Water turbine adjusting system executing mechanism dynamic process abrasion quantitative evaluation method oriented to new energy access

Abstract

The invention discloses a new energy access-oriented water turbine adjusting system executing mechanism dynamic process wear quantitative evaluation method. The method is oriented to a second-level control level hydroelectric generation system, and particularly relates to water turbine adjusting system executing mechanism abrasion quantitative evaluation of the hydroelectric generation system under different degrees of new energy output scenes. According to the method, on the basis of an analytic hierarchy process, two aspects of guide vane action and vibration area operation duration are considered, and a new energy access-oriented water turbine adjusting system executing mechanism dynamic process wear quantitative evaluation model is established. Compared with the prior art, the method can evaluate the wear condition of the water turbine execution mechanism of the new energy accessed hydroelectric system along with the change of the new energy, is beneficial to the safety management and operation of traditional hydroelectric power, and is also beneficial to the construction and development of a novel multi-energy complementary power generation system containing the hydroelectric power.

Description

Technical Field

[0001] This invention belongs to the field of hydropower system performance evaluation, and in particular relates to a method for quantitative evaluation of dynamic process wear of actuators in hydro turbine regulating systems for new energy access. Background Technology

[0002] Hydropower is the world's third largest source of electricity, after coal and natural gas, and it is also the world's largest renewable energy source, accounting for 37% of all renewable energy generation. Among different renewable energy structures, the hydro-wind-solar multi-energy complementary system, with hydropower as the main source of flexible power, demonstrates excellent energy absorption capacity and is an important direction for future clean energy development. To meet the demand of the receiving end load, hydropower systems need to perform frequent tracking and regulation. If new multi-energy complementary power generation systems are built, coupled with the random and fluctuating output processes of wind and solar power, the hydropower system needs to have greater flexibility, durability, and reliability. This places a greater burden on the regulation of the hydropower system, and the actuators of the turbine regulation system also pose certain safety hazards as the operating time increases.

[0003] The dynamic process of the turbine regulating system actuator refers to the continuous friction, collision, and displacement of the regulating system actuator caused by load changes in the hydropower system. This dynamic process is essentially the continuous adjustment of the hydropower system as a flexible power source over time. Summarizing the existing technological background, the quantitative assessment methods for the dynamic process wear of turbine regulating system actuators for new energy access have the following shortcomings: 1) Regarding the research object: Research on the wear of turbine actuators lacks systematic and in-depth discussion, making it difficult to formulate scientific and effective prevention and response measures in actual maintenance and management; 2) Regarding performance evaluation: Evaluation of hydropower systems focuses on the stability and efficiency of regulation. Durability research involves multiple dimensions such as material aging, fatigue accumulation, and environmental adaptability, and these factors have complex interactions, making it difficult to provide a unified, clear, and universally applicable evaluation standard. This not only increases the difficulty of long-term operation and maintenance of hydropower facilities, but also limits the promotion and application of new technologies and materials in the hydropower field; 3) In terms of research methods: many studies, when evaluating the performance of new power generation systems, only remain at the level of qualitative description and comparison, lacking the introduction and comparative analysis of quantitative indicators, which greatly reduces the practicality and persuasiveness of the research results. In summary, although the existing technology provides a certain foundation for the quantitative evaluation of the dynamic process wear of the actuators of the turbine regulating system for new energy access, there are still some shortcomings that need further improvement. Therefore, based on the above-mentioned widespread technical problems, it is necessary to propose a method for the quantitative evaluation of the dynamic process wear of the actuators of the turbine regulating system for new energy access to solve the above problems. Summary of the Invention

[0004] The technical problem this invention aims to solve is to provide a method for quantitatively assessing the dynamic process wear of turbine regulating system actuators in response to new energy access. Specifically designed for multi-energy complementary power generation systems incorporating hydropower, this method establishes a framework for quantitatively assessing the dynamic process wear of turbine regulating system actuators in response to new energy access. It examines the mechanical friction and fatigue accumulation of the regulating system actuators caused by guide vane movement and the duration of operation in the unit's vibration zone. The method transforms commonly used power commands in power systems into changes in guide vane and unit vibration, and further into the wear status of the regulating system actuators. Based on the analytic hierarchy process (AHP), this method fully considers various factors that may cause wear to the turbine regulating system actuators, aiming to explore the wear of related hydraulic machinery during the dynamic regulation process of hydropower systems.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for quantitatively evaluating the dynamic process wear of actuators in a hydro-turbine regulating system for new energy integration, comprising the following steps: S1, New energy input scenario classification, including defining the new energy output volatility index and obtaining hydropower system output data; S2, Establish a framework for quantitative assessment of dynamic process wear of actuators in hydro-turbine regulation systems responding to new energy access; S3, Determine the evaluation indicators, including defining system wear indicators; S4, weighting of each indicator is performed based on the analytic hierarchy process; S5, numerical simulation calculation and data processing evaluation.

