Method, device and equipment for adjusting start-stop control mode of wind turbine generator system and medium

Abstract

The application provides a wind turbine unit start-stop control mode adjustment method, device, equipment and medium, and relates to the technical field of wind power generation. The method comprises the following steps: obtaining historical time series data generated by a wind turbine unit in a historical operation process in an original start-stop control mode; calculating evaluation data of the wind turbine unit on each index combination in a preset evaluation index model according to the historical time series data; determining that the original start-stop control mode is abnormal when any evaluation data meets a preset condition of a corresponding index; and adjusting the original start-stop control mode according to an adjustment mode corresponding to the index combination to obtain a target start-stop control mode. The above method improves the actual power generation of the wind turbine unit and improves the wind energy utilization rate.

Description

Technical Field

[0001] This application relates to the field of wind power generation technology, and in particular to a method, device, equipment and medium for adjusting the start-stop control mode of a wind turbine generator set. Background Technology

[0002] The start-up and shutdown control of wind turbine generators is a dynamic control process. It should be optimally adjusted according to wind conditions to minimize frequent shutdowns caused by wind speed fluctuations in low wind speed ranges. At the same time, it should reduce waiting time and start up in a timely manner to improve the efficiency of wind turbine generators in entering the power generation state, so as to maximize the utilization of wind energy. This is especially necessary for areas with frequent power curtailment to increase power generation at low wind speeds.

[0003] However, the meteorological conditions at the actual installation locations of wind turbine generators differ from the design standards. After commissioning, it is difficult to determine whether the start-stop control reaches its optimal level under low wind speeds, and whether the aerodynamic performance of the entire unit affects the effectiveness of the start-stop control as the operating time increases. Currently, there is a lack of reasonable methods for evaluating and correcting whether the start-stop control is functioning properly.

[0004] Therefore, existing technologies suffer from low wind energy utilization rates because they rely on the same start-stop control strategy for wind turbine generators for a long time, especially after prolonged operation when the strategy becomes inapplicable. Summary of the Invention

[0005] This application provides a method, device, equipment, and medium for adjusting the start-stop control mode of a wind turbine generator set, in order to solve the technical problems of low power generation and low wind energy utilization rate of existing wind turbine generator sets.

[0006] According to a first aspect of this application, a method for adjusting the start-stop control mode of a wind turbine generator set is provided, comprising:

[0007] Acquire historical time-series data generated by wind turbine generators during historical operation using the original start-stop control method;

[0008] Based on the historical time series data, calculate the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model;

[0009] If any of the evaluation data meets the preset conditions of the corresponding indicator, it is determined that the original start-stop control method is abnormal;

[0010] Based on the adjustment method corresponding to the combination of indicators, the original start-stop control method is adjusted to obtain the target start-stop control method.

[0011] Optionally, the step of calculating the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model based on the historical time-series data includes:

[0012] Based on the historical time-series data, the characteristic data of the wind turbine generator set are calculated;

[0013] Based on the characteristic data of the wind turbine generator set, the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model is calculated.

[0014] Optionally, calculating the characteristic data of the wind turbine generator based on the historical time-series data includes:

[0015] The evaluation period is determined, and data segments of the wind turbine generator within the evaluation period are extracted from the historical time-series data; wherein, the data segments include wind speed and power.

[0016] Based on the data fragments, the various states of the wind turbine generator set are identified, and the power curve of the wind turbine generator set is plotted; wherein, the states include at least one of the following: standby state, start-up state, power generation state, first shutdown state and second shutdown state, and the power curve is used to reflect the relationship between the wind speed and the power.

[0017] Based on the power curve of the wind turbine generator set, calculate the power loss of the wind turbine generator set under each state, and based on the power loss of the wind turbine generator set under each state, calculate the power consumption of the wind turbine generator set.

[0018] The power loss and power consumption of the wind turbine generator set under various conditions are used as characteristic data of the wind turbine generator set.

[0019] Optionally, after identifying the various states of the wind turbine generator set, the step of calculating the characteristic data of the wind turbine generator set based on the historical time-series data further includes:

[0020] The number of times the wind turbine generator set switches from the power generation state to the first shutdown state is counted to obtain the first shutdown count;

[0021] The number of times the wind turbine generator set switches from the start-up state to the second shutdown state is counted to obtain the second shutdown count;

[0022] Both the first number of shutdowns and the second number of shutdowns are used as characteristic data of the wind turbine generator set.

[0023] Optionally, the preset evaluation index model includes a first index combination, a second index combination, a third index combination, a fourth index combination, and a fifth index combination;

[0024] The step of calculating the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model based on the characteristic data of the wind turbine generator set includes:

[0025] The sum of the power loss of the wind turbine generator set in the standby state, the power loss in the start-up state, the power loss in the first shutdown state, and the power loss in the second shutdown state is used as the first evaluation data of the wind turbine generator set on the first index combination.

[0026] The sum of the power loss of the wind turbine in the standby state and the power loss in the start-up state is used as the second evaluation data of the wind turbine on the second index combination.

[0027] The sum of the power loss of the wind turbine generator set in the first shutdown state and the power loss in the second shutdown state is used as the third evaluation data of the wind turbine generator set on the third index combination.

[0028] The sum of the first number of shutdowns and the second number of shutdowns is used as the fourth evaluation data of the wind turbine generator set on the fourth combination of indicators;

[0029] The power consumption of the wind turbine generator set is used as the fifth evaluation data of the wind turbine generator set on the fifth index combination.

