A wind turbine full life cycle loss quantification evaluation method

Abstract

The application discloses a kind of wind turbine full life cycle loss quantification evaluation method, it is related to the technical field of data analysis, comprising the following steps, step S1, the loss amount of resource utilization is calculated, step S2, the loss amount of running, aging loss amount and environmental protection loss amount are calculated, step S3, assesses comprehensive loss amount.The application is convenient for horizontal comparison and longitudinal trend analysis between different units, different wind fields by comprehensive evaluation, the severity of resource waste, performance degradation and environmental negative externality of wind turbine in full life cycle can be directly reflected by the numerical size of comprehensive loss amount, improve full life cycle economic benefit and environmental benefit.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and in particular to a method for quantitatively assessing the life-cycle losses of wind turbine generators. Background Technology

[0002] In recent years, the technology for quantitative assessment of wind turbine life cycle losses has developed rapidly. Through the life cycle health management framework, damage mechanisms are linked with proactive decision-making, covering the impact assessment of environmental degradation (lightning erosion, icing, etc.) on power generation losses. SCADA data is used to isolate normal operation data to estimate annual energy losses. By detecting abnormal points and assessing their impact on power generation, it has achieved a transition from qualitative anomaly detection to quantitative loss assessment. The introduction of a temporal convolutional variational depth Gaussian process has enabled high-precision RUL prediction while quantifying the uncertainty of the prediction results.

[0003] Currently, Chinese invention patent CN120597744A discloses a method, device, equipment, and medium for assessing the velocity loss of the entire wake of a wind turbine. This method determines preset parameter information through incoming wind speed and direction, determines the amplitude and shape distribution of a double Gaussian wake model based on the preset parameter information, and assesses the wake velocity loss of the wind turbine based on the amplitude and shape distribution of the double Gaussian wake model. Pressure difference correction compensates for the insufficient assessment accuracy in the near-wake region. However, the related technology does not consider the operating losses of the wind turbine during the usage phase outside the planning stage caused by eddies, aerodynamics, gear transmission, etc., nor does it assess the aging losses caused by changes in main bearing temperature, oil temperature, and vibration. Furthermore, it does not involve the quantification of environmental losses during the decommissioning stage. This is not conducive to a comprehensive assessment of the energy loss, performance degradation, and environmental impact of the wind turbine throughout its entire life cycle, and it is difficult to support cross-stage comprehensive decision-making and optimization. Summary of the Invention

[0004] The technical problem solved by this invention is that related technologies do not consider the operating losses of wind turbines during the use phase outside the planning phase due to eddy currents, aerodynamics, gear transmission, etc., nor do they assess the aging losses caused by changes in main bearing temperature, oil temperature, and vibration. Furthermore, they do not involve the quantification of environmental losses during the decommissioning phase. This makes it difficult to comprehensively assess the energy loss, performance degradation, and environmental impact of wind turbines throughout their entire life cycle, and it is hard to support comprehensive decision-making and optimization across different phases.

[0005] To solve the above technical problems, the present invention provides the following technical solution: a method for quantitative assessment of wind turbine losses throughout the entire life cycle, comprising the following steps: Step S1, for the planning stage, calculate the resource utilization loss based on wind resource data and wind turbine parameters within a first time window; Step S2: For the usage phase, calculate the operating loss based on the wind turbine parameters within the second time window, calculate the aging loss based on the maintenance parameters within the second time window, and calculate the environmental loss based on the recycling parameters for the decommissioning phase.

[0006] Step S3: Assess the overall loss based on the loss in resource utilization, operation, aging, and environmental protection.

[0007] As a preferred embodiment of the method for quantitatively assessing the full life-cycle losses of wind turbines as described in this invention, wind resource data includes wind speed and air density. Wind turbine parameters include blade pitch angle, blade tip speed, blade length, number of blades, wind speed inflow angle, blade root distance, hub radius, gear radius, gear pitch circle diameter, gear angular velocity, gear immersion angle in lubricating oil, gear immersion area in lubricating oil, addendum circle radius, and root circle radius.

[0008] As a preferred embodiment of the wind turbine whole life cycle loss quantitative assessment method described in this invention, step S1 includes the following sub-steps: step S11, within the first time window, calculate the blade sweep area based on the blade length, and calculate the wind power based on the air density, wind speed and blade sweep area. Step S12: Calculate the tip speed ratio based on the tip speed of the wind turbine blades and the wind speed; calculate the wind energy utilization coefficient based on the tip speed ratio and the blade pitch angle. Step S13: Obtain the theoretical power generation capacity based on the wind energy utilization coefficient and wind power. Step S14: Obtain the actual power generation and calculate the resource utilization loss based on the deviation between the theoretical power generation and the actual power generation.