[0006] Preferably, in step S1, the definition of the new energy output volatility index includes: Considering fluctuation range I and fluctuation rate γ Volatility is defined as a comprehensive measure of volatility amplitude and volatility rate, ranging from 0 to 1, and represented by the letter . V The calculation formula is as follows: ; ; ; In the formula, The standard deviation of new energy output; This represents the average output of new energy sources; and They represent and The constant output of new energy sources; Represents the logarithm of the data; Indicates a time interval; and These represent the maximum fluctuation amplitude and fluctuation rate within a certain range, respectively. as well as The relative importance of the fluctuation amplitude and fluctuation rate representing the data on the output of new energy sources in this set, among which .

[0007] Preferably, in step S1, obtaining the power output data of the hydropower system includes: Based on the defined volatility index, a series of renewable energy output data with volatility ranging from low to high are selected to form independent variable factors based on the volatility of renewable energy output; the receiving-end load is set as... P 0, new energy output set at P n The per-unit output value of the hydropower system P u Represented as: ; In the formula, P r This refers to the rated power of the turbine unit.

[0008] Preferably, in step S2, establishing a framework for quantitatively assessing the dynamic process wear of the turbine regulating system actuators in response to new energy access includes: S201, The target power generation system is determined to be a hydropower and new energy multi-energy complementary power generation system: S202, Selection of independent variables: Based on the defined volatility index, multiple new energy output data with volatility ranging from small to large are selected to form independent variable factors based on the volatility of new energy output. S203, Selection of wear dependent variable: For different power generation systems, the working behaviors that may cause wear and tear on the actuators of the regulation system should be considered separately.

[0009] Preferably, the system wear indicators are defined as follows: Guide vane adjustment mileage and The total regulating mileage of hydropower stations It is the sum of the adjustment mileage of all units in the plant. It is the guide vane adjustment mileage of the target hydroelectric unit; Number of guide vane reversals and : Indicates the directional change of the actuator, including the number of times the main guide vanes of the hydropower station change direction. It is the sum of the number of guide vane reversals of all units within the plant. It is the number of guide vane commutations of the target hydroelectric generator unit; Vibration zone running time .

[0010] Preferably, in step S4, the weighting of each indicator based on the analytic hierarchy process includes: S401, Establish a hierarchical structure model: Based on the nature of the problem and the overall goal to be achieved, the problem is broken down into different components; Based on the interrelationships and hierarchical relationships among these factors, they are grouped and combined at different levels to form a multi-level analytical structure model; the model includes the highest level, the middle level, and the lowest level. S402, Construct the judgment matrix: After establishing the hierarchical model, for each criterion, pairwise comparisons are made between each scheme or factor under it, and a pairwise comparison matrix is ​​constructed of all factors in each level relative to a certain factor in the previous level. The elements in the matrix represent the relative importance of factors in the current level to factors related to factors in the previous level. A scale of 1 to 9 is used to represent the relative importance between factors. S403, Perform hierarchical single ranking and consistency test: By calculating the largest eigenvalue of the judgment matrix and its corresponding eigenvector, the importance ranking of the factor at this level to a certain factor at the previous level is obtained, i.e., hierarchical single ranking. A consistency check is performed. If the consistency index CI of the judgment matrix is ​​less than the threshold, the judgment matrix is ​​considered to have passed the consistency check; otherwise, the judgment matrix is ​​adjusted. S404, Calculate indicator weights: For each judgment matrix that passes the consistency test, the eigenvector corresponding to its eigenvalue is normalized to obtain the corresponding weight vector.