[0030] Optionally, based on the power curve of the wind turbine generator set, the power loss of the wind turbine generator set under various states is calculated, including:

[0031] The data segment is divided according to the time of each state to obtain the data sub-segment corresponding to each state;

[0032] The data segments are smoothed and filtered to obtain the wind speed distribution corresponding to each state;

[0033] Based on the wind speed distribution corresponding to each state, determine the time length corresponding to each state of the wind turbine generator set;

[0034] Based on the time length corresponding to each state of the wind turbine generator set and the power curve of the wind turbine generator set, the power loss of the wind turbine generator set in each state is calculated.

[0035] Optionally, the original start-stop control method is adjusted according to the adjustment method corresponding to the combination of indicators to obtain the target start-stop control method, including any of the following cases:

[0036] Based on the adjustment method corresponding to the first indicator combination, the start method in the original start-stop control method is adjusted to obtain the target start-stop control method;

[0037] Based on the adjustment method corresponding to the second indicator combination, the starting conditions in the original start-stop control method are adjusted to obtain the target start-stop control method;

[0038] The shutdown conditions in the original start-stop control method are adjusted according to the adjustment method corresponding to the third indicator combination or the fourth indicator combination to obtain the target start-stop control method.

[0039] According to a second aspect of this application, a wind turbine generator start-stop control mode adjustment device is provided, comprising:

[0040] The acquisition module is used to acquire historical time-series data generated by the wind turbine generator set during its historical operation in the original start-stop control mode.

[0041] The calculation module is used to calculate the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model based on the historical time series data.

[0042] The determination module is used to determine that there is an anomaly in the original start-stop control method when any of the evaluation data meets the preset conditions of the corresponding indicator;

[0043] The adjustment module is used to adjust the original start-stop control method according to the adjustment method corresponding to the combination of indicators, so as to obtain the target start-stop control method.

[0044] According to a third aspect of this application, an electronic device is provided, comprising: at least one processor and a memory;

[0045] The memory stores computer-executed instructions;

[0046] The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the wind turbine generator start-stop control mode adjustment method as described in the first aspect above.

[0047] According to a fourth aspect of this application, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, which, when executed by a processor, are used to implement the wind turbine generator start-stop control mode adjustment method as described in the first aspect above.

[0048] According to a fifth aspect of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the wind turbine generator start-stop control mode adjustment method described in the first aspect.

[0049] This application provides a method for adjusting the start-stop control mode of a wind turbine generator set. The method involves acquiring historical time-series data generated during the historical operation of the wind turbine generator set using its original start-stop control mode; calculating evaluation data for each combination of indicators in a preset evaluation index model based on the historical time-series data; determining that the original start-stop control mode is abnormal when any evaluation data meets the preset conditions of the corresponding indicator; and adjusting the original start-stop control mode according to the adjustment method corresponding to the indicator combination to obtain the target start-stop control mode.

[0050] This application uses a combination of multiple indicators to determine whether there are any abnormalities in the original start-stop control method during historical operation. If abnormalities are found, the original start-stop control method is adaptively adjusted according to the adjustment method corresponding to the indicator combination. It has a high degree of intelligence and automatically adjusts the original start-stop control method. In turn, by applying the target start-stop control method, the actual power generation of the wind turbine generator in the subsequent operation process is improved, thereby increasing the wind energy utilization rate.

[0051] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0052] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0053] Figure 1 A flowchart illustrating a method for adjusting the start-stop control mode of a wind turbine generator set, provided in an embodiment of this application;

[0054] Figure 2 A flowchart illustrating another method for adjusting the start-stop control mode of a wind turbine generator set, provided in an embodiment of this application;

[0055] Figure 3(a) is a schematic diagram of the power curve provided in an embodiment of this application;

[0056] Figure 3(b) is a schematic diagram of the wind speed distribution provided in the embodiment of this application;

[0057] Figure 4 A flowchart illustrating another method for adjusting the start-stop control mode of a wind turbine generator set, provided in an embodiment of this application;

[0058] Figure 5 A schematic diagram of a wind turbine generator start-stop control mode adjustment device provided in this application embodiment;

[0059] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0060] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0062] The meteorological conditions at the actual installation location of wind turbine generator sets differ from the design standards. After commissioning, it is difficult to determine whether the start-stop control reaches its optimal level under low wind speeds, and whether the aerodynamic performance of the entire unit affects the effectiveness of the start-stop control as the operating time increases. Currently, there is a lack of reasonable methods for evaluating and correcting whether the start-stop control is functioning properly.

[0063] Therefore, existing technologies suffer from low wind energy utilization rates because they rely on the same start-stop control strategy for wind turbine generators for a long time, especially after prolonged operation when the strategy becomes inapplicable.

[0064] To address the aforementioned technical problems, the overall inventive concept of this application is to provide a method for adjusting the start-stop control mode of a wind turbine generator set, applicable to the field of wind power, to improve the power generation of the wind turbine generator set and enhance the utilization rate of wind energy.

[0065] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0066] Example 1:

[0067] Figure 1 This is a flowchart illustrating a method for adjusting the start-stop control mode of a wind turbine generator set, as provided in an embodiment of this application. Figure 1 As shown, the method in this embodiment includes:

[0068] S10. Obtain historical time-series data generated by the wind turbine generator set during its historical operation using the original start-stop control method.

[0069] It should be understood that the original start-stop control method is also known as the original low-wind-speed start-stop control method for wind turbine generators. Historical time-series data includes, but is not limited to, information such as wind speed, power, blade angle, speed, and windward angle.

[0070] S20. Based on historical time series data, calculate the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model.

[0071] In summary, the indicators in this embodiment include two categories: indicators related to start-stop control losses and indicators related to the number of shutdowns. The indicators related to start-stop control losses (reflected in the amount of electricity lost due to start-stop control) include: electricity loss in standby mode, electricity loss in startup mode, electricity loss in power generation mode, electricity loss due to low-wind shutdown in power generation mode, electricity loss due to low-wind shutdown in startup mode, and electricity consumption. The indicators related to the number of shutdowns (reflected in the number of shutdowns) include: the number of low-wind shutdowns in power generation mode and the number of low-wind shutdowns in startup mode. Furthermore, the calculation process based on the above two types of indicators is described in Example 2 below, and will not be repeated here.

