide vane friction torque is calculated based on the shaft diameter size and friction resistance of the guide vane shaft diameter.

[0050] In one example, based on the turbine operating information, a joint CFD calculation can be performed on the volute and the movable guide vane, and based on the pump operating information, a segmented CFD calculation can be performed on the runner and the double-row blade cascade, which is the main flow-through component of the turbine and consists of fixed guide vanes and movable guide vanes. It should be noted that in order to ensure the accuracy of the calculation, in this embodiment, the volute, fixed guide vanes, movable guide vanes and runner are meshed separately. The mesh is one of the basic elements of CFD calculation. The mesh is composed of units and / or nodes, which can have almost any shape or size, and is used to solve the partial differential variance, and can discretize the region to facilitate simulation analysis of each divided object.

[0051] Step S406: determining a target operating force of a guide vane servomotor for driving the target water turbine based on the guide vane water torque and the guide vane friction resistance torque.

[0052] Step S408, optimizing the servomotor diameter of the guide vane servomotor according to the target operating force, and obtaining a diameter optimization result of the guide vane servomotor.

[0053] The target operating force refers to the force applied to the guide vane servomotor to drive the guide vane to rotate.

[0054] For example, after the server obtains the guide vane water moment and guide vane friction resistance moment of the target turbine through CFD calculation, the operating force required for the guide vane servomotor to drive the guide vane to rotate can be directly calculated through the guide vane water moment and the guide vane friction resistance moment. Thus, the servomotor diameter of the guide vane servomotor is optimized according to the target operating force and the corresponding operating oil pressure, and the diameter optimization result of the guide vane servomotor is obtained.

[0055] In this embodiment, a three-dimensional modeling method is used to calculate the guide vane water torque and guide vane friction resistance torque of the target turbine, thereby calculating the corresponding operating force, and then completing the diameter selection of the guide vane servomotor based on the operating force, thereby improving the accuracy of the guide vane servomotor diameter.

[0056] In an exemplary embodiment, as shown in FIG6 , according to the target operating force, the servomotor diameter of the guide vane servomotor is optimized to obtain the diameter optimization result of the guide vane servomotor, including:

[0057] Step S602: determining the safe operating oil pressure of the guide vane servomotor according to the target operating oil pressure required by the target operating force and the rated oil pressure of the guide vane servomotor.

[0058] Step S604: Optimizing the servomotor diameter of the guide vane servomotor based on the safe operating oil pressure to obtain a diameter optimization result of the guide vane servomotor.

[0059] Among them, the oil pressure is the pressure of the pressure oil source provided by the oil pressure system for the speed control system of the turbine generator set. The target operating oil pressure refers to the oil pressure corresponding to the target operating force, the rated oil pressure is the standard oil pressure under the safe operation of the guide vane servo, and the safe operating oil pressure is the safe operating oil pressure of the guide vane operator.

[0060] It is understandable that, under the premise of meeting the operating requirements of the turbine unit, in order to allow the guide vane servomotor to have sufficient operating space, a certain proportion of oil pressure margin can be reserved for the guide vane servomotor. Therefore, in this embodiment, on the basis of the target operating oil pressure and the rated oil pressure, a certain proportion of the oil pressure margin set in advance is reduced to obtain a safe operating oil pressure. The safe operating oil pressure can also be understood as the minimum operating oil pressure of the guide vane servomotor. The minimum operating oil pressure refers to the maximum oil pressure at which the guide vane servomotor can operate the moving guide vanes. In one example, the minimum operating oil pressure is lower than the rated oil pressure and the target operating oil pressure. The server can calculate the servomotor diameter of the guide vane servomotor according to the size of the guide vane itself and the safe operating oil pressure. The operating space corresponding to the diameter is the safe operating space of the guide vane servomotor.

[0061] In this embodiment, the servomotor diameter of the guide vane servomotor is calculated according to the rated oil pressure and the safe operating oil pressure of the guide vane servomotor, thereby improving the accuracy of the guide vane servomotor diameter and thus improving the accuracy of turbine operation optimization.

[0062] In an exemplary embodiment, the complexity analysis process of the guide vane mechanism parts includes: obtaining part structure information of the guide vane mechanism parts, and based on the part structure information, performing complexity analysis on the guide vane mechanism parts to obtain complexity analysis results for each guide vane mechanism part.