[0011] Preferably, in step S5, the numerical simulation calculation and data processing evaluation include: S501 converts new energy power output data into hydropower output data, and then through the governor system, converts the hydropower output data into turbine guide vane opening data, thereby performing numerical simulation calculations for different scenarios, and obtaining a set of data values ​​for wear indicators for each fluctuation index. S502, for a certain indicator d The maximum value of the corresponding indicator under all scenarios or working conditions. Normalization to the baseline yields the following metric: ; S503, based on the index weights in step S404, the wear index data corresponding to each volatility index is weighted and summed to obtain the corresponding wear score.

[0012] Preferably, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the dynamic process wear quantification assessment method for the actuator of the hydro-turbine regulating system for new energy access.

[0013] Preferably, a non-transitory computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the dynamic process wear quantification assessment method for the actuator of the hydro-turbine regulating system oriented towards new energy access.

[0014] Preferably, a computer program product includes a computer program that, when executed by a processor, implements the dynamic process wear quantification assessment method for the actuator of a hydro-turbine regulating system oriented towards new energy access.

[0015] The beneficial effects of this invention are as follows: The dynamic process wear quantification assessment method for turbine regulating system actuators designed in this invention is a widely applicable and highly flexible assessment tool. It can effectively assess the wear status of turbine actuators in new hydropower systems under different load conditions. It can adapt to the complex hydropower systems after the integration of new energy sources and quantify the wear of turbine actuators caused by fluctuations in new energy sources, providing strong support for the optimized operation and maintenance management of the system. Attached Figure Description

[0016] Figure 1 This is a framework diagram for the dynamic process wear quantification assessment of the actuators of a hydro-turbine regulating system for new energy access, as per the present invention. Figure 2 This is a schematic diagram illustrating the input scenario division of the power generation system of the present invention; Figure 3 This is a vibration zone division diagram of a certain unit of the present invention; Figure 4 This is a schematic diagram of wear score in an example of the present invention; Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0017] Example 1: like Figure 1 As shown, a method for quantitatively assessing the dynamic process wear of actuators in a hydro-turbine regulating system for new energy access includes the following steps: S1, New energy input scenario classification, including defining the new energy output volatility index and obtaining hydropower system output data; S2, Establish a framework for quantitative assessment of dynamic process wear of actuators in hydro-turbine regulation systems responding to new energy access; S3, Determine the evaluation indicators, including defining system wear indicators; S4, weighting of each indicator is performed based on the analytic hierarchy process; S5, numerical simulation calculation and data processing evaluation.

[0018] Preferably, in step S1, the definition of the new energy output volatility index includes: Considering fluctuation range I and fluctuation rate γ Volatility is defined as a comprehensive measure of volatility amplitude and volatility rate, ranging from 0 to 1, and represented by the letter . V The calculation formula is as follows: ; ; ; In the formula, The standard deviation of new energy output; This represents the average output of new energy sources; and They represent and The constant output of new energy sources; Represents the logarithm of the data; Indicates a time interval; and These represent the maximum fluctuation amplitude and fluctuation rate within a certain range, respectively. as well as The relative importance of the fluctuation amplitude and fluctuation rate representing the data on the output of new energy sources in this set, among which .

[0019] Preferably, in step S1, obtaining the power output data of the hydropower system includes: Based on the defined volatility index, a series of renewable energy output data with volatility ranging from low to high are selected to form independent variable factors based on the volatility of renewable energy output; the receiving-end load is set as... P 0, new energy output set at P n The per-unit output value of the hydropower system P u Represented as: ; In the formula, P r This refers to the rated power of the turbine unit.

[0020] Preferably, in step S2, establishing a framework for quantitatively assessing the dynamic process wear of the turbine regulating system actuators in response to new energy access includes: S201, The target power generation system is determined to be a hydropower and new energy multi-energy complementary power generation system: S202, Selection of independent variables: Based on the defined volatility index, multiple new energy output data with volatility ranging from small to large are selected to form independent variable factors based on the volatility of new energy output. S203, Selection of wear dependent variable: For different power generation systems, the working behaviors that may cause wear and tear on the actuators of the regulation system should be considered separately.