[0072] In this embodiment of the application, the indicator combination can be adaptively set according to the actual situation. The indicator combination includes the first indicator combination, the second indicator combination, the third indicator combination, the fourth indicator combination and the fifth indicator combination. The specific description of the evaluation data on each indicator combination is shown in steps S2021 to S2025 below, and will not be repeated here.

[0073] S30. When any evaluation data meets the preset conditions of the corresponding indicator, it is determined that there is an anomaly in the original start-stop control method.

[0074] It should be understood that an indicator can refer to a numerical limitation, and this embodiment does not limit the specific definition of the preset conditions corresponding to the indicators. For example, the first preset condition (condition a) is that the first evaluation data of the first indicator combination is greater than the first preset threshold; the second preset condition (condition b) is that the second evaluation data of the second indicator combination is greater than the second preset threshold; the third preset condition (condition c) is that the third evaluation data of the third indicator combination is greater than the third preset threshold; the fourth preset condition (condition d) is that the fourth evaluation data of the fourth indicator combination is greater than the fourth preset threshold; and the fifth preset condition (condition e) is that the fifth evaluation data of the fifth indicator combination is less than the first evaluation data of the first indicator combination.

[0075] By executing steps S20 and S30, the embodiments of this application can identify the anomalies in the original low wind speed start-stop control mode of the wind turbine generator, thereby providing data support for selecting a correction method in step S40.

[0076] S40. Adjust the original start-stop control method according to the adjustment method corresponding to the indicator combination to obtain the target start-stop control method.

[0077] It should be understood that adjustment methods, or correction methods, are used. Different combinations of indicators correspond to different adjustment methods, which will be described in detail below and will not be repeated here.

[0078] This application uses a combination of multiple indicators to determine whether there are any abnormalities in the original start-stop control method during historical operation. If abnormalities are found, the original start-stop control method is adaptively adjusted according to the adjustment method corresponding to the indicator combination. It has a high degree of intelligence and automatically adjusts the original start-stop control method. In turn, by applying the target start-stop control method, the actual power generation of the wind turbine generator in the subsequent operation process is improved, thereby increasing the wind energy utilization rate.

[0079] In one possible implementation, S40, the original start-stop control method is adjusted according to the adjustment method corresponding to the indicator combination to obtain the target start-stop control method, including any of the following cases:

[0080] Based on the adjustment method corresponding to the first indicator combination, the start method in the original start-stop control method is adjusted to obtain the target start-stop control method.

[0081] Based on the adjustment method corresponding to the second indicator combination, the starting conditions in the original start-stop control method are adjusted to obtain the target start-stop control method.

[0082] The shutdown conditions in the original start-stop control method are adjusted according to the adjustment method corresponding to the third indicator combination or the fourth indicator combination to obtain the target start-stop control method.

[0083] In this embodiment, the normal grid connection process of the wind turbine generator is: shutdown-standby-start-generation. The original start-stop control method provides switching conditions between all adjacent states. This embodiment adjusts the original start-stop control method, which essentially involves resetting each switching condition.

[0084] For example, when condition a is met, the optimization strategy is initiated, that is, optimization is performed on each wind turbine.

[0085] When condition b is met, the switching conditions from standby to startup are reduced, i.e., the speed threshold or delay time is reduced. Specifically, this optimization step indicates that the loss between standby and startup states is high and needs optimization. The optimization focuses on the switching conditions between standby and startup states, including the speed threshold or speed delay time for transitioning from standby to startup. Meeting condition b indicates that the previous program settings wasted a lot of energy, and the wind turbine needs to enter the startup state as soon as possible.

[0086] When condition c or condition d is met, the shutdown conditions are raised, and the power threshold or delay time is lowered. Specifically, meeting condition c or condition d means that the wind turbine generator set experiences significant losses due to the control system's judgment of low wind speed causing it to shut down during power generation and startup. In this case, the shutdown logic needs to be optimized, for example, by adjusting the minimum power or delay time during power generation.

[0087] To avoid over-optimization, measures can be stopped once condition e is met.

[0088] In practical applications, this wind turbine start-stop control adjustment method was applied to a wind farm, and problems were found in 17 power stations. The original low-wind-speed start-stop control method used by the abnormal wind turbines in these abnormal power stations was optimized. Through optimization, the annual power generation can be increased by 20 million kWh, which greatly improves the actual power generation and wind energy utilization rate.

[0089] The wind turbine generator start-stop control method provided in this embodiment can serve as a low-input, high-output efficiency assessment and improvement technique. In essence, it is an evaluation and correction method that can evaluate the quality of wind turbine generator start-stop control at low wind speeds. This embodiment uses a combination of multiple indicators to evaluate the start-stop control process of wind turbine generators at low wind speeds, and provides a correction method based on the evaluation results of the indicator combination reflected by the evaluation data.

[0090] Since historical time-series data can reflect the wind conditions during the actual operation of wind turbine generators, this embodiment can ensure that the evaluation results obtained are true and reliable based on the historical time-series data. The adjustment method is highly operable and can effectively identify whether there are any abnormalities in the start-up and shutdown control of wind turbine generators at low wind speeds. In turn, the actual power generation of wind turbine generators at low wind speeds can be improved through correction methods, thereby improving wind energy utilization and increasing the operator's revenue.

[0091] Based on the above embodiments, the technical solution of this application will be described in more detail below with reference to several specific embodiments.