[0009] As a preferred embodiment of the wind turbine whole life cycle loss quantitative assessment method described in this invention, step S14 includes the following sub-steps: step S141, within the first time window, the actual power generation sequence is collected, wherein the collection frequency of the actual power generation is equal to the collection frequency of the wind resource data. Step S142: At any data acquisition time, calculate the difference between the actual power generation and the corresponding theoretical power generation, and set the difference as the deviation of the wind turbine at that data acquisition time. Step S143: Calculate the sum of the deviations of all acquisition times within the first time window, and set this sum as the resource utilization loss.

[0010] As a preferred embodiment of the wind turbine whole life cycle loss quantitative assessment method described in this invention, a setting method is configured for the first time window, including setting a base time and extracting statistical features of wind resource data within the base time according to a statistical method. Determine whether the statistical characteristics within the base duration exhibit periodicity; If there is a periodicity, the base duration is divided according to the periodicity, and any one of the sub-durations after the division is selected as the first duration window; If there is no periodicity, the base duration is extended in reverse until the statistical characteristics corresponding to the base duration after the reverse extension are periodic. At this point, the segmentation operation is repeated to obtain the corresponding first duration window, or the extended base duration is used as the first duration window.

[0011] Statistical characteristics include daily average wind speed, daily average wind speed fluctuations, and adjacent change trends.

[0012] As a preferred embodiment of the wind turbine whole life cycle loss quantitative assessment method described in this invention, the operating loss includes eddy current failure, aerodynamic failure, tooth peripheral power failure and inter-tooth power failure. Obtain the starting evaluation time point. Based on the starting evaluation time point and the first duration window, obtain the starting time point of the second duration window. Based on the experienced service life of the wind turbine and the starting time point, set the second duration window and set the acquisition frequency of the second duration window to be equal to the acquisition frequency of the first duration window. At any given moment, monitor the wind speed inflow angle, gear angular velocity, gear immersion angle in lubricating oil, and gear immersion area in lubricating oil. The eddy failure amount is obtained based on the number of blades, blade length, wind speed inflow angle, and blade root distance; The aerodynamic failure parameters are obtained based on the blade root distance and hub radius; The power failure of the gear circumferential structure is obtained based on the gear radius, gear pitch circle diameter, gear angular velocity, and gear immersion angle in lubricating oil. The inter-tooth power failure amount is obtained based on the area of ​​the gear immersed in lubricating oil, the radius of the addendum circle, and the radius of the root circle.

[0013] As a preferred embodiment of the method for quantitatively assessing the full life cycle loss of a wind turbine as described in this invention, the operation and maintenance parameters include the main bearing temperature, gearbox oil temperature, and main bearing vibration amplitude. The calculation methods for aging losses include calculating the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate. Weight values ​​were set for the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate, respectively. Calculate the product of the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate with their corresponding weight values, respectively. Calculate the sum of each product and set this sum as the aging loss.

[0014] As a preferred embodiment of the method for quantitative assessment of the full life cycle loss of wind turbine units as described in this invention, the recovery parameter is the amount of carbon emissions recovered. Obtain the carbon emissions from production, calculate the sum of the carbon emissions from recycling and production, set this as the carbon increment, calculate the average annual power generation during the usage phase, retrieve the annual emission reduction calculation formula for wind power and photovoltaic projects, and obtain the carbon reduction based on the formula and the average annual power generation during the usage phase. Calculate the difference between carbon increment and carbon reduction, and set it as the environmental loss.

[0015] As a preferred embodiment of the method for quantitatively assessing the life-cycle losses of wind turbines as described in this invention, the ratio of peripheral power failure to eddy current failure is calculated, and the ratio of inter-tooth power failure to aerodynamic failure is calculated. The sum of the ratios of the periodic power failure to the eddy current failure and the ratios of the inter-tooth power failure to the aerodynamic failure is denoted as the power loss. The first and second time windows are converted into hours respectively, and the product of the power loss and the converted second time window is calculated and recorded as the energy loss. The product of the resource utilization loss and the first duration after conversion is recorded as wasted energy consumption. Calculate the ratio of environmental losses to the power grid emission factor, denoted as equivalent electricity, and select the negative of the equivalent electricity. The aging energy consumption is obtained by multiplying the normalized aging loss, empirical coefficient, and theoretical annual power generation.

[0016] As a preferred embodiment of the wind turbine whole life cycle loss quantitative assessment method described in this invention, the method for calculating the comprehensive loss includes calculating the sum of the negative values ​​of lost energy consumption, wasted energy consumption, aging energy consumption, and equivalent electricity, and setting this as the comprehensive loss.