[0021] Preferably, the system wear indicators are defined as follows: Guide vane adjustment mileage and The total regulating mileage of hydropower stations It is the sum of the adjustment mileage of all units in the plant. It is the guide vane adjustment mileage of the target hydroelectric unit; Number of guide vane reversals and : Indicates the directional change of the actuator, including the number of times the main guide vanes of the hydropower station change direction. It is the sum of the number of guide vane reversals of all units within the plant. It is the number of guide vane commutations of the target hydroelectric generator unit; Vibration zone running time .

[0022] Preferably, in step S4, the weighting of each indicator based on the analytic hierarchy process includes: S401, Establish a hierarchical structure model: Based on the nature of the problem and the overall goal to be achieved, the problem is broken down into different components; Based on the interrelationships and hierarchical relationships among these factors, they are grouped and combined at different levels to form a multi-level analytical structure model; the model includes the highest level, the middle level, and the lowest level. S402, Construct the judgment matrix: After establishing the hierarchical model, for each criterion, pairwise comparisons are made between each scheme or factor under it, and a pairwise comparison matrix is ​​constructed of all factors in each level relative to a certain factor in the previous level. The elements in the matrix represent the relative importance of factors in the current level to factors related to factors in the previous level. A scale of 1 to 9 is used to represent the relative importance between factors. S403, Perform hierarchical single ranking and consistency test: By calculating the largest eigenvalue of the judgment matrix and its corresponding eigenvector, the importance ranking of the factor at this level to a certain factor at the previous level is obtained, i.e., hierarchical single ranking. A consistency check is performed. If the consistency index CI of the judgment matrix is ​​less than the threshold, the judgment matrix is ​​considered to have passed the consistency check; otherwise, the judgment matrix is ​​adjusted. S404, Calculate indicator weights: For each judgment matrix that passes the consistency test, the eigenvector corresponding to its eigenvalue is normalized to obtain the corresponding weight vector.

[0023] Preferably, in step S5, the numerical simulation calculation and data processing evaluation include: S501 converts new energy power output data into hydropower output data, and then through the governor system, converts the hydropower output data into turbine guide vane opening data, thereby performing numerical simulation calculations for different scenarios, and obtaining a set of data values ​​for wear indicators for each fluctuation index. S502, for a certain indicator d The maximum value of the corresponding indicator under all scenarios or working conditions. Normalization to the baseline yields the following metric: ; S503, based on the index weights in step S404, the wear index data corresponding to each volatility index is weighted and summed to obtain the corresponding wear score.

[0024] Preferably, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the dynamic process wear quantification assessment method for the actuator of the turbine regulating system for new energy access.

[0025] Preferably, a non-transitory computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the dynamic process wear quantification assessment method for the actuator of the hydro-turbine regulating system oriented towards new energy access.

[0026] Preferably, a computer program product includes a computer program that, when executed by a processor, implements the dynamic process wear quantification assessment method for the actuator of a hydro-turbine regulating system oriented towards new energy access.

[0027] Example 2: In this embodiment, the dynamic process wear quantification evaluation method of the turbine regulating system actuator for new energy access proposed in this invention is specifically implemented using a real hydropower station in my country as a prototype.

[0028] Step 1: Classification of New Energy Input Scenarios: The power station has a total installed capacity of 10.2 million kW, with a single unit rated output of 862.1 MW. If it is to be developed into a multi-energy complementary power generation system of hydropower, wind power, and solar power, the carrying capacity of hydropower needs to be considered to determine the installed capacity of wind and solar power. We analyzed over 1400 existing measured data points on wind and solar power output, calculated the corresponding volatility indicators, and selected several sets of data with volatility ranging from high to low.

[0029] Based on the volatility index, the scenarios are set as follows: three scenarios with high, medium and low volatility are set on a 15-minute scale, and two scenarios with low and high volatility are set on a second-level scale, for a total of 3×2=6 sets of scenarios.

[0030] Step 2: Establish a framework for quantitative assessment of dynamic process wear of actuators in hydro-turbine regulating systems oriented towards new energy access. The objective of this simulation is to assess the wear and tear of the turbine regulating system actuators in a hydropower system with new energy integration. The determining criteria are the guide vane adjustment mileage and guide vane reversal frequency of a single unit in the system. These two indicators are related to the frequency of mechanical friction during the guide vane adjustment process and are key indicators for judging the wear rate. Another criterion is the unit's operating time in the vibration zone. This parameter reveals the unit's operating time under vibration conditions that may cause additional wear and is crucial for assessing the cumulative wear effect. The solution layer represents several scenarios with varying volatility, specifically as follows: Figure 2 As shown; Step 3: Determine the evaluation indicators: For the guide vane adjustment mileage of a single unit in the target hydropower system Number of guide vane reversals and the duration of operation of the unit in the vibration zone. t vibration The formula for calculating the adjustment mileage of the guide vane adjustment is as follows, and the vibration zone division of this unit is as follows. Figure 3 As shown; ; In the formula, P e This is the rated power of the single unit.