[0092] Example 2:

[0093] Figure 2 This is a flowchart illustrating another method for adjusting the start-stop control mode of a wind turbine generator set, provided in an embodiment of this application. Figure 1 Based on the illustrated embodiment, this embodiment focuses on Figure 1 S20 in the text is further refined. For example... Figure 2 As shown, step S20 involves calculating the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model based on historical time-series data, including:

[0094] S201. Calculate the characteristic data of the wind turbine generator set based on historical time series data.

[0095] In this embodiment of the application, the characteristic data of the wind turbine generator set includes: power loss in standby state, power loss in startup state, power loss in power generation state, power loss due to low wind speed during power generation state, power loss due to low wind speed during startup state, power consumption, number of times the generator set stops during low wind speed, and number of times the generator set stops during low wind speed during startup state.

[0096] S202. Based on the characteristic data of the wind turbine generator set, calculate the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model.

[0097] It should be understood that the specific descriptions of each indicator combination are shown in steps S2021 to S2025 below, and will not be repeated here.

[0098] This embodiment provides characteristic data for different types of wind turbine generator sets, improving the comprehensiveness of the data and thus improving the accuracy of the evaluation data for wind turbine generator sets on various indicator combinations.

[0099] In one possible implementation, step S201, calculating the characteristic data of the wind turbine generator based on historical time-series data, includes:

[0100] S2011. Determine the assessment period and extract data segments of the wind turbine generator within the assessment period from historical time-series data; the data segments include wind speed and power.

[0101] In this embodiment, the evaluation period, also known as the evaluation period or statistical period, is generally recommended to be a complete calendar year. However, this embodiment does not specify the exact value of the evaluation period.

[0102] S2012. Based on the data segments, identify the various states of the wind turbine generator set and plot the power curve of the wind turbine generator set; wherein, the states include at least one of the following: standby state, start-up state, power generation state, first shutdown state and second shutdown state, and the power curve is used to reflect the relationship between wind speed and power.

[0103] It should be understood that the standby state refers to the wind turbine generator's blades being deployed to a certain angle to determine if there is sufficient wind energy; the startup state refers to the wind turbine generator's blade angle being deployed from the standby state to 0°, before being connected to the grid; the power generation state refers to the state where the grid connection switch of the inverter in the wind turbine generator is closed; the first shutdown state, also known as the power generation state low-wind shutdown state, specifically refers to the wind turbine generator's shutdown in the power generation state due to the main control system deeming insufficient energy. The second shutdown state, also known as the startup state low-wind shutdown state, specifically refers to the wind turbine generator's shutdown in the startup state due to the main control system deeming insufficient energy.

[0104] The merits and demerits of the original low-wind-speed start-stop control method for wind turbine generators are reflected in the rationality of standby, start-up, power generation, low-wind-speed shutdown, start-up, low-wind-speed shutdown, and power consumption. If the start-stop control method performs poorly, high energy loss is likely to occur in the low-wind-speed range.

[0105] In this embodiment, the power curve (i.e., the actual power curve) of the wind turbine generator set can be drawn according to the description in the national standard "GBT18451.2-2003 Wind Turbine Generator Set Power Characteristic Test", as shown in Figure 3(a). The horizontal axis of the drawn power curve is wind speed and the vertical axis is power. This curve is used to represent the relationship between wind speed and power, and the power curve of the corresponding number of wind turbine generator sets should be drawn for the number of wind turbine generator sets being evaluated.

[0106] The data source is time-series data stored in the monitoring system, and the data sampling frequency requirement is within 0.1 Hz (i.e., the sampling period is more than 10 seconds). Based on the time-series data within 0.1 Hz stored in the monitoring system, this embodiment can effectively identify standby state, start-up state, power generation state, power generation state with low wind shutdown state, and start-up state with low wind shutdown state.

[0107] Specifically, the information involved in the identification method is obtained from time-series data, and the identification method is as follows:

[0108] Standby state = Non-generating state & Blade angle <= Standby state angle.

[0109] Start-up state = non-power generation state & blade angle > standby state angle.

[0110] Power generation status = grid-connected contactor is on.

[0111] Generating status, low wind shutdown status = grid-connected contactor changes from on to off, non-fault, non-external command shutdown until the next standby state.

[0112] Start-up state, low wind, shutdown state = Start-up state, blade angle reduced to 0° & non-fault & non-external command shutdown to the next standby state.

[0113] It should be understood that this embodiment identifies the state of a wind turbine at different times based on the timing data of the turbine.

[0114] S2013. Based on the power curve of the wind turbine generator set, calculate the power loss of the wind turbine generator set under each state, and based on the power loss of the wind turbine generator set under each state, calculate the power consumption of the wind turbine generator set.

[0115] In the embodiments of this application, the power loss of the wind turbine generator in standby state (hereinafter referred to as standby power loss), the power loss of the wind turbine generator in startup state (hereinafter referred to as startup power loss), the power loss of the wind turbine generator in power generation state (hereinafter referred to as power generation power loss), the power loss of the wind turbine generator in power generation state with low wind speed shutdown state (hereinafter referred to as power generation state with low wind speed shutdown power loss), and the power loss of the wind turbine generator in startup state with low wind speed shutdown state (startup state with low wind speed shutdown power loss) can all be accurately calculated by performing the following steps S1 to S4.

[0116] In this embodiment of the application, power consumption refers to the amount of electricity absorbed by the wind turbine when its power is less than 0. It can be accurately calculated by accumulating the active power values ​​measured by the grid in the above five states.