[0063] The part structure information refers to the structural composition information of the guide vane mechanism parts, including but not limited to the material, manufacturing cost, purpose, connection relationship with other guide vane mechanism parts, etc. The complexity analysis result is used to characterize the complexity of the part structure of the guide vane mechanism parts.

[0064] For example, before performing reliability analysis on the guide vane mechanism parts, the server may first obtain the material, manufacturing cost, purpose, connection relationship with other guide vane mechanism parts, etc. of each guide vane mechanism part, and then analyze the complexity of each guide vane mechanism part based on these structural composition information. For example, if a guide vane mechanism part has more uses or is connected with multiple other guide vane mechanism parts, then the structure of the guide vane mechanism part can be considered to be relatively complex. If a guide vane mechanism part has a single use or is connected with a small number or even no other guide vane mechanism parts, then the structure of the guide vane mechanism part can be considered to be relatively simple.

[0065] In practical applications, the complexity analysis results of the guide vane mechanism parts can be used for reliability analysis. Therefore, in one embodiment, based on the diameter optimization results, reliability analysis is performed on the guide vane mechanism parts to obtain the reliability analysis results of each guide vane mechanism part, including: based on the complexity analysis results and the diameter optimization results, reliability analysis is performed on the guide vane mechanism parts to obtain the reliability analysis results of each guide vane mechanism part.

[0066] Exemplarily, based on the complexity analysis results, different reliability analysis methods can be selected, so that reliability analysis of the guide vane mechanism parts can be performed according to different reliability analysis methods and diameter optimization results, and reliability analysis results of each guide vane mechanism part can be obtained. In one example, the reliability analysis methods include three-dimensional modeling and analytical methods. The three-dimensional modeling method has corresponding explanations in steps S302-S304 and will not be repeated here. The analytical rule refers to the use of material mechanics calculation formulas to calculate the stress conditions of the guide vane mechanism parts. For guide vane mechanism parts with complex structures, the three-dimensional modeling method can be used for reliability analysis, and for guide vane mechanism parts with simple structures, the analytical method can be used for reliability analysis.

[0067] In this embodiment, a suitable reliability analysis method is matched based on the complexity of the guide vane mechanism parts, so as to perform reliability analysis on the guide vane mechanism parts, thereby improving the accuracy and efficiency of the reliability analysis.

[0068] In an exemplary embodiment, as shown in FIG7 , based on the complexity analysis results and the diameter optimization results, reliability analysis is performed on the guide vane mechanism parts to obtain respective reliability analysis results of each guide vane mechanism part, including:

[0069] Step S702, when the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, the three-dimensional turbine model of the target turbine is operated, and the stiffness of the guide vane mechanism parts during operation is analyzed to obtain the stiffness analysis results of each guide vane mechanism part.

[0070] The safe operating space refers to the space in which the guide vane servo operates under the safe operating oil pressure. The results of the stiffness analysis are used to characterize the ability of the guide vane mechanism parts to resist damage or significant deformation under the action of external forces.

[0071] For example, when the complexity analysis results indicate that the structure of the guide vane mechanism parts is complex, the three-dimensional modeling method is selected for reliability analysis, that is, the server runs a three-dimensional simulation model of the target turbine. More specifically, it can be to build and run a three-dimensional simulation model of the guide vane mechanism parts to obtain the stiffness analysis results of each guide vane mechanism part output by the model.

[0072] Step S704, input the stiffness analysis results into the component life prediction model, perform life prediction on the guide vane mechanism components, and obtain the remaining operating life of each guide vane mechanism component.

[0073] The component life prediction model is a pre-established mathematical model for predicting the component life of the guide vane mechanism component. The remaining operating life refers to the remaining operating time of the guide vane mechanism component.

[0074] Exemplarily, the server inputs the results of the stiffness analysis of each guide vane mechanism part into a pre-established part life prediction model to predict the life of each guide vane mechanism part. In one example, the part life prediction model may include an Arrhenius model, a Coffin-Manson model, etc. The Arrhenius model accelerates the internal reaction of the part and causes the part to fail prematurely, thereby evaluating the life characteristics of the part in a short time. The Coffin-Manson model is a model for evaluating the fatigue life of a part. It predicts the life of a part under fatigue load by considering factors such as the stress level, stress amplitude, and strain amplitude of the part.