[0031] Step 4: Assign weights to each indicator based on the Analytic Hierarchy Process (AHP): First, construct a judgment matrix, typically using a scale of 1 to 9 to represent the relative importance of factors, as shown in Table 1 below: Table 1: Statistical table of raw data for each indicator;

[0032] Then, by calculating the largest eigenvalue of the judgment matrix and its corresponding eigenvector, the importance ranking of the factors at this level to a certain factor at the previous level can be obtained, i.e., hierarchical single ranking. To ensure the rationality of the ranking, a consistency check is required. The purpose of the consistency check is to determine whether the judgment matrix has satisfactory consistency. If the consistency index (CI) of the judgment matrix is ​​less than 0.1 (or a threshold determined according to the specific situation), the judgment matrix is ​​considered to have passed the consistency check; otherwise, the judgment matrix needs to be adjusted.

[0033] Calculating the eigenvector E of the judgment matrix yields: ; Calculate its largest eigenvalue have to: ; The consistency index CI is calculated as follows: ; because Therefore, the random consistency index RI is taken as . Therefore, the consistency ratio (CR) is: ; because The consistency test of the judgment matrix is ​​passed. Therefore... The corresponding feature vector, after being normalized, becomes the weight vector of the corresponding index, which is calculated as [0.2; 0.4; 0.4].

[0034] Step 5: Numerical simulation calculation and data processing evaluation: To understand the wear and tear of the turbine regulating system actuators in hydropower systems oriented towards new energy integration, simulations were conducted for various preset scenarios to collect raw data on key indicators such as guide vane regulating mileage, guide vane reversal frequency, and vibration zone operating time. Specific data are shown in Table 1, providing a foundation for subsequent analysis and evaluation.

[0035] After obtaining the raw data, a normalization process was adopted to eliminate potential dimensional differences between different indicators and ensure the accuracy and comparability of the evaluation results. Normalization is a commonly used data preprocessing technique that transforms data of different magnitudes to the same scale, ensuring that each indicator has the same weight in the evaluation process. In this study, we normalized the data for the same indicators in Table 1, ensuring that the data for each indicator falls within the range of 0 to 1, facilitating subsequent weighted scoring and comprehensive analysis.

[0036] Next, based on the normalized data and the corresponding weights of each indicator, a weighted scoring method was used to quantitatively assess the wear and tear in various scenarios.

[0037] Ultimately, we obtained the following: Figure 4 The assessment results are shown below. These results visually demonstrate the wear and tear of the turbine regulating system actuators under different renewable energy fluctuation scenarios, providing a strong basis for subsequent decision-making and optimization. By comparing and analyzing the assessment results under different scenarios, we can more clearly understand the impact of renewable energy fluctuations on the wear and tear of hydropower system equipment, thereby providing scientific guidance for the system's operation and maintenance management.

[0038] The quantitative results presented in this example clearly demonstrate a significant correlation between the wear condition of the turbine regulating system actuators and the integration of new energy sources. Specifically, for every 1% increase in the volatility of new energy sources such as wind and solar power, the wear degree of the turbine regulating system actuators increases by approximately 0.81%. This shows that the volatility of new energy sources has a profound impact on the wear of critical equipment in hydropower systems. The increasing proportion of new energy sources in the power system, with their intermittency and randomness, presents unprecedented challenges to the stable operation of hydropower systems. In particular, when the volatility of new energy sources increases, the turbine regulating system needs to adjust the guide vane opening more frequently to adapt to changes in water flow and load, which undoubtedly exacerbates the mechanical friction and wear of the actuators. Therefore, to reduce the wear degree of the turbine regulating system actuators and extend the service life of the equipment, we need to take a series of effective measures to address the impact of new energy volatility. This includes, but is not limited to, optimizing the regulation strategy to improve the system's response speed and regulation accuracy; strengthening equipment maintenance to promptly identify and address potential wear problems; and exploring more advanced turbine regulating technologies and materials to improve the wear resistance of the equipment.