[0117] This embodiment calculates the power consumption in standby, startup, power generation, low-wind shutdown, startup, low-wind shutdown, and all power states where the power is less than 0, using the following formula:

[0118]

[0119] Where N is the power consumption, P n Let H be the power consumption of the nth sampling point where the power is less than 0 in standby, start-up, power generation, low-power shutdown, start-up, low-power shutdown, and power generation states, and let H be the sampling interval. Therefore, in these five states, this embodiment calculates power consumption by accumulating each sampling point where the power is negative.

[0120] S2014. The power loss and power consumption of the wind turbine generator set under various conditions shall be used as characteristic data of the wind turbine generator set.

[0121] This application provides a method for identifying various states of a wind turbine generator set and a specific method for calculating power consumption, which can ensure the accuracy of the characteristic data of the wind turbine generator set.

[0122] In one possible implementation, after identifying the various states of the wind turbine generator set, step S201, calculating the characteristic data of the wind turbine generator set based on historical time-series data, further includes the following steps:

[0123] S2015. Count the number of times the wind turbine generator set switches from the power generation state to the first shutdown state to obtain the first shutdown count.

[0124] S2016. Count the number of times the wind turbine generator set switches from the start state to the second shutdown state to obtain the second shutdown count.

[0125] S2017. The first number of shutdowns and the second number of shutdowns are both used as characteristic data of the wind turbine generator set.

[0126] In this embodiment, there is a first number of shutdowns (i.e., the number of shutdowns during the power generation state with low wind speed) and a second number of shutdowns (i.e., the number of shutdowns during the startup state with low wind speed).

[0127] This embodiment can accurately calculate the first number of shutdowns by accumulating the number of small-wind shutdowns when the generator switches from power generation state to power generation state; similarly, this embodiment can accurately calculate the second number of shutdowns by accumulating the number of small-wind shutdowns when the generator switches from startup state to startup state.

[0128] In the above technical solution, this embodiment provides a specific calculation method for calculating the characteristic data of the wind turbine generator set: the first number of shutdowns and the second number of shutdowns. The entire process is intelligent, requires no human intervention, improves the calculation efficiency of the characteristic data of the wind turbine generator set, and ensures the comprehensiveness of the characteristic data of the wind turbine generator set, providing accurate data for subsequent determination of whether the original start-stop control mode is abnormal.

[0129] In one possible implementation, the preset evaluation index model includes a first index combination, a second index combination, a third index combination, a fourth index combination, and a fifth index combination. Step S202: Based on the characteristic data of the wind turbine generator set, calculate the evaluation data of the wind turbine generator set on each index combination in the preset evaluation index model, including the following steps:

[0130] S2021. The sum of the power loss of the wind turbine generator set in standby mode, power loss in startup mode, power loss in first shutdown mode, and power loss in second shutdown mode shall be used as the first evaluation data of the wind turbine generator set in the first index combination.

[0131] S2022. The sum of the power loss of the wind turbine generator set in standby mode and the power loss in startup mode shall be used as the second evaluation data of the wind turbine generator set in the second index combination.

[0132] S2023. The sum of the power loss of the wind turbine generator under the first shutdown state and the power loss under the second shutdown state shall be used as the third evaluation data of the wind turbine generator under the third index combination.

[0133] S2024. The sum of the first number of shutdowns and the second number of shutdowns shall be used as the fourth evaluation data for the wind turbine generator set in the fourth index combination.

[0134] S2025. The power consumption of wind turbine generator sets shall be used as the fifth evaluation data for wind turbine generator sets in the fifth indicator combination.

[0135] Based on steps S2021 to S2025, it can be seen that in step S30:

[0136] Condition a is: The total loss of standby state + start-up state + power generation state + low wind shutdown state + start-up state + low wind shutdown state > 0.5%.

[0137] Condition b is: the total loss in standby state + startup state > 0.3%.

[0138] Condition c is: The total loss from low wind shutdown during power generation and low wind shutdown during startup is greater than 0.2%.

[0139] Condition d is: the number of times the generator stops during low-speed operation in power generation mode + the number of times the generator stops during low-speed operation in startup mode > 150 times.

[0140] Condition e is: power consumption is less than the total loss of standby state + start-up state + power generation state + low wind shutdown state + start-up state + low wind shutdown state.

[0141] In this embodiment, when the preset evaluation index model contains multiple index combinations, each index combination is analyzed, and the conditions corresponding to each index combination are described in an exemplary manner, which can provide accurate data for subsequently selecting which adjustment method to use.

[0142] In one possible implementation, step S2013, calculating the power loss of the wind turbine generator under various states based on its power curve, includes the following steps:

[0143] S1. Divide the data segment according to the time of each state to obtain the data sub-segment corresponding to each state.

[0144] S2 performs smoothing filtering on the data sub-segments to obtain the wind speed distribution corresponding to each state.

[0145] This wind speed distribution, also known as the wind frequency distribution, is shown in Figure 3(b), where the horizontal axis represents wind speed and the vertical axis represents the distribution frequency. This embodiment calculates the wind speed distribution using data points in the same state from the time-series data.

[0146] S3. Based on the wind speed distribution corresponding to each state, determine the time length corresponding to each state when the wind turbine generator is in each state.

[0147] In other words, wind speed distribution is the cumulative time for each wind speed range. For example, 1 m / s represents 0.75 m / s-1.25 m / s, 1.5 m / s represents 1.25 m / s-1.75 m / s, ..., and 5 m / s represents 4.75 m / s-5.25 m / s.

[0148] In this embodiment, after identifying each state, the interval from the start of power generation to the cutoff point of strong winds is divided into 0.5 m / s intervals, and then the wind speed distribution for each state during the statistical period is statistically analyzed. This wind speed distribution represents the cumulative time length of the unit in each wind speed segment (0.5 m / s interval).

[0149] S4. Based on the time length corresponding to each state of the wind turbine generator set and the power curve of the wind turbine generator set, calculate the power loss of the wind turbine generator set in each state.