[0017] The beneficial effects of this invention are as follows: By uniformly quantifying wind resource utilization losses during the planning stage, operational and aging losses during the usage stage, and environmental losses during the decommissioning stage, a comprehensive assessment of the entire life cycle losses of wind turbine units can be achieved. By calculating eddy current failure, aerodynamic failure, peripheral power failure, inter-tooth power failure, and aging losses based on temperature and vibration change rates, performance losses can be refined. By correlating production carbon emissions, recycling carbon emissions, and power generation carbon emission reductions, environmental losses can be obtained. Furthermore, by uniformly converting resource utilization losses, operational losses, aging losses, and environmental losses into equivalent electricity, a single comprehensive loss index can be obtained, facilitating horizontal comparisons and vertical trend analysis between different units and different wind farms. The magnitude of the comprehensive loss directly reflects the severity of resource waste, performance degradation, and negative environmental externalities of wind turbine units throughout their entire life cycle, thereby improving the economic and environmental benefits throughout the entire life cycle. Attached Figure Description

[0018] Figure 1 A basic flowchart illustrating a method for quantitatively assessing the life-cycle losses of wind turbine units, as provided in one embodiment of the present invention; Figure 2 This is a schematic diagram of the data processing flow for a method for quantitatively assessing the life-cycle losses of wind turbine units, provided as an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0020] It should be understood that the step numbers used herein are for ease of description only and are not intended to limit the order in which the steps are performed. It should also be understood that the terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention.

[0021] As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0022] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0023] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0024] Example, refer to Figure 1 As an embodiment of the present invention, a method for quantitative assessment of wind turbine life cycle loss is provided, including the following steps: Step S1, for the planning stage, the resource utilization loss is calculated based on wind resource data and wind turbine parameters within a first time window; Step S2: For the usage phase, calculate the operating loss based on the wind turbine parameters within the second time window, calculate the aging loss based on the maintenance parameters within the second time window, and calculate the environmental loss based on the recycling parameters for the decommissioning phase.

[0025] Step S3: Assess the overall loss based on the loss in resource utilization, operation, aging, and environmental protection.

[0026] More preferably, this invention achieves a comprehensive assessment of the entire lifecycle losses of wind turbine units by uniformly quantifying wind resource utilization losses during the planning stage, operational and aging losses during the usage stage, and environmental losses during the decommissioning stage. By calculating eddy current failure, aerodynamic failure, peripheral power failure, inter-tooth power failure, and aging losses based on temperature and vibration change rates, performance losses can be refined. Environmental losses are obtained by correlating production carbon emissions, recycling carbon emissions, and power generation carbon emission reductions. Furthermore, resource utilization losses, operational losses, aging losses, and environmental losses are uniformly converted into equivalent electricity, resulting in a single comprehensive loss index. This facilitates horizontal comparisons and vertical trend analysis between different units and wind farms. The magnitude of the comprehensive loss directly reflects the severity of resource waste, performance degradation, and negative environmental externalities of wind turbine units throughout their lifecycle, thereby improving the economic and environmental benefits throughout the entire lifecycle.

[0027] Wind resource data includes wind speed and air density; Wind turbine parameters include blade pitch angle, blade tip speed, blade length, number of blades, wind speed inflow angle, blade root distance, hub radius, gear radius, gear pitch circle diameter, gear angular velocity, gear immersion angle in lubricating oil, gear immersion area in lubricating oil, addendum circle radius, and root circle radius.

[0028] Step S1 includes the following sub-steps: Step S11, within the first time window, calculate the blade sweeping area based on the blade length, and calculate the wind power based on the air density, wind speed and blade sweeping area. More preferably, the formula for calculating the blade sweep area is: ; More preferably, the expression for calculating wind power is: ; in, The wind power flowing through the wind turbine per unit time. air density, The impeller swept area, For wind speed, For the blade length, It is a constant.

[0029] Step S12: Calculate the tip speed ratio based on the tip speed of the wind turbine blades and the wind speed; calculate the wind energy utilization coefficient based on the tip speed ratio and the blade pitch angle. More preferably, the formula for calculating the tip speed ratio is: ; in, For the tip speed ratio, The wind turbine blade tip velocity is the angular velocity, and the wind speed is the linear velocity. More preferably, the formula for calculating the wind energy utilization coefficient is: ; in, The wind energy utilization coefficient, , , , , and Both are constants. The base of the natural logarithm, It is the propeller pitch angle.

[0030] More preferably, in one embodiment, , , , , and The values ​​are 0.5176, 116, 0.4, 5, 21, and 0.0068, respectively.

[0031] Step S13: Obtain the theoretical power generation capacity based on the wind energy utilization coefficient and wind power. More preferably, the formula for calculating the theoretical power generation is: ; in, This represents the theoretical power generation capacity.

[0032] Step S14: Obtain the actual power generation and calculate the resource utilization loss based on the deviation between the theoretical power generation and the actual power generation.

[0033] Step S14 includes the following sub-steps: Step S141, within the first time window, the actual power generation sequence is collected, wherein the collection frequency of the actual power generation is equal to the collection frequency of the wind resource data. Step S142: At any data acquisition time, calculate the difference between the actual power generation and the corresponding theoretical power generation, and set the difference as the deviation of the wind turbine at that data acquisition time. Step S143: Calculate the sum of the deviations of all acquisition times within the first time window, and set this sum as the resource utilization loss.

[0034] More preferably, the dimension of resource utilization loss is kW·h (kilowatt-hour), which represents the cumulative energy loss of the wind turbine due to the failure to effectively capture wind resources within the first time window.