[0075] In one embodiment, before performing a part life prediction, the part type of each part part in the guide vane mechanism part can be determined first. The part part refers to each part on the guide vane mechanism part. The part type includes a weak part part and a stable part part. The weak part part is a part with a relatively weak structure on the guide vane mechanism part, and the stable part part is a part with a relatively stable structure on the guide vane mechanism part. The weak part part and the stable part part can be distinguished by the rigidity analysis result, that is, the rigidity analysis can be performed for each part on the guide vane mechanism part, so as to obtain the rigidity analysis result of each part. The higher the rigidity analysis result, the more stable the part is, and it is determined that the part belongs to the stable part part. The lower the rigidity analysis result, the weaker the part is, and it is determined that the part belongs to the weak part part.

[0076] In practical applications, in order to further improve the accuracy of the life prediction of parts, life prediction can be performed based on the weak parts and stable parts in the guide vane mechanism parts. Therefore, in one embodiment, the rigidity analysis results are input into the part life prediction model, and the life prediction of the guide vane mechanism parts is performed to obtain the remaining operating life of the guide vane mechanism parts, including: inputting the rigidity analysis results of the weak parts and the rigidity analysis results of the stable parts into the part life prediction model, and performing life prediction on the guide vane mechanism parts to obtain the remaining operating life of each guide vane mechanism part.

[0077] Exemplarily, the results of the rigidity analysis include the results of the rigidity analysis of the weak parts and the results of the rigidity analysis of the stable parts. The results of the rigidity analysis of the two types of parts can be input into the parts life prediction model to predict the life of the guide vane mechanism parts, thereby obtaining the remaining service life of each guide vane mechanism part. Furthermore, corresponding parts life prediction models can be established for the weak parts and the stable parts, respectively, so that the results of the rigidity analysis of the weak parts are input into the corresponding parts life prediction model to output the parts life of the weak parts, and the results of the rigidity analysis of the stable parts are input into the corresponding parts life prediction model to output the parts life of the stable parts, and then the parts life of the two types of parts are combined to comprehensively evaluate the remaining service life of the guide vane mechanism parts.

[0078] In this embodiment, the reliability of the guide vane mechanism parts is analyzed from two aspects of part stiffness and part life, and the part life model is used to predict the remaining operating life of the guide vane mechanism parts, thereby improving the comprehensiveness, accuracy and reliability of the reliability analysis of the guide vane mechanism parts, thereby improving the comprehensiveness, accuracy and reliability of the turbine operation optimization.

[0079] In a specific embodiment, the process of the water turbine operation optimization method includes:

[0080] In response to the operation optimization instruction for the target turbine, the turbine operating condition information and the pump operating condition information of the target turbine are obtained. Based on the turbine operating condition information and the pump operating condition information, a three-dimensional model of the target turbine is established, and the guide vane water moment and the guide vane friction resistance moment of the guide vane servomotor in the target turbine are calculated using CFD. Based on the guide vane water moment and the guide vane friction resistance moment, the target operating force of the guide vane servomotor driving the target turbine is calculated. According to the target operating oil pressure required for the target operating force and the rated oil pressure of the guide vane servomotor, the safe operating oil pressure of the guide vane servomotor is determined. Based on the safe operating oil pressure, the servomotor diameter of the guide vane servomotor is optimized to obtain the servomotor diameter of the guide vane servomotor and the corresponding safe operating space. For each guide vane mechanism part except the guide vane servomotor in the target turbine, the part structure information of each guide vane mechanism part is obtained, and based on the part structure information, the complexity analysis of the guide vane mechanism part is performed to obtain the complexity analysis result of each guide vane mechanism part. When the complexity analysis results indicate that the structure of the guide vane mechanism parts is simple, the stress of the guide vane mechanism parts is calculated using an analytical method to analyze its reliability. When the complexity analysis results indicate that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, the three-dimensional turbine model of the target turbine is operated, and the rigidity of the guide vane mechanism parts during operation is analyzed to obtain the rigidity analysis results of each guide vane mechanism part. The rigidity analysis results include the rigidity analysis results of the weak parts in the guide vane mechanism parts and the rigidity analysis results of the stable parts in the guide vane mechanism parts. The rigidity analysis results are input into the part life prediction model to predict the life of the guide vane mechanism parts and obtain the remaining operating life of each guide vane mechanism part. According to the servomotor diameter, the rigidity analysis results and the remaining operating life of each guide vane mechanism part, the target turbine is controlled to operate and the operating results of the target turbine are obtained.