[0150] In other words, this embodiment uses time-series data within 0.1 Hz stored in the monitoring system to smooth and filter the wind speed, and then calculates the wind frequency distribution for each of the above states. For each state, the power loss in that state can be calculated by multiplying the time length (obtained from the wind frequency distribution) by the power (obtained from the power curve).

[0151] Therefore, this embodiment uses the following formula to calculate the power loss in each state:

[0152]

[0153] Where, λ n Let ν be the power value in the nth wind speed interval of the power curve. n This represents the time distribution of the nth wind speed interval in the power curve, where n is the interval divided between the wind speed at the start of power generation and the wind speed at which the strong wind cuts out. Therefore, this embodiment, by accurately mapping wind speed intervals, can determine the time distribution and power generation for the same wind speed interval. It should be noted that the value of n for the wind speed interval can be different in different states.

[0154] In the above technical solution, this embodiment provides a specific calculation method for calculating the power loss of a wind turbine generator set under various states. The entire process is intelligent, requires no human intervention, improves the calculation efficiency of the wind turbine generator set's characteristic data, and ensures the comprehensiveness of the wind turbine generator set's characteristic data, providing accurate data for subsequent determination of whether the original start-stop control mode is abnormal.

[0155] Example 3:

[0156] Figure 4 This is a flowchart illustrating another method for adjusting the start-stop control mode of a wind turbine generator set, provided as an embodiment of this application. Figure 4 As shown, the method of this embodiment includes the following steps:

[0157] S100. Determine the evaluation cycle.

[0158] S200. Plot the power curve for each unit. It should be understood that "unit" is short for wind turbine generator set.

[0159] S300 identifies the status involved in low wind speed start-stop control.

[0160] S400: Calculate the power loss and power consumption for each state.

[0161] S500: Calculate the number of small-wind shutdowns during power generation and the number of small-wind shutdowns during startup.

[0162] S600, Calculate start-stop control evaluation indicators. This step refers to calculating the evaluation data for each combination of indicators for the start-stop control mode of the wind turbine generator.

[0163] S700. Develop a correction method based on the indicators. The process of developing the correction method is described in the specific implementation process of step S40 provided in Example 1.

[0164] S800, Evaluation and optimization results.

[0165] The specific processes of steps S100 to S800 are described in Embodiments 1 and 2 above. Their implementation principles and technical effects are similar, and will not be repeated here.

[0166] This embodiment provides a specific application case, showing the values ​​of relevant parameters such as start-stop control losses and number of shutdowns generated by a wind turbine generator operating in the original start-stop control mode over an annual period, as shown in Table 1:

[0167] Table 1. Parameters, values, and percentages in the original start-stop control mode.

[0168]

[0169] As shown in Table 1, the actual power generation equivalent hours generated by the wind turbine in the original start-stop control mode for one year is 1479.3 hours, and the average actual power generation equivalent hours per month is 123.275 hours.

[0170] After running this embodiment, the original start-stop control method was adjusted. On a monthly cycle, the prototype was run with the target start-stop control method, while the control unit was still run with the original start-stop control method corresponding to Table 1, resulting in the data in Table 2:

[0171] Table 2 Comparison results of the two start-stop control methods

[0172]

[0173]

[0174] The comparison results in Table 2 show that the prototype's actual power generation equivalent hours (149.9h) are greater than the control unit's (129.1h); the prototype's self-consumption loss equivalent hours (0.2h) are less than the control unit's (0.7h); the prototype's standby and start-up loss equivalent hours (0.5h) are less than the control unit's (2.9h); and the prototype's small-wind shutdown loss equivalent hours (0.1h) are significantly less than the control unit's (2.4h). The prototype's total start-stop control loss equivalent hours (0.5h) are significantly less than the control unit's (5.2h). Furthermore, the prototype's small-wind shutdown frequency (112.5h) and total small-wind shutdown frequency (117.5h) are significantly less than the control unit's (485.56h) and total small-wind shutdown frequency (488.26h), respectively. Therefore, the embodiments of this application show that the adjusted target start-stop control method is superior to the original start-stop control method, thereby increasing the actual power generation of the wind turbine generator and improving the wind energy utilization rate.

[0175] It should be noted that the number of times in Table 2 are decimals rather than integers because, in order to improve the accuracy of the experiment, this embodiment runs the experiment multiple times and then takes the average of the number of times obtained from the multiple runs.

[0176] This application embodiment uses a combination of multiple indicators to determine whether there are any abnormalities in the original start-stop control method during historical operation. If there are abnormalities, the original start-stop control method is adaptively adjusted according to the adjustment method corresponding to the indicator combination. It has a high degree of intelligence and automatically adjusts the original start-stop control method. In turn, by applying the target start-stop control method, the actual power generation of the wind turbine generator in the subsequent operation process is improved, and the wind energy utilization rate is increased.

[0177] Example 4:

[0178] Figure 5 This is a schematic diagram of a wind turbine generator start-stop control mode adjustment device provided in an embodiment of this application. The device in this embodiment can be in software and / or hardware form. For example... Figure 5 As shown, the wind turbine generator start-stop control mode adjustment device provided in this embodiment includes: an acquisition module 51, a calculation module 52, a determination module 53, and an adjustment module 54. Wherein:

[0179] The acquisition module 51 is used to acquire historical time-series data generated by the wind turbine generator set during its historical operation in the original start-stop control mode.

[0180] The calculation module 52 is used to calculate the evaluation data of the wind turbine generator set on the combination of various indicators in the preset evaluation index model based on historical time series data.

[0181] The determination module 53 is used to determine that there is an anomaly in the original start-stop control method when any evaluation data meets the preset conditions of the corresponding indicator.