[0035] More preferably, an ultrasonic anemometer or mechanical anemometer, as well as a temperature, humidity and air pressure sensor, are installed on the top of the wind turbine nacelle or on the wind measurement tower to continuously collect instantaneous wind speed (m / s) and air density (kg / m³) at a sampling frequency of 1Hz to 10Hz. The data is recorded by the SCADA system and stored in the historical database. Since wind speed and air density are the fundamental physical quantities for wind energy calculation, their accuracy directly affects the quantitative results of resource utilization loss. Wind speed (m / s) and air density (kg / m³) are selected to calculate theoretical wind power and tip speed ratio, and then to evaluate wind resource utilization loss.

[0036] More preferably, the blade length, pitch angle, number of blades, blade root distance, and hub radius are directly read from the unit design manual, factory technical documents, or BOM list, and are fixed parameters that do not require real-time data acquisition. The blade length, pitch angle, number of blades, blade root distance, and hub radius are used to calculate the swept area, tip speed ratio, wind energy utilization coefficient, and eddy current / aerodynamic failure, and are key constants for describing the geometric and aerodynamic characteristics of the unit.

[0037] More preferably, the actual power generation is collected and recorded in real time by an energy meter or power transmitter at the unit outlet at the same sampling frequency as the wind speed (e.g., 1Hz). The instantaneous power (kW) is stored in the SCADA system and compared with the theoretical power generation to calculate the power deviation at each moment, thereby quantifying the actual energy loss caused by low wind resource capture efficiency (e.g., yaw error, blade icing, etc.).

[0038] More preferably, the wind speed inflow angle is the angle between the wind direction and the blade rotation plane, measured by an ultrasonic wind profiler or radar anemometer on the top of the nacelle. Gear angular velocity: Measured by a speed sensor (magnetoelectric or photoelectric) mounted on the input or output shaft of the gearbox; Gear immersion angle / area in lubricating oil: The oil level height is measured by an oil level sensor or laser displacement sensor and converted by combining the gearbox geometric model; The addendum circle, dedendum circle radius, pitch circle diameter, and gear radius are read from the gearbox design drawings and are fixed structural parameters.

[0039] Wind speed inflow angle, gear angular velocity, gear immersion lubricating oil angle / area, and tooth tip circle / tooth root circle radius are used to calculate eddy current failure, aerodynamic failure, peripheral power failure, and inter-tooth power failure. These parameters directly reflect the angle of attack relationship between the blades and the incoming flow, as well as the lubrication state and meshing efficiency inside the gearbox, and are the core inputs for quantifying operating losses.

[0040] For the first duration window, there are configuration methods, including setting the basic duration and extracting the statistical features of wind resource data within the basic duration according to the statistical method; Determine whether the statistical characteristics within the base duration exhibit periodicity; If there is a periodicity, the base duration is divided according to the periodicity, and any one of the sub-durations after the division is selected as the first duration window; If there is no periodicity, the base duration is extended in reverse until the statistical characteristics corresponding to the base duration after the reverse extension are periodic. At this point, the segmentation operation is repeated to obtain the corresponding first duration window, or the extended base duration is used as the first duration window.

[0041] Statistical characteristics include daily average wind speed, daily average wind speed fluctuations, and adjacent change trends.

[0042] More preferably, the base duration is set to (In this embodiment, the time zone is 365 days), wind speed data is collected at fixed time intervals (in this embodiment, the time zone is 8 hours) to obtain a time series. , where N is the total number of time intervals (i.e., the total number of hours). The average of the three daily wind speed values ​​is calculated to obtain the daily average wind speed series. ; Calculate the difference between the maximum and minimum wind speeds for each day, and denote it as the daily average wind speed fluctuation series. The daily average wind speed fluctuation series is as follows: ; The initial judgment is performed by calculating the difference in daily average wind speed between two consecutive days, thus obtaining a series of adjacent trend data. , where k is distributed in [1, 2]; The daily average wind speed is grouped by month (30 days), and the average wind speed and the range of wind speed fluctuations for each month are calculated. The average wind speeds of adjacent months in time sequence are compared to see if they are close. If the difference between the maximum values ​​of the average wind speed of any two adjacent months is less than 0.5 (unit: m / s), and the wind speed fluctuation patterns of these two adjacent months are consistent (i.e., the difference between the time points of the maximum wind speed in each month is less than 16 hours, and the difference between the time points of the minimum wind speed in each month is less than 16 hours), then the process jumps to three consecutive months. A review panel will be formed over these three months to conduct a second review. The re-judgment process involves calculating the average wind speed of the re-judgment group. If the variation range of the average wind speed of adjacent re-judgment groups does not exceed 10%, and the fluctuation range of the re-judgment groups is consistent (the difference in the time points of the occurrence of the maximum wind speed in the re-judgment group is less than 48 hours, and the difference in the time points of the occurrence of the minimum wind speed in the re-judgment group is less than 48 hours), then it is determined that the basic duration has periodicity; otherwise, it is determined that the basic duration does not have periodicity.