[0039] In summary, the quantitative results of this example not only provide us with an intuitive understanding of the impact of new energy volatility on the wear of turbine regulating system actuators, but also offer valuable reference for the optimized operation and equipment management of hydropower systems.

[0040] Figure 5 A schematic diagram of the physical structure of an electronic device is shown. In this diagram, the electronic device mainly consists of a processor, a communication interface, a memory, and a communication bus. These components exchange information with each other via the communication bus. Specifically, the processor can call logic instructions stored in the memory to run a method for quantitatively assessing the dynamic process wear of the actuators in a hydro-turbine regulating system oriented towards new energy integration.

[0041] Furthermore, if these logical instructions in the memory are implemented as software functional units and can be sold or used as independent products, they can be stored in a computer-readable storage medium. From this perspective, the technical solution of the present invention, or its innovation, can exist in the form of a software product. Such a software product contains instructions that, when loaded onto a computer device (such as a personal computer, server, or network device) and executed, can complete all or part of the processes of the methods described in the various embodiments of the present invention. The aforementioned storage media are wide and diverse, including but not limited to media capable of storing program code such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, and optical disks.

[0042] Furthermore, this invention also provides a computer program product containing computer programs that can be stored on a non-volatile computer-readable storage medium. When these programs are executed by a processor, the computer can run the aforementioned method for quantitatively assessing the wear of actuators in a hydro-turbine regulating system for new energy access.

[0043] Furthermore, the present invention also relates to a non-transitory computer-readable storage medium storing computer programs. When these programs are executed by a processor, they can implement the aforementioned method for quantitatively assessing the wear of actuators in a hydro-turbine regulating system for new energy access.

[0044] The description of the above device embodiments is for illustrative purposes only. Units mentioned as independent components may or may not be physically separated; components shown as units may or may not be physical entities, meaning they may be located in the same location or distributed across multiple network units. Depending on actual needs, some or all modules can be selected to achieve the objectives of this embodiment. Those skilled in the art can understand and implement this without creative effort.

[0045] Through the above description of the embodiments, those skilled in the art will understand that each embodiment can be implemented by combining software with necessary general-purpose hardware platforms, or by a purely hardware approach. Based on this understanding, the above technical solutions, or their innovative points, can also be presented in the form of a software product. This software product is stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and contains instructions that enable a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some portions thereof.

[0046] Obviously, the above description is only a preferred embodiment of the present invention. It should be noted that, without departing from the basic principles of the present invention, those skilled in the art can make various improvements and modifications to the above quantitative evaluation method for different types of hydropower system objects, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for quantitatively evaluating the wear of the actuator of a hydroelectric turbine regulation system in the presence of new energy access, characterized by, Comprise the following steps: S1, new energy input scene division, including defining new energy output fluctuation index and obtaining hydropower system output data; S2, establish the dynamic process wear quantitative evaluation framework of the governing system actuator responding to the access of new energy; S3, determine the evaluation index, including defining the system wear index; S4, weight division of each index based on the analytic hierarchy process; S5, numerical simulation calculation and data processing evaluation.

2. The method of claim 1, wherein the method is a method of quantitatively evaluating the wear of the dynamic process of the actuator of the hydro-turbine governing system for new energy access, characterized in that, In step S1, the definition of new energy output fluctuation index includes: Considering the fluctuation amplitude I and the fluctuation rate γ, the fluctuation is defined as the comprehensive consideration of the fluctuation amplitude and the fluctuation rate, the value range is 0 to 1, represented by the letter V, the calculation formula is as follows: ； ； ； In the formula, represents the standard deviation of new energy output; represents the average value of new energy output; and respectively represent and new energy output at the moment; represents the data logarithm; represents the time interval; and respectively represent the fluctuation amplitude and the maximum fluctuation rate within a certain range; and represent the relative importance of the fluctuation amplitude and the fluctuation rate of the group of new energy output data, wherein .

