A method and system for constructing a power characteristic curve of a wind turbine

Abstract

The present invention provides a method and system for constructing a power characteristic curve of a wind turbine, including: constructing an initial wind speed-power characteristic curve within a current period based on the current operating power and the wind speed corresponding to the operating power; constructing a power composite influence factor matrix based on historical operating data and current influencing factors; revising the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the power characteristic curve of the wind turbine within a current period; the influencing factors include: air density, turbulence intensity, yaw error. When constructing the power characteristic curve of the wind turbine, the present invention not only considers the influencing factor of wind speed, but also further considers the influencing factors such as air density, turbulence intensity, and yaw error conditions, so that the obtained power characteristic curve of the wind turbine can more accurately reflect the actual operating conditions of the wind turbine, providing strong support for exploring the optimization solution of the operating power characteristic of the wind turbine.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind power generation, and particularly relates to a method and a system for constructing a power characteristic curve of a wind turbine generator set. Background Art

[0002] As a renewable clean energy source, wind energy has received increasing attention, and the wind power industry has entered a period of rapid development, with the installed capacity of wind power increasing year by year. With the increase in operation time, the structural components of wind turbine generator sets age, and their operating characteristics change significantly, directly affecting the output characteristics of wind turbine generator sets, that is, the power generation output decreases significantly. In order to analyze the power characteristics of in-service wind turbine generator sets, it is necessary to analyze the accumulated power operation data of wind turbine generator sets, analyze the differences between their actual operating power characteristics and design output characteristics, find the sources of differences, and explore optimization solutions for the operating power characteristics of wind turbine generator sets.

[0003] The power characteristic is one of the most critical indicators of a wind turbine generator set, and it is directly related to the annual power generation of the wind turbine generator set. For the evaluation of the power curve of a wind turbine generator set, the traditional technical means is to use the interval analysis method to obtain the interval wind speed-power curve of the unit, and use the interval average method to calculate the power coefficient corresponding to each interval of the wind turbine generator set, that is, the wind energy conversion rate. This traditional power curve evaluation method uses the average algorithm from a statistical perspective, resulting in the averaging of a large amount of potential information in the original data, and the true operating power curve of the unit cannot be obtained. Therefore, how to construct the power characteristic curve of a wind turbine generator set to accurately reflect the true power characteristics of the wind turbine generator set is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0004] To overcome the deficiencies of the above-mentioned prior art, the present invention provides a method for constructing a power characteristic curve of a wind turbine generator set, including:

[0005] Obtaining the operation data and historical operation data of the wind turbine generator set within a current period of time; the operation data includes: operating power, the wind speed corresponding to the operating power, and preset influencing factors;

[0006] Based on the current operating power and the wind speed corresponding to the operating power, constructing an initial wind speed-power characteristic curve within a current period of time;

[0007] Based on the historical operation data and current influencing factors, constructing a power composite influence factor matrix;

[0008] Revising the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the power characteristic curve of the wind turbine generator set within a current period of time;

[0009] The influencing factors include: air density, turbulence intensity, and yaw error; the power composite influence factor matrix is constructed by the influence factor values corresponding to different influencing factor conditions; the influence factor value is the correlation coefficient between the wind speed-power characteristic curve and the initial wind speed-power characteristic curve under different influencing factor conditions.

[0010] Preferably, based on the current operating power and the wind speed corresponding to the operating power, an initial wind speed-power characteristic curve for a current period is constructed, including:

[0011] Dividing the operating power and the wind speed data corresponding to the operating power within the current period based on a preset wind speed interval;

[0012] Based on the operating power and the wind speed corresponding to the operating power in each interval, calculating the average wind speed and the average output power in each interval respectively;

[0013] Based on the average wind speed and the average output power in each interval, constructing an initial wind speed-power characteristic curve for the current period.

[0014] Preferably, based on historical operation data and current influencing factors, a power composite influence factor matrix is constructed, including:

[0015] Based on historical operation data, successively calculating the influence factor values corresponding to different influencing factor conditions;

[0016] Based on the influence factor values corresponding to different influencing factor conditions, determining the influence factor values respectively corresponding to the current influencing factor conditions;

[0017] Based on the influence factor values respectively corresponding to the current influencing factor conditions, constructing a power composite influence factor matrix.