[0043] If a period exists, the duration corresponding to the re-judgment group is taken as the sub-duration, and this sub-duration is used as the first duration window; If no period exists, extend the base duration forward (e.g., trace back historical data, adding 1 year to the previous period) and check the periodicity of the new sequence again. The initial judgment period after extension is 2 months, and the judgment period after extension is 6 months. Repeat until the maximum number of cycles or extensions is detected (e.g., 3 times); If no cycle exists, then the entire 4-year period is taken as the first duration window.

[0044] If a period exists, calculate the product of the extension number and 3, and record it as the first month number. Set the first month number as the first duration window.

[0045] Operational losses include eddy current failure, aerodynamic failure, peripheral power failure, and inter-tooth power failure. Obtain the starting evaluation time point. Based on the starting evaluation time point and the first duration window, obtain the starting time point of the second duration window. Based on the experienced service life of the wind turbine and the starting time point, set the second duration window and set the acquisition frequency of the second duration window to be equal to the acquisition frequency of the first duration window. At any given moment, monitor the wind speed inflow angle, gear angular velocity, gear immersion angle in lubricating oil, and gear immersion area in lubricating oil. The eddy failure amount is obtained based on the number of blades, blade length, wind speed inflow angle, and blade root distance; More preferably, the expression for calculating the eddy current failure amount is: ; in, This is the eddy current failure quantity. For the number of leaves, The distance between the leaf roots, The angle of wind speed inflow. It is an inverse cosine function.

[0046] More preferably, the eddy current failure quantity is dimensionless, representing the proportion of power loss or efficiency discount factor caused by the eddy current effect.

[0047] The aerodynamic failure parameters are obtained based on the blade root distance and hub radius; More preferably, the formula for calculating the aerodynamic failure amount is: ; in, This represents the aerodynamic failure quantity. Where is the hub radius.

[0048] More preferably, the aerodynamic failure quantity is dimensionless, representing the efficiency discount or loss ratio caused by aerodynamic losses.

[0049] The power failure of the gear circumferential structure is obtained based on the gear radius, gear pitch circle diameter, gear angular velocity, and gear immersion angle in lubricating oil. More preferably, the formula for calculating the periodic power failure is: ; in, This represents the periodic power failure amount. The pitch circle diameter of the gear. For the gear radius, For the gear angular velocity, The angle at which the gear is immersed in the lubricating oil.

[0050] More preferably, the dimension of the periodic power failure is kW, which represents the instantaneous power loss amplitude caused by poor inter-tooth lubrication and abnormal meshing clearance.

[0051] The inter-tooth power failure amount is obtained based on the area of ​​the gear immersed in lubricating oil, the radius of the addendum circle, and the radius of the root circle.

[0052] More preferably, the formula for calculating the inter-tooth power failure is: ; in, This represents the inter-tooth power failure amount. The area of ​​the gear immersed in lubricating oil. The radius of the tooth tip circle, The radius of the tooth root circle is denoted as ...

[0053] More preferably, the dimension of the inter-tooth power failure is kW, which represents the instantaneous power dissipation amplitude caused by the combined effects of fretting wear on the gear meshing surface, oil film rupture, and micro-slippage on the tooth surface.

[0054] Operational parameters include main bearing temperature, gearbox oil temperature, and main bearing vibration amplitude; The calculation methods for aging losses include calculating the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate. Weight values ​​were set for the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate, respectively. Calculate the product of the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate with their corresponding weight values, respectively. Calculate the sum of each product and set this sum as the aging loss.

[0055] More preferably, the calculation method for each rate of change is the same, which is expressed as follows: subtract the data of adjacent monitoring time points in time sequence to obtain the first difference value, calculate the first ratio of the first difference value to the first data of the previous data in this group of adjacent data, traverse the first ratio within the second time window, calculate the average value of the first ratio, and set the average value of the first ratio as the rate of change.

[0056] More preferably, the weight values ​​for the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate are set to 0.4, 0.35, and 0.25, respectively.

[0057] More preferably, the main bearing temperature is collected in real time by a PT100 platinum resistance temperature sensor installed in the outer ring of the bearing or in the oil sump (sampling frequency 1Hz). Gearbox oil temperature: Temperature sensor in the oil sump, sampling frequency 1Hz; Bearing vibration amplitude: A piezoelectric accelerometer mounted on the bearing housing, with a sampling frequency of 10kHz, extracts the effective value (RMS) or peak value; These parameters are used to calculate the rate of temperature change and the rate of vibration change, thereby assessing the amount of aging loss. They are key indicators reflecting the health status of components and can provide early warning of performance degradation trends.

[0058] The recovery parameter is the amount of carbon emissions recovered; Obtain the carbon emissions from production, calculate the sum of the carbon emissions from recycling and production, set this as the carbon increment, calculate the average annual power generation during the usage phase, retrieve the annual emission reduction calculation formula for wind power and photovoltaic projects, and obtain the carbon reduction based on the formula and the average annual power generation during the usage phase. Calculate the difference between carbon increment and carbon reduction, and set it as the environmental loss.