3. The method of claim 2, wherein the method is a method of quantitatively evaluating the wear of the dynamic process of the actuator of the hydro-turbine governing system for new energy access, characterized in that, In step S1, obtaining hydropower system output data includes: According to the defined volatility index, a series of new energy output data from small to large volatility is selected to form the independent variable factor based on the volatility of new energy output; the receiving end load is set as P 0, and the new energy output is set as P n , then the unit value of the hydropower system output is P u , which is represented as: ； In the formula, P r P is the rated power of the turbine unit.

4. The method of claim 1, wherein the method is a method of quantitatively evaluating the wear of the dynamic process of the actuator of the hydro-turbine governing system for new energy access, characterized in that, In step S2, establishing the dynamic process wear quantitative evaluation framework of the governing system actuator responding to the access of new energy includes: S201, determining the target power generation system as a hydropower and new energy multi-energy complementary power generation system: S202, selection of independent variables: According to the defined fluctuation index, select multiple new energy output data from small to large fluctuation, form the independent variable factor based on new energy output fluctuation; S203, selection of dependent variable of wear: For different power generation systems, consider their possible working behaviors that may cause wear of the governing system actuator.

5. The method of claim 4, wherein the method is a method of quantitatively evaluating the wear of the dynamic process of the actuator of the hydro-turbine governing system for new energy access, characterized in that, The definition of system wear index includes: Guide vane adjustment mileage and The total regulating mileage of hydropower stations It is the sum of the adjustment mileage of all units in the plant. It is the guide vane adjustment mileage of the target hydroelectric unit; number of guide vane reversals and : represents the direction change of the actuator, wherein the total number of guide vane reversals of the hydropower station is the sum of the number of guide vane reversals of each unit in the plant, is the number of guide vane reversals of the target hydropower unit; Vibration zone runtime .

6. The method of claim 1, wherein the method is a method of quantitatively evaluating the wear of the dynamic process of the actuator of the hydro-turbine governing system for new energy access. In step S4, weight division of each index based on the analytic hierarchy process includes: S401, establish a hierarchical structure model: According to the nature of the problem and the overall goal to be achieved, the problem is decomposed into different constituent factors; According to the mutual influence and membership relationship between these factors, these factors are aggregated and combined according to different levels to form a multi-level analysis structure model; The model includes the highest layer, the middle layer and the lowest layer; S402, construct the judgment matrix: After establishing the hierarchical structure model, for each criterion, compare the schemes or factors under it pairwise, construct the pairwise comparison matrix of all factors in each level relative to a factor in the previous level; The elements in the matrix represent the relative importance between the factors in this level related to the factors in the previous level; The relative importance between factors is represented by a scale of 1-9; S403, perform hierarchical single ordering and consistency check: By calculating the largest eigenvalue of the judgment matrix and its corresponding eigenvector, the importance ordering of the factors in this level relative to a factor in the previous level, i.e. the hierarchical single ordering, is obtained; Conduct consistency check, if the consistency index CI of the judgment matrix is less than the threshold value, it is considered that the judgment matrix passes the consistency check, otherwise adjust the judgment matrix; S404, calculate the index weight: For each judgment matrix that passes the consistency check, the eigenvector corresponding to the eigenvalue after normalization is the corresponding weight vector.

7. The method of claim 6, wherein the method is a method of quantitatively evaluating the wear of the dynamic process of the actuator of the hydro-turbine governing system for new energy access, characterized in that, In step S5, numerical simulation calculation and data processing evaluation includes: S501, the new energy output data is converted into hydropower output data, and then the hydropower output data is converted into the guide vane opening data of the water turbine through the governor system, so that numerical simulation and calculation are performed on different scenes, and a group of data values of the wear index corresponding to each volatility index are obtained; S502, for a certain index d The maximum value of the corresponding index under all scenes or working conditions Normalization is taken as a reference, and the processed index is: ； S503, according to the index weight in step S404, the wear index data corresponding to each volatility index is weighted and summed to obtain a corresponding wear score.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the method for quantitatively evaluating the wear of the dynamic process of the executing mechanism of the water turbine regulating system facing the new energy access when the program is executed. 9.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the method for quantitatively evaluating the wear of the dynamic process of the executing mechanism of the water turbine regulating system facing the new energy access.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the method for quantitatively evaluating the wear of the dynamic process of the executing mechanism of the water turbine regulating system facing the new energy access.

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