[0182] The adjustment module 54 is used to adjust the original start-stop control method according to the adjustment method corresponding to the indicator combination, so as to obtain the target start-stop control method.

[0183] In one possible implementation, the calculation module 52 is further used for:

[0184] Based on historical time-series data, calculate the characteristic data of the wind turbine generator set.

[0185] Based on the characteristic data of the wind turbine generator set, the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model is calculated.

[0186] In one possible implementation, the calculation module 52 is further used for:

[0187] The evaluation period is determined, and data segments of wind turbine generators within the evaluation period are extracted from historical time-series data; these data segments include wind speed and power.

[0188] Based on the data fragments, identify the various states of the wind turbine generator set and plot the power curve of the wind turbine generator set; wherein, the state includes at least one of the following: standby state, start-up state, power generation state, first shutdown state and second shutdown state, and the power curve is used to reflect the relationship between wind speed and power.

[0189] Based on the power curve of the wind turbine generator set, calculate the power loss of the wind turbine generator set under various conditions, and based on the power loss of the wind turbine generator set under various conditions, calculate the power consumption of the wind turbine generator set.

[0190] The power loss and power consumption of the wind turbine generator under various conditions are used as characteristic data of the wind turbine generator.

[0191] In one possible implementation, the calculation module 52 is further used for:

[0192] The number of times the wind turbine generator switched from the power generation state to the first shutdown state is counted to obtain the first shutdown count.

[0193] The number of times the wind turbine generator switched from the start-up state to the second shutdown state was counted to obtain the second shutdown count.

[0194] The first and second number of shutdowns were both used as characteristic data of the wind turbine generator set.

[0195] In one possible implementation, the preset evaluation index model includes a first index combination, a second index combination, a third index combination, a fourth index combination, and a fifth index combination; the calculation module 52 is further used for:

[0196] The sum of the power loss of the wind turbine generator in standby mode, power loss in startup mode, power loss in the first shutdown mode, and power loss in the second shutdown mode is used as the first evaluation data of the wind turbine generator in the first index combination.

[0197] The sum of the power loss of the wind turbine generator in standby mode and the power loss in startup mode is used as the second evaluation data of the wind turbine generator in the second index combination.

[0198] The sum of the power loss of the wind turbine in the first shutdown state and the power loss in the second shutdown state is used as the third evaluation data of the wind turbine in the third index combination.

[0199] The sum of the first and second number of shutdowns is used as the fourth evaluation data for the wind turbine generator set based on the fourth combination of indicators.

[0200] The power consumption of wind turbine generators will be used as the fifth evaluation data for wind turbine generators in the fifth indicator combination.

[0201] In one possible implementation, the calculation module 52 is further used for:

[0202] The data segments are divided according to the time of each state, resulting in data sub-segments corresponding to each state.

[0203] Smoothing filters are applied to the data segments to obtain the wind speed distribution corresponding to each state.

[0204] Based on the wind speed distribution corresponding to each state, determine the corresponding time length when the wind turbine is in each state.

[0205] Based on the time length corresponding to each state of the wind turbine generator set and the power curve of the wind turbine generator set, the power loss of the wind turbine generator set in each state is calculated.

[0206] In one possible implementation, adjustment module 54 is also used for:

[0207] Based on the adjustment method corresponding to the first indicator combination, the start method in the original start-stop control method is adjusted to obtain the target start-stop control method.

[0208] Based on the adjustment method corresponding to the second indicator combination, the starting conditions in the original start-stop control method are adjusted to obtain the target start-stop control method.

[0209] The shutdown conditions in the original start-stop control method are adjusted according to the adjustment method corresponding to the third indicator combination or the fourth indicator combination to obtain the target start-stop control method.

[0210] The wind turbine generator start-stop control mode adjustment device provided in this embodiment can be used to execute the wind turbine generator start-stop control mode adjustment method provided in any of the above method embodiments. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0211] It should be noted that the user information and data involved in this application (including but not limited to data used for analysis, stored data, and displayed data) are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, and processing of the relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0212] In other words, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0213] According to embodiments of this application, this application also provides an electronic device and a readable storage medium.

[0214] Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of this application. The electronic device includes a receiver 60, a transmitter 61, at least one processor 62, and a memory 63. The electronic device composed of the above components can be used to implement the above-described specific embodiments of this application, which will not be described in detail here.

[0215] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the methods described above.

[0216] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the various steps in the methods described above.

[0217] Various embodiments of the systems and technologies described above in this application can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0218] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or electronic device.

[0219] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0220] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0221] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data electronic devices), or computing systems that include middleware components (e.g., application electronic devices), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0222] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0223] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this application should be included within the scope of protection of this application.

Claims

1. A method for adjusting the start-stop control mode of a wind turbine generator set, characterized in that, include: Acquire historical time-series data generated by wind turbine generators during historical operation using the original start-stop control method; Based on the historical time series data, the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation indicator model is calculated; the preset evaluation indicator model includes a first combination of indicators, a second combination of indicators, a third combination of indicators, a fourth combination of indicators, and a fifth combination of indicators. If any of the evaluation data meets the preset conditions of the corresponding indicator, it is determined that the original start-stop control method is abnormal; Based on the adjustment method corresponding to the combination of indicators, the original start-stop control method is adjusted to obtain the target start-stop control method; The step of calculating the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation index model based on the historical time series data includes: Based on the historical time-series data, the characteristic data of the wind turbine generator set are calculated; The sum of the power loss of the wind turbine generator set in standby mode, power loss in startup mode, power loss in the first shutdown mode, and power loss in the second shutdown mode is used as the first evaluation data of the wind turbine generator set on the first index combination; wherein, the first shutdown mode refers to the shutdown of the wind turbine generator set in the power generation mode due to insufficient energy as determined by the main control system; the second shutdown mode refers to the shutdown of the wind turbine generator set in the startup mode due to insufficient energy as determined by the main control system. The sum of the power loss of the wind turbine in the standby state and the power loss in the start-up state is used as the second evaluation data of the wind turbine on the second index combination. The sum of the power loss of the wind turbine generator set in the first shutdown state and the power loss in the second shutdown state is used as the third evaluation data of the wind turbine generator set on the third index combination. The sum of the first number of shutdowns and the second number of shutdowns is used as the fourth evaluation data of the wind turbine generator set on the fourth index combination; the first number of shutdowns is obtained by counting the number of times the wind turbine generator set switches from the power generation state to the first shutdown state; the second number of shutdowns is obtained by counting the number of times the wind turbine generator set switches from the start-up state to the second shutdown state. The power consumption of the wind turbine generator set is used as the fifth evaluation data of the wind turbine generator set on the fifth index combination.