[0018] Preferably, based on historical operation data, successively calculating the influence factor values corresponding to different influencing factor conditions, including:

[0019] Based on historical operating power and the wind speed corresponding to the operating power, constructing a historical initial wind speed-power characteristic curve;

[0020] Based on historical operating power, wind speed, air density, and the historical initial wind speed-power characteristic curve, calculating the correlation coefficient between the wind speed-power characteristic curve under different air density conditions and the historical initial wind speed-power characteristic curve, as the influence factor value corresponding to different air density conditions;

[0021] Based on historical operating power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, calculating the correlation coefficient between the wind speed-power characteristic curve under different turbulence intensity conditions and the historical initial wind speed-power characteristic curve, as the influence factor value corresponding to different turbulence intensity conditions;

[0022] Based on the historical operating power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, calculate the correlation coefficient between the wind speed-power characteristic curve under different yaw error conditions and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different yaw error conditions.

[0023] Preferably, based on the historical operating power, wind speed, air density, and the historical initial wind speed-power characteristic curve, calculate the correlation coefficient between the wind speed-power characteristic curve under different air density conditions and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different air density conditions, including:

[0024] Divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset air density conditions;

[0025] Based on the historical operating power and the wind speed corresponding to the operating power in each air density condition interval, construct the wind speed-power characteristic curve for each air density condition interval;

[0026] Calculate the correlation coefficient between the wind speed-power characteristic curve for each air density condition interval and the historical initial wind speed-power characteristic curve in sequence, and use it as the influence factor value corresponding to different air density conditions.

[0027] Preferably, based on the historical operating power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, calculate the correlation coefficient between the wind speed-power characteristic curve under different turbulence intensity conditions and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different turbulence intensity conditions, including:

[0028] Divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset turbulence intensity conditions;

[0029] Based on the historical operating power and the wind speed corresponding to the operating power in each turbulence intensity condition interval, construct the wind speed-power characteristic curve for each turbulence intensity condition interval;

[0030] Calculate the correlation coefficient between the wind speed-power characteristic curve for each turbulence intensity condition interval and the historical initial wind speed-power characteristic curve in sequence, and use it as the influence factor value corresponding to different turbulence intensity conditions.

[0031] Preferably, based on the historical operating power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, calculate the correlation coefficient between the wind speed-power characteristic curve under different yaw error conditions and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different yaw error conditions, including:

[0032] Divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on a preset yaw error condition;

[0033] Based on the historical operating power and the wind speed corresponding to the operating power in each yaw error condition interval, construct the wind speed-power characteristic curve for each yaw error condition interval;

[0034] Calculate the correlation coefficient between the wind speed-power characteristic curve of the yaw error condition interval and the historical initial wind speed-power characteristic curve in sequence, and use it as the influence factor value corresponding to different yaw error conditions.

[0035] Preferably, the expression of the wind turbine power characteristic curve within a current period of time is as follows:

[0036]

[0037] In the formula: P is the operating power of the wind turbine, C p is the power coefficient, ρ0 is the standard air density, A is the swept area of the wind turbine rotor, v is the average wind speed, α ρ is the influence factor value corresponding to the current air density condition, α TI is the influence factor value corresponding to the current turbulence intensity condition, α yaw is the influence factor value corresponding to the current yaw error condition, ρ represents the air density, TI represents the turbulence intensity, and yaw represents the yaw error.

[0038] Based on the same concept, the present invention also provides a system for constructing a wind turbine power characteristic curve, including:

[0039] A data acquisition module for acquiring the operating data and historical operating data of the wind turbine within a current period of time; the operating data includes: operating power, the wind speed corresponding to the operating power, and preset influencing factors;

[0040] An initial power curve construction module for constructing an initial wind speed-power characteristic curve within a current period of time based on the current operating power and the wind speed corresponding to the operating power;

[0041] A composite influence factor matrix construction module for constructing a power composite influence factor matrix based on the historical operating data and the current influencing factors;

[0042] A composite power curve construction module for revising the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the wind turbine power characteristic curve within a current period of time;

[0043] The influencing factors include: air density, turbulence intensity, and yaw error; the power composite influence factor matrix is constructed from the influence factor values corresponding to different influencing factor conditions; the influence factor value is the correlation coefficient between the wind speed-power characteristic curve and the initial wind speed-power characteristic curve under different influencing factor conditions.

[0044] Preferably, the initial power curve construction module includes:

[0045] The wind speed data division sub-module is used to divide the operating power and the wind speed data corresponding to the operating power within a current period of time based on a preset wind speed interval.

[0046] The interval data calculation sub-module is used to calculate the average wind speed and the average output power of each interval respectively based on the operating power of each interval and the wind speed corresponding to the operating power.

[0047] The initial power curve fitting sub-module is used to construct the initial wind speed-power characteristic curve within a current period of time based on the average wind speed and the average output power of each interval.