[0081] In this embodiment, in response to the operation optimization instruction for the target turbine, the operating condition information of the target turbine is first obtained, and then the servomotor diameter of the guide vane servomotor in the target turbine is optimized according to the operating condition information to obtain an accurate and reliable diameter optimization result. It can be understood that the guide vane servomotor is one of the core mechanisms for driving the turbine, and for the guide vane servomotor, the servomotor diameter affects the driving efficiency of the guide vane servomotor by affecting the operating space of the guide vane servomotor. Therefore, the diameter of the guide vane servomotor is one of the important factors affecting the operation of the turbine. The present application optimizes from the perspective of the diameter of the guide vane servomotor, and by selecting a suitable servomotor diameter, the guide vane servomotor has a reasonable and safe operating space, thereby improving the driving efficiency of the guide vane servomotor and thus improving the operation efficiency of the turbine. In addition, the present application also takes into account that other guide vane mechanism parts in the turbine will also have a certain impact on the operation of the turbine. Therefore, for each guide vane mechanism part except the guide vane servomotor in the target turbine, on the basis of the diameter optimization result of the guide vane servomotor, the guide vane mechanism parts are further subjected to reliability analysis, that is, the rigidity and remaining life of the guide vane mechanism parts are analyzed. Finally, according to the diameter optimization result and the reliability analysis result, the operation of the target turbine is controlled, thereby effectively improving the operation efficiency of the turbine.

[0082] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0083] Based on the same inventive concept, the embodiment of the present application also provides a turbine operation optimization device for implementing the turbine operation optimization method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more turbine operation optimization device embodiments provided below can refer to the limitations of the turbine operation optimization method above, and will not be repeated here.

[0084] In an exemplary embodiment, as shown in FIG8 , a turbine operation optimization device is provided, including: an information acquisition module 802, for acquiring the operating condition information of the target turbine in response to an operation optimization instruction for the target turbine; a diameter selection module 804, for optimizing the servo diameter of the guide vane servo in the target turbine based on the operating condition information, and obtaining the diameter optimization result of the guide vane servo; a part optimization module 806, for performing reliability analysis on the guide vane mechanism parts of each guide vane mechanism part other than the guide vane servo in the target turbine based on the diameter optimization result, and obtaining the reliability analysis result of each guide vane mechanism part; an operation module 806, for controlling the operation of the target turbine according to the diameter optimization result and the reliability analysis result, and obtaining the operation result of the target turbine.

[0085] In one embodiment, the diameter selection module 804 is also used to: perform three-dimensional modeling of the target turbine based on the operating condition information to obtain a three-dimensional turbine model of the target turbine; run the three-dimensional turbine model to obtain the guide vane water torque and the guide vane friction resistance torque output by the three-dimensional turbine model; determine the target operating force of the guide vane servomotor that drives the target turbine to operate based on the guide vane water torque and the guide vane friction resistance torque; optimize the servomotor diameter of the guide vane servomotor according to the target operating force to obtain a diameter optimization result of the guide vane servomotor.

[0086] In one embodiment, the diameter selection module 804 is further used to: determine the safe operating oil pressure of the guide vane servomotor according to the target operating oil pressure required for the target operating force and the rated oil pressure of the guide vane servomotor; and optimize the servomotor diameter of the guide vane servomotor based on the safe operating oil pressure to obtain a diameter optimization result of the guide vane servomotor.

[0087] In one embodiment, the turbine operation optimization device is further used to: obtain part structure information of the guide vane mechanism parts, and based on the part structure information, perform complexity analysis on the guide vane mechanism parts to obtain a complexity analysis result of each guide vane mechanism part. The part optimization module 806 is further used to: perform reliability analysis on the guide vane mechanism parts based on the complexity analysis result and the diameter optimization result to obtain a reliability analysis result of each guide vane mechanism part.

[0088] In one embodiment, the part optimization module 806 is also used for: when the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, operating the three-dimensional turbine model of the target turbine, analyzing the stiffness of the guide vane mechanism parts during operation, and obtaining the stiffness analysis results of each guide vane mechanism part; inputting the stiffness analysis results into the part life prediction model, performing life prediction on the guide vane mechanism parts, and obtaining the remaining operating life of each guide vane mechanism part.