[0059] More preferably, the annual emission reduction calculation formula for wind power and photovoltaic projects is: carbon emission reduction = average annual power generation × emission intensity of pollutants from coal power plants; Among them, the emission intensity of pollutants from coal-fired power plants is the emission intensity of CO2 per unit of electricity generated, and the emission intensity of CO2 is 841.

[0060] More preferably, the average annual power generation during the usage phase is expressed as follows: obtain the power generation at each monitoring moment within the second time window, obtain the monitoring time interval within the second time window, convert the time interval into a value in years, calculate the ratio of the power generation to the value, iterate through the ratios corresponding to the power generation at each monitoring moment, calculate the average value of each ratio, and set the average value as the average annual power generation during the usage phase.

[0061] More preferably, the carbon emissions from production are expressed as the sum of the products of the weight of each component and its corresponding carbon emission factor; In one embodiment, the carbon emission factors of the tower, nacelle, blades, generator, and gearbox are 1.25, 2.80, 3.15, 4.60, and 3, respectively. If the tower weighs 360 tons, then the carbon emission of the tower is 450 tons.

[0062] More preferably, the amount of carbon emissions recovered is expressed as the CO2 equivalent converted from the energy consumption of the recovery process, and its calculation formula is: amount of carbon emissions recovered = Σ (energy consumption of recovery process i × CO2 emission factor of corresponding process i). In one embodiment, the recycling process i includes dismantling, transportation, crushing, sorting, and smelting. The energy consumption of the dismantling process is 120 kWh / ton, the transportation process is 85 kWh / ton, the crushing process is 210 kWh / ton, the sorting process is 165 kWh / ton, and the smelting process is 480 kWh / ton. In one embodiment, the CO2 emission factors corresponding to the dismantling, transportation, crushing, sorting, and smelting processes are 0.85, 0.92, 1.05, 0.78, and 2.36 kgCO2 / kWh, respectively. Therefore, the carbon emission amount recovered is calculated to be 120×0.85+85×0.92+210×1.05+165×0.78+480×2.36=1626.

[0063] More preferably, the unit of measurement for environmental loss is kg, i.e., carbon emission mass.

[0064] More preferably, the energy consumption and CO2 emission factor of the recycling process are obtained from the actual dismantling and recycling report of the retired wind turbine, or by using industry average statistical data. The energy consumption (kWh / ton) of processes such as dismantling, transportation, crushing, sorting, and smelting is obtained through work records or energy consumption monitoring instruments. The emission factor is referenced to the average emission factor of the power grid and used to calculate the carbon emission of recycling. Combined with the carbon emission of production, the carbon increment is obtained. Then, it is compared with the carbon reduction during the use stage to obtain the environmental loss (net CO2 emission). More preferably, the component weight is obtained from the manufacturer's BOM list or procurement contract; the carbon emission factor is obtained from a Life Cycle Assessment (LCA) database (such as Ecoinvent) or an industry standard value (such as GB / T 45855-2025) to calculate the carbon emissions during production and to assess the environmental cost of the wind turbine from raw material mining to delivery.

[0065] Calculate the ratio of periodontal power failure to eddy current failure, and calculate the ratio of inter-tooth power failure to aerodynamic failure. The sum of the ratios of the periodic power failure to the eddy current failure and the ratios of the inter-tooth power failure to the aerodynamic failure is denoted as the power loss. The first and second time windows are converted into hours respectively, and the product of the power loss and the converted second time window is calculated and recorded as the energy loss. The product of the resource utilization loss and the first duration after conversion is recorded as wasted energy consumption. Calculate the ratio of environmental losses to the power grid emission factor, denoted as equivalent electricity, and select the negative of the equivalent electricity. The aging energy consumption is obtained by multiplying the normalized aging loss, empirical coefficient, and theoretical annual power generation.

[0066] More preferably, the empirical coefficient is 0.2.

[0067] The method for calculating the overall loss includes calculating the sum of the energy loss, wasted energy, aging energy, and the negative of the equivalent electricity, and setting this as the overall loss.

[0068] More preferably, the larger the value of the comprehensive loss, the more serious the resource waste, performance degradation and negative environmental externalities of the wind turbine throughout its entire life cycle. This comprehensive loss, as a core evaluation indicator, supports cross-stage horizontal comparison and vertical trend analysis, and qualitatively represents quantitative characteristics.

[0069] More preferably, this invention achieves a comprehensive assessment of the entire lifecycle losses of wind turbine units by uniformly quantifying wind resource utilization losses during the planning stage, operational and aging losses during the usage stage, and environmental losses during the decommissioning stage. By calculating eddy current failure, aerodynamic failure, peripheral power failure, inter-tooth power failure, and aging losses based on temperature and vibration change rates, performance losses can be refined. Environmental losses are obtained by correlating production carbon emissions, recycling carbon emissions, and power generation carbon emission reductions. Furthermore, resource utilization losses, operational losses, aging losses, and environmental losses are uniformly converted into equivalent electricity, resulting in a single comprehensive loss index. This facilitates horizontal comparisons and vertical trend analysis between different units and wind farms. The magnitude of the comprehensive loss directly reflects the severity of resource waste, performance degradation, and negative environmental externalities of wind turbine units throughout their lifecycle, thereby improving the economic and environmental benefits throughout the entire lifecycle.