[0048] Preferably, the composite influence factor matrix construction module includes:

[0049] The historical influence factor value calculation sub-module is used to calculate the influence factor values corresponding to different influencing factor conditions in sequence based on historical operation data.

[0050] The current influence factor value determination sub-module is used to determine the influence factor values corresponding to the current influencing factor conditions respectively based on the influence factor values corresponding to different influencing factor conditions.

[0051] The matrix construction sub-module is used to construct the power composite influence factor matrix based on the influence factor values corresponding to the current influencing factor conditions respectively.

[0052] Preferably, the historical influence factor value calculation sub-module includes:

[0053] The historical initial power curve construction unit is used to construct the historical initial wind speed-power characteristic curve based on the historical operating power and the wind speed corresponding to the operating power.

[0054] The different air density influence factor value calculation unit is used to calculate the correlation coefficient between the wind speed-power characteristic curve and the historical initial wind speed-power characteristic curve under different air density conditions based on the historical operating power, wind speed, air density, and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different air density conditions.

[0055] A calculation unit for influence factor values of different turbulence intensities, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve under different turbulence intensity conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, and take it as the influence factor value corresponding to different turbulence intensity conditions;

[0056] A calculation unit for influence factor values of different yaw errors, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve under different yaw error conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, and take it as the influence factor value corresponding to different yaw error conditions.

[0057] Preferably, the calculation unit for influence factor values of different air densities includes:

[0058] An air density data partitioning subunit, which is used to partition the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset air density conditions;

[0059] An air density power curve construction subunit, which is used to construct the wind speed-power characteristic curves for each air density condition interval based on the historical operating power and the wind speed corresponding to the operating power in each air density condition interval;

[0060] An air density influence factor value calculation subunit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve of each air density condition interval and the historical initial wind speed-power characteristic curve in sequence, and take it as the influence factor value corresponding to different air density conditions.

[0061] Preferably, the calculation unit for influence factor values of different turbulence intensities includes:

[0062] A turbulence intensity data partitioning subunit, which is used to partition the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset turbulence intensity conditions;

[0063] A turbulence intensity power curve construction subunit, which is used to construct the wind speed-power characteristic curves for each turbulence intensity condition interval based on the historical operating power and the wind speed corresponding to the operating power in each turbulence intensity condition interval;

[0064] A turbulence intensity influence factor value calculation subunit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve of each turbulence intensity condition interval and the historical initial wind speed-power characteristic curve in sequence, and take it as the influence factor value corresponding to different turbulence intensity conditions.

[0065] Preferably, the calculation unit for influence factor values of different yaw errors includes:

[0066] A yaw error data division sub-unit, which is used to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on a preset yaw error condition;

[0067] A yaw error power curve construction sub-unit, which is used to construct a wind speed-power characteristic curve for each yaw error condition interval based on the historical operating power in each yaw error condition interval and the wind speed corresponding to the operating power;

[0068] A yaw error influence factor value calculation sub-unit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve of the yaw error condition interval and the historical initial wind speed-power characteristic curve in sequence, as the influence factor value corresponding to different yaw error conditions.

[0069] Compared with the closest prior art, the beneficial effects of the present invention are as follows:

[0070] The present invention provides a method and a system for constructing a wind turbine power characteristic curve, including: constructing an initial wind speed-power characteristic curve within a current period based on the current operating power and the wind speed corresponding to the operating power; constructing a power composite influence factor matrix based on historical operating data and current influencing factors; revising the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the wind turbine power characteristic curve within a current period; the influencing factors include: air density, turbulence intensity, yaw error. When constructing the wind turbine power characteristic curve, the present invention not only considers the influencing factor of wind speed, but also further considers the influencing factors of air density, turbulence intensity, and yaw error conditions, so that the obtained wind turbine power characteristic curve can more accurately reflect the actual operating conditions of the wind turbine, and provides strong data support for exploring the optimization solution of the wind turbine operating power characteristic. Description of the Drawings

[0071] Figure 1 It is a schematic diagram of a method for constructing a wind turbine power characteristic curve provided by the present invention;

[0072] Figure 2 It is a schematic diagram of a system for constructing a wind turbine power characteristic curve provided by the present invention;

[0073] Figure 3 It is an initial wind speed-power characteristic curve diagram provided in an embodiment of the present invention;

[0074] Figure 4 It is a flow chart for constructing a wind turbine power characteristic curve provided in an embodiment of the present invention;

[0075] Figure 5 It is a wind speed-power characteristic curve diagram under different air density conditions provided in an embodiment of the present invention;

[0076] Figure 6 It is the wind speed-power characteristic curve diagram under different turbulence intensity conditions provided in the embodiments of the present invention;

[0077] Figure 7 It is the wind speed-power characteristic curve diagram under different yaw error conditions provided in the embodiments of the present invention. Specific Embodiments

[0078] The following further elaborates on the specific embodiments of the present invention in conjunction with the accompanying drawings.