[0089] In one embodiment, the turbine operation optimization device is further used to: determine the part type of each part of the guide vane mechanism parts. The part optimization module 806 is further used to: input the rigidity analysis results of the weak part parts and the rigidity analysis results of the stable part parts into the part life prediction model, perform life prediction on the guide vane mechanism parts, and obtain the remaining operating life of each guide vane mechanism part.

[0090] Each module in the above-mentioned turbine operation optimization device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0091] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG9. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store turbine operation optimization data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for optimizing the operation of a turbine is implemented.

[0092] Those skilled in the art will understand that the structure shown in FIG. 9 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0093] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: in response to an operation optimization instruction for a target water turbine, the operating condition information of the target water turbine is obtained; based on the operating condition information, the servo diameter of the guide vane servo in the target water turbine is optimized to obtain a diameter optimization result of the guide vane servo; for each guide vane mechanism part other than the guide vane servo in the target water turbine, based on the diameter optimization result, the reliability analysis of the guide vane mechanism part is performed to obtain a reliability analysis result of each guide vane mechanism part; according to the diameter optimization result and the reliability analysis result, the operation of the target water turbine is controlled to obtain an operation result of the target water turbine.

[0094] In one embodiment, the processor further implements the following steps when executing the computer program: based on the operating condition information, three-dimensional modeling is performed on the target turbine to obtain a three-dimensional turbine model of the target turbine; the three-dimensional turbine model is operated to obtain the guide vane water torque and the guide vane friction resistance torque output by the three-dimensional turbine model; based on the guide vane water torque and the guide vane friction resistance torque, a target operating force of the guide vane servomotor that drives the target turbine to operate is determined; according to the target operating force, the servomotor diameter of the guide vane servomotor is optimized to obtain a diameter optimization result of the guide vane servomotor.

[0095] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the safe operating oil pressure of the guide vane servomotor according to the target operating oil pressure required for the target operating force and the rated oil pressure of the guide vane servomotor; optimizing the servomotor diameter of the guide vane servomotor based on the safe operating oil pressure to obtain a diameter optimization result of the guide vane servomotor.

[0096] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining part structure information of the guide vane mechanism parts, and based on the part structure information, performing complexity analysis on the guide vane mechanism parts to obtain complexity analysis results for each guide vane mechanism part; based on the diameter optimization results, performing reliability analysis on the guide vane mechanism parts to obtain reliability analysis results for each guide vane mechanism part, including: performing reliability analysis on the guide vane mechanism parts based on the complexity analysis results and the diameter optimization results to obtain reliability analysis results for each guide vane mechanism part.

[0097] In one embodiment, the processor further implements the following steps when executing the computer program: when the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, the three-dimensional turbine model of the target turbine is operated, and the stiffness of the guide vane mechanism parts during operation is analyzed to obtain the stiffness analysis results of each guide vane mechanism part; the stiffness analysis results are input into the part life prediction model, and the life of the guide vane mechanism parts is predicted to obtain the remaining operating life of each guide vane mechanism part.

[0098] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the part type of each part in the guide vane mechanism parts; the part type includes a weak part part and a stable part part; inputting the stiffness analysis results into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of the guide vane mechanism parts, including: inputting the stiffness analysis results of the weak part parts and the stiffness analysis results of the stable part parts into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of each guide vane mechanism part.

[0099] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: in response to an operation optimization instruction for a target water turbine, the operating condition information of the target water turbine is obtained; based on the operating condition information, the servomotor diameter of the guide vane servomotor in the target water turbine is optimized to obtain a diameter optimization result of the guide vane servomotor; for each guide vane mechanism part other than the guide vane servomotor in the target water turbine, based on the diameter optimization result, the reliability analysis of the guide vane mechanism part is performed to obtain a reliability analysis result of each guide vane mechanism part; according to the diameter optimization result and the reliability analysis result, the operation of the target water turbine is controlled to obtain an operation result of the target water turbine.

[0100] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the operating condition information, three-dimensional modeling of the target turbine is performed to obtain a three-dimensional turbine model of the target turbine; the three-dimensional turbine model is run to obtain the guide vane water torque and the guide vane friction resistance torque output by the three-dimensional turbine model; based on the guide vane water torque and the guide vane friction resistance torque, a target operating force of the guide vane servomotor that drives the target turbine to operate is determined; according to the target operating force, the servomotor diameter of the guide vane servomotor is optimized to obtain a diameter optimization result of the guide vane servomotor.