2. The method according to claim 1, characterized in that, The step of calculating the characteristic data of the wind turbine generator set based on the historical time-series data includes: The evaluation period is determined, and data segments of the wind turbine generator within the evaluation period are extracted from the historical time-series data; wherein, the data segments include wind speed and power. Based on the data fragments, the various states of the wind turbine generator set are identified, and the power curve of the wind turbine generator set is plotted; wherein, the states include at least one of the following: standby state, start-up state, power generation state, first shutdown state and second shutdown state, and the power curve is used to reflect the relationship between the wind speed and the power. Based on the power curve of the wind turbine generator set, calculate the power loss of the wind turbine generator set under each state, and based on the power loss of the wind turbine generator set under each state, calculate the power consumption of the wind turbine generator set. The power loss and power consumption of the wind turbine generator set under various conditions are used as characteristic data of the wind turbine generator set.

3. The method according to claim 2, characterized in that, After identifying the various states of the wind turbine generator set, the step of calculating the characteristic data of the wind turbine generator set based on the historical time-series data further includes: Both the first number of shutdowns and the second number of shutdowns are used as characteristic data of the wind turbine generator set.

4. The method according to claim 2, characterized in that, Based on the power curve of the wind turbine generator set, calculate the power loss of the wind turbine generator set under various conditions, including: The data segment is divided according to the time of each state to obtain the data sub-segment corresponding to each state; The data segments are smoothed and filtered to obtain the wind speed distribution corresponding to each state; Based on the wind speed distribution corresponding to each state, determine the time length corresponding to each state of the wind turbine generator set; Based on the time length corresponding to each state of the wind turbine generator set and the power curve of the wind turbine generator set, the power loss of the wind turbine generator set in each state is calculated.

5. The method according to claim 1, characterized in that, Based on the adjustment method corresponding to the aforementioned indicator combination, the original start-stop control method is adjusted to obtain the target start-stop control method, including any one of the following: Based on the adjustment method corresponding to the first indicator combination, the start method in the original start-stop control method is adjusted to obtain the target start-stop control method; Based on the adjustment method corresponding to the second indicator combination, the starting conditions in the original start-stop control method are adjusted to obtain the target start-stop control method; The shutdown conditions in the original start-stop control method are adjusted according to the adjustment method corresponding to the third indicator combination or the fourth indicator combination to obtain the target start-stop control method.

6. A wind turbine generator start-stop control mode adjustment device, characterized in that, include: The acquisition module is used to acquire historical time-series data generated by the wind turbine generator set during its historical operation in the original start-stop control mode. The calculation module is used to calculate the evaluation data of the wind turbine generator set on each combination of indicators in the preset evaluation indicator model based on the historical time series data; the preset evaluation indicator model includes a first combination of indicators, a second combination of indicators, a third combination of indicators, a fourth combination of indicators, and a fifth combination of indicators. The determination module is used to determine that there is an anomaly in the original start-stop control method when any of the evaluation data meets the preset conditions of the corresponding indicator; The adjustment module is used to adjust the original start-stop control method according to the adjustment method corresponding to the combination of indicators, so as to obtain the target start-stop control method; The calculation module is used to calculate the characteristic data of the wind turbine generator set based on the historical time series data. The sum of the power loss of the wind turbine generator set in standby mode, power loss in startup mode, power loss in the first shutdown mode, and power loss in the second shutdown mode is used as the first evaluation data of the wind turbine generator set on the first index combination; wherein, the first shutdown mode refers to the shutdown of the wind turbine generator set in the power generation mode due to insufficient energy as determined by the main control system; the second shutdown mode refers to the shutdown of the wind turbine generator set in the startup mode due to insufficient energy as determined by the main control system. The sum of the power loss of the wind turbine in the standby state and the power loss in the start-up state is used as the second evaluation data of the wind turbine on the second index combination. The sum of the power loss of the wind turbine generator set in the first shutdown state and the power loss in the second shutdown state is used as the third evaluation data of the wind turbine generator set on the third index combination. The sum of the first number of shutdowns and the second number of shutdowns is used as the fourth evaluation data of the wind turbine generator set on the fourth index combination; the first number of shutdowns is obtained by counting the number of times the wind turbine generator set switches from the power generation state to the first shutdown state; the second number of shutdowns is obtained by counting the number of times the wind turbine generator set switches from the start-up state to the second shutdown state. The power consumption of the wind turbine generator set is used as the fifth evaluation data of the wind turbine generator set on the fifth index combination.

7. An electronic device, characterized in that, include: At least one processor and memory; The memory stores computer-executed instructions; The at least one processor executes the computer execution instructions stored in the memory, causing the at least one processor to perform the wind turbine generator start-stop control mode adjustment method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the wind turbine generator start-stop control mode adjustment method as described in any one of claims 1 to 5.

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