[0070] More preferably, this embodiment takes an onshore wind turbine with a rated power of 2000kW, a blade length of 45m, and a hub height of 80m as the object, and collects one month's data during its planning stage (site selection verification period), the same month's data during its usage stage (5th year of operation), and the recovery data during its decommissioning stage to conduct a quantitative assessment of the full life cycle loss. Representing the data: Therefore, the swept area is 3181m². 2 With a wind power of 821kW and a blade tip speed of 10rad / s (near the rated operating conditions), the blade tip speed ratio is 60. Due to the excessively large blade tip speed ratio, the actual unit will limit the speed by adjusting the pitch during operation. The tip speed ratio is taken as 8. Substituting it into the wind energy utilization coefficient formula, the wind energy utilization coefficient is 0.4794. The theoretical power generation capacity is 393.5 kW, the actual average power of the month is Pact=370 kW, the monthly duration is 720 h, and the resource utilization loss is 16920 kWh. Within the same month, using the same wind speed of 7.5 m / s, the various failure quantities are calculated. The eddy current failure quantity is 3.43. When the ratio is greater than 1, the inverse cosine is undefined, so the eddy current failure quantity is taken as 0 (meaning that the eddy current loss can be ignored). The aerodynamic failure value is 0.629 kW, the peripheral power failure value is 1.506 kW, and the inter-tooth power failure value is 0.279 kW. The total instantaneous power loss during operation (rated power of 2000 kW) is 1259.8 kW, and the energy loss during operation within one month is 907056 kWh; During the month, the main bearing temperature rose from 50℃ to 52℃, the oil temperature rose from 56℃ to 58℃, and the vibration increased from 0.15 to 0.21 mm / s². Calculate the rate of change (by dividing the difference between the first and last values ​​by 720 hours). The obtained values ​​for the main bearing temperature change rate were 0.00278, the oil temperature change rate was 0.00278, and the vibration change rate was 8.33 × 10⁻⁶. 5 Normalizing each rate of change to the [0,1] interval, the aging loss is 0.002106. This value is small, indicating slow aging. To convert it into energy loss, multiply by the empirical coefficient 0.2 and the annual theoretical power generation of 3500MWh to obtain the aging energy consumption.

[0071] Carbon emissions (Cprod) during production: Tower 400t × 1.25 = 500t, Nacelle 50t × 2.8 = 140t, Blades 45t × 3.15 = 141.75t, Generator 10t × 4.6 = 46t, Gearbox 15t × 3 = 45t, Total 872.75t; Recovered carbon emissions Crecy: 1626 kg of carbon emissions are recovered per ton of unit. The total weight of the unit is about 520 t, so Crecy≈845.5 t (rounded up to 864 t). The carbon increment is 1736.75t, and the average annual power generation (during the usage phase) is taken as the actual power generation of the month, which is 266400kWh, and the annualized result is 3.1968×106kWh. Carbon reduction of 2688 tons, environmental loss 951.25t (negative values ​​indicate net environmental benefits).

[0072] The ratio of the tooth circumferential power failure to the eddy current failure is calculated. Since the denominator is zero, the ratio is invalid. That is, when the eddy current failure is 0, only the relationship between inter-tooth and aerodynamic failure is considered. The power loss is 1.785kW, the energy loss is 1285.2kWh, and the total loss is 924,099kWh, or approximately 924,000 kilowatt-hours of electricity. For example, when considering the application scenario of the comprehensive loss, dividing the comprehensive loss by the unit's annual theoretical power generation of 3,500,000 kWh yields a comprehensive loss rate of 26.4%. This value can be used as a performance evaluation benchmark for the unit throughout its entire life cycle. If it is higher than other units in the same wind farm, it indicates that technical upgrades or early retirement are necessary.

[0073] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0074] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the protection scope of the present invention.

Claims

1. A method for quantitatively assessing the life-cycle losses of wind turbine generators, characterized in that, The steps include: Step S1, for the planning stage, calculate the resource utilization loss based on the wind resource data and wind turbine parameters within the first time window; Step S2: For the usage phase, calculate the operating loss based on the wind turbine parameters in the second time window, calculate the aging loss based on the maintenance parameters in the second time window, and calculate the environmental loss based on the recycling parameters in the decommissioning phase. Step S3: Assess the overall loss based on the loss in resource utilization, operation, aging, and environmental protection.

2. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 1, characterized in that, Wind resource data includes wind speed and air density; Wind turbine parameters include blade pitch angle, blade tip speed, blade length, number of blades, wind speed inflow angle, blade root distance, hub radius, gear radius, gear pitch circle diameter, gear angular velocity, gear immersion angle in lubricating oil, gear immersion area in lubricating oil, addendum circle radius, and root circle radius.

3. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 1, characterized in that, Step S1 includes the following sub-steps: Step S11, within the first time window, calculate the blade sweeping area based on the blade length, and calculate the wind power based on the air density, wind speed and blade sweeping area. Step S12: Calculate the tip speed ratio based on the tip speed of the wind turbine blades and the wind speed; calculate the wind energy utilization coefficient based on the tip speed ratio and the blade pitch angle. Step S13: Obtain the theoretical power generation capacity based on the wind energy utilization coefficient and wind power. Step S14: Obtain the actual power generation and calculate the resource utilization loss based on the deviation between the theoretical power generation and the actual power generation.

4. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 3, characterized in that, Step S14 includes the following sub-steps: Step S141, within the first time window, the actual power generation sequence is collected, wherein the collection frequency of the actual power generation is equal to the collection frequency of the wind resource data. Step S142: At any data acquisition time, calculate the difference between the actual power generation and the corresponding theoretical power generation, and set the difference as the deviation of the wind turbine at that data acquisition time. Step S143: Calculate the sum of the deviations of all acquisition times within the first time window, and set this sum as the resource utilization loss.

5. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 1, characterized in that, For the first duration window, there are configuration methods, including setting the base duration and extracting the statistical features of wind resource data within the base duration according to the statistical method; Determine whether the statistical characteristics within the base duration exhibit periodicity; If there is a periodicity, the base duration is divided according to the periodicity, and any one of the sub-durations after the division is selected as the first duration window; If there is no periodicity, the base duration is extended in reverse until the statistical characteristics corresponding to the base duration after the reverse extension are periodic. At this point, the segmentation operation is repeated to obtain the corresponding first duration window, or the extended base duration is used as the first duration window. Statistical characteristics include daily average wind speed, daily average wind speed fluctuations, and adjacent change trends.

6. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 1, characterized in that, Operational losses include eddy current failure, aerodynamic failure, peripheral power failure, and inter-tooth power failure. Obtain the starting evaluation time point. Based on the starting evaluation time point and the first duration window, obtain the starting time point of the second duration window. Based on the experienced service life of the wind turbine and the starting time point, set the second duration window and set the acquisition frequency of the second duration window to be equal to the acquisition frequency of the first duration window. At any given moment, monitor the wind speed inflow angle, gear angular velocity, gear immersion angle in lubricating oil, and gear immersion area in lubricating oil. The eddy failure amount is obtained based on the number of blades, blade length, wind speed inflow angle, and blade root distance; The aerodynamic failure parameters are obtained based on the blade root distance and hub radius; The power failure of the gear circumferential structure is obtained based on the gear radius, gear pitch circle diameter, gear angular velocity, and gear immersion angle in lubricating oil. The inter-tooth power failure amount is obtained based on the area of ​​the gear immersed in lubricating oil, the radius of the addendum circle, and the radius of the root circle.

7. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 1, characterized in that, Operational parameters include main bearing temperature, gearbox oil temperature, and main bearing vibration amplitude; The calculation methods for aging losses include calculating the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate. Weight values ​​were set for the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate, respectively. Calculate the product of the main bearing temperature change rate, gearbox oil temperature change rate, and main bearing vibration amplitude change rate with their corresponding weight values, respectively. Calculate the sum of each product and set this sum as the aging loss.

8. The method for quantitatively assessing the life-cycle losses of wind turbine generators as described in claim 1, characterized in that; The recovery parameter is the amount of carbon emissions recovered; Obtain the carbon emissions from production, calculate the sum of the carbon emissions from recycling and production, set this as the carbon increment, calculate the average annual power generation during the usage phase, retrieve the annual emission reduction calculation formula for wind power and photovoltaic projects, and obtain the carbon reduction based on the formula and the average annual power generation during the usage phase. Calculate the difference between carbon increment and carbon reduction, and set it as the environmental loss.

9. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 1, characterized in that, Calculate the ratio of periodontal power failure to eddy current failure, and calculate the ratio of inter-tooth power failure to aerodynamic failure. The sum of the ratios of the periodic power failure to the eddy current failure and the ratios of the inter-tooth power failure to the aerodynamic failure is denoted as the power loss. The first and second time windows are converted into hours respectively, and the product of the power loss and the converted second time window is calculated and recorded as the energy loss. The product of the resource utilization loss and the first duration after conversion is recorded as wasted energy consumption. Calculate the ratio of environmental losses to the power grid emission factor, denoted as equivalent electricity, and select the negative of the equivalent electricity. The aging energy consumption is obtained by multiplying the normalized aging loss, empirical coefficient, and theoretical annual power generation.

10. The method for quantitatively assessing the life-cycle losses of wind turbine units as described in claim 9, characterized in that, The method for calculating the overall loss includes calculating the sum of the energy loss, wasted energy, aging energy, and the negative of the equivalent electricity, and setting this as the overall loss.

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