[0101] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the safe operating oil pressure of the guide vane servomotor based on the target operating oil pressure required for the target operating force and the rated oil pressure of the guide vane servomotor; optimizing the servomotor diameter of the guide vane servomotor based on the safe operating oil pressure to obtain a diameter optimization result of the guide vane servomotor.

[0102] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining part structure information of the guide vane mechanism parts, and based on the part structure information, performing complexity analysis on the guide vane mechanism parts to obtain complexity analysis results for each guide vane mechanism part; based on the diameter optimization results, performing reliability analysis on the guide vane mechanism parts to obtain reliability analysis results for each guide vane mechanism part, including: performing reliability analysis on the guide vane mechanism parts based on the complexity analysis results and the diameter optimization results to obtain reliability analysis results for each guide vane mechanism part.

[0103] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, a three-dimensional turbine model of the target turbine is operated, and the stiffness of the guide vane mechanism parts during operation is analyzed to obtain the stiffness analysis results of each guide vane mechanism part; the stiffness analysis results are input into the part life prediction model, and the life of the guide vane mechanism parts is predicted to obtain the remaining operating life of each guide vane mechanism part.

[0104] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the part type of each part in the guide vane mechanism parts; the part type includes a weak part part and a stable part part; inputting the stiffness analysis results into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of the guide vane mechanism parts, including: inputting the stiffness analysis results of the weak part parts and the stiffness analysis results of the stable part parts into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of each guide vane mechanism part.

[0105] In one embodiment, a computer program product is provided, comprising a computer program, which implements the following steps when executed by a processor: in response to an operation optimization instruction for a target water turbine, obtaining operating condition information of the target water turbine; optimizing the servo diameter of a guide vane servo in the target water turbine based on the operating condition information to obtain a diameter optimization result of the guide vane servo; performing reliability analysis on the guide vane mechanism parts of each guide vane mechanism part other than the guide vane servo in the target water turbine based on the diameter optimization result to obtain a reliability analysis result of each guide vane mechanism part; and controlling the operation of the target water turbine based on the diameter optimization result and obtaining an operation result of the target water turbine.

[0106] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the operating condition information, three-dimensional modeling of the target turbine is performed to obtain a three-dimensional turbine model of the target turbine; the three-dimensional turbine model is run to obtain the guide vane water torque and the guide vane friction resistance torque output by the three-dimensional turbine model; based on the guide vane water torque and the guide vane friction resistance torque, a target operating force of the guide vane servomotor that drives the target turbine to operate is determined; according to the target operating force, the servomotor diameter of the guide vane servomotor is optimized to obtain a diameter optimization result of the guide vane servomotor.

[0107] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the safe operating oil pressure of the guide vane servomotor based on the target operating oil pressure required for the target operating force and the rated oil pressure of the guide vane servomotor; optimizing the servomotor diameter of the guide vane servomotor based on the safe operating oil pressure to obtain a diameter optimization result of the guide vane servomotor.

[0108] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining part structure information of the guide vane mechanism parts, and based on the part structure information, performing complexity analysis on the guide vane mechanism parts to obtain complexity analysis results for each guide vane mechanism part; based on the diameter optimization results, performing reliability analysis on the guide vane mechanism parts to obtain reliability analysis results for each guide vane mechanism part, including: performing reliability analysis on the guide vane mechanism parts based on the complexity analysis results and the diameter optimization results to obtain reliability analysis results for each guide vane mechanism part.

[0109] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operating space of the guide vane servomotor, a three-dimensional turbine model of the target turbine is operated, and the stiffness of the guide vane mechanism parts during operation is analyzed to obtain the stiffness analysis results of each guide vane mechanism part; the stiffness analysis results are input into the part life prediction model, and the life of the guide vane mechanism parts is predicted to obtain the remaining operating life of each guide vane mechanism part.

[0110] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the part type of each part in the guide vane mechanism parts; the part type includes a weak part part and a stable part part; inputting the stiffness analysis results into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of the guide vane mechanism parts, including: inputting the stiffness analysis results of the weak part parts and the stiffness analysis results of the stable part parts into the part life prediction model, predicting the life of the guide vane mechanism parts, and obtaining the remaining operating life of each guide vane mechanism part.

[0111] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0112] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0113] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0114] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for optimizing the operation of a hydraulic turbine, characterized in that: The method comprises: In response to an operation optimization instruction for a target water turbine, obtaining operating condition information of the target water turbine; Based on the operating condition information, optimizing the servomotor diameter of the guide vane servomotor in the target turbine to obtain a diameter optimization result of the guide vane servomotor; For each guide vane mechanism part except the guide vane servomotor in the target turbine, based on the diameter optimization result, reliability analysis is performed on the guide vane mechanism part to obtain respective reliability analysis results of each guide vane mechanism part; According to the diameter optimization result and the reliability analysis result, the operation of the target water turbine is controlled to obtain the operation result of the target water turbine.

2. The method according to claim 1, characterized in that: The step of optimizing the servomotor diameter of the guide vane servomotor in the target turbine based on the operating condition information to obtain a diameter optimization result of the guide vane servomotor includes: Based on the operating condition information, three-dimensional modeling is performed on the target water turbine to obtain a three-dimensional water turbine model of the target water turbine; Running the three-dimensional water turbine model to obtain the guide vane water torque and guide vane friction resistance torque output by the three-dimensional water turbine model; Determining a target operating force of a guide vane servomotor for driving the target water turbine to operate based on the guide vane water torque and the guide vane friction resistance torque; According to the target operating force, the servomotor diameter of the guide vane servomotor is optimized to obtain a diameter optimization result of the guide vane servomotor.

3. The method according to claim 2, characterized in that The step of optimizing the servomotor diameter of the guide vane servomotor according to the target operating force to obtain a diameter optimization result of the guide vane servomotor includes: determining a safe operating oil pressure of the guide vane servomotor according to a target operating oil pressure required for the target operating force and a rated oil pressure of the guide vane servomotor; Based on the safe operating oil pressure, the servomotor diameter of the guide vane servomotor is optimized to obtain a diameter optimization result of the guide vane servomotor.

4. The method according to claim 1, characterized in that The method further comprises: Acquire part structure information of the guide vane mechanism parts, and based on the part structure information, perform complexity analysis on the guide vane mechanism parts to obtain complexity analysis results of each guide vane mechanism part; The reliability analysis of the guide vane mechanism parts is performed based on the diameter optimization result to obtain the reliability analysis result of each guide vane mechanism part, including: Based on the complexity analysis result and the diameter optimization result, reliability analysis is performed on the guide vane mechanism parts to obtain respective reliability analysis results of each guide vane mechanism part.

5. The method according to claim 4, characterized in that The diameter optimization result includes the safe operating space of the guide vane servomotor; the reliability analysis result includes the rigidity analysis result and the remaining operating life of the guide vane mechanism parts; The reliability analysis of the guide vane mechanism parts is performed based on the complexity analysis result and the diameter optimization result to obtain the reliability analysis result of each guide vane mechanism part, including: When the complexity analysis result indicates that the structure of the guide vane mechanism parts is complex, based on the safe operation space of the guide vane servomotor, the three-dimensional turbine model of the target turbine is operated to analyze the rigidity of the guide vane mechanism parts during operation, and obtain the rigidity analysis result of each guide vane mechanism part; The stiffness analysis results are input into a component life prediction model to perform life prediction on the guide vane mechanism components to obtain the remaining operating life of each of the guide vane mechanism components.

6. The method according to claim 5, characterized in that The method further comprises: Determine the part type of each part of the guide vane mechanism parts; the part type includes a weak part part and a stable part part; The step of inputting the stiffness analysis result into a component life prediction model, performing life prediction on the guide vane mechanism component, and obtaining the remaining operating life of the guide vane mechanism component includes: The results of the stiffness and strength analysis of the weak parts and the results of the stiffness and strength analysis of the stable parts are respectively input into the parts life prediction model, and the life of the guide vane mechanism parts is predicted to obtain the remaining operating life of each of the guide vane mechanism parts.

7. A turbine operation optimization device, characterized in that: The device comprises: An information acquisition module, configured to acquire operating condition information of a target water turbine in response to an operation optimization instruction for the target water turbine; A diameter selection module, configured to optimize the servomotor diameter of the guide vane servomotor in the target turbine based on the operating condition information, and obtain a diameter optimization result of the guide vane servomotor; a parts optimization module, configured to perform reliability analysis on each guide vane mechanism part except the guide vane servomotor in the target turbine based on the diameter optimization result, and obtain a reliability analysis result of each guide vane mechanism part; An operation module is used to control the operation of the target water turbine according to the diameter optimization result and the reliability analysis result to obtain the operation result of the target water turbine.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. 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 the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, 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 6 are implemented.

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