[0079] Embodiment 1:

[0080] The embodiments of the present invention provide a method for constructing a power characteristic curve of a wind turbine as Figure 1 shown, including:

[0081] S1 Obtain the operation data and historical operation data of the wind turbine within a current period of time; the operation data includes: operation power, the wind speed corresponding to the operation power, and preset influencing factors;

[0082] S2 Based on the current operation power and the wind speed corresponding to the operation power, construct an initial wind speed-power characteristic curve within a current period of time;

[0083] S3 Based on the historical operation data and the current influencing factors, construct a power composite influence factor matrix;

[0084] S4 Based on the power composite influence factor matrix, revise the initial wind speed-power characteristic curve to obtain the power characteristic curve of the wind turbine within a current period of time;

[0085] The influencing factors include: air density, turbulence intensity, yaw error; the power composite influence factor matrix is constructed by the influence factor values corresponding to different influencing factor conditions; the influence factor value is the correlation coefficient between the wind speed-power characteristic curve under different influencing factor conditions and the initial wind speed-power characteristic curve.

[0086] The steps of S2 for constructing an initial wind speed-power characteristic curve within a current period of time based on the current operation power and the wind speed corresponding to the operation power are as follows:

[0087] S2-1 Obtain the current operation power and the wind speed data corresponding to the operation power, and use the interval average method to divide the data at an interval of 0.5 m / s for the wind speed condition;

[0088] S2-2 Based on the operation power and the wind speed corresponding to the operation power in each interval, calculate the average wind speed and the average output power of each wind speed interval according to the following formula:

[0089]

[0090]

[0091] Wherein, V i is the average wind speed of the i-th interval, V n,i,j is the wind speed of the j-th array in the i-th interval, P i is the average output power of the i-th interval, P n,i,j is the average output power of the j-th array in the i-th interval, N i is the number of 10-min arrays in the i-th interval;

[0092] S2-3 Based on the average wind speed and average output power of each interval, an initial wind speed-power characteristic curve is fitted and generated. The initial wind speed-power characteristic curve is as Figure 3 shown.

[0093] Furthermore, the power coefficient corresponding to the initial wind speed-power characteristic curve is calculated as follows:

[0094]

[0095] Wherein, C P,i is the power coefficient of the i-th interval, V i is the average wind speed of the i-th interval, P i is the average output power of the i-th interval, A is the swept area of the wind turbine, and ρ0 is the standard air density.

[0096] Furthermore, based on the power coefficient corresponding to the initial wind speed-power characteristic curve, the mathematical expression of the initial wind speed-power characteristic curve can be determined, and the expression is as follows:

[0097]

[0098] Wherein, P is the average output power, C P is the power coefficient, ρ0 is the standard air density, A is the swept area of the wind turbine, and v is the average wind speed.

[0099] After the initial wind speed-power characteristic curve is generated, it is necessary to consider the current air density, turbulence intensity, and yaw error conditions to revise the initial wind speed-power characteristic curve and generate a composite power curve of the wind turbine characteristics. The flow block diagram for constructing the wind turbine power characteristic curve is as Figure 4As shown in the figure, it mainly includes: obtaining the operating power data of the wind turbine; classifying the data according to characteristics; constructing an air density characteristic library, a turbulence intensity characteristic library, and a yaw error characteristic library; calculating the air density characteristic power curve library, the turbulence intensity characteristic power curve library, and the yaw error characteristic power curve library; calculating the characteristic composite power curve of the wind turbine. The steps for constructing the characteristic composite power curve of the wind turbine specifically include:

[0100] S3 Based on historical operation data and current air density, turbulence intensity, and yaw error, construct a power composite influence factor matrix, including:

[0101] S3-1 Based on historical operating power and the wind speed corresponding to the operating power, construct a historical initial wind speed-power characteristic curve.

[0102] Considering that air density, turbulence intensity, and yaw error have a great impact on the output characteristics of the wind turbine, this patent first classifies the historical operating power data of the wind turbine according to different characteristic values such as air density, turbulence intensity, and yaw error, and constructs a characteristic database. Specifically:

[0103] S3-2-1 Construction of the air density characteristic database

[0104] Classify the historical operating power data of the wind turbine according to the different magnitudes of air density. In the actual air density range, use 0.1 kg / m3 as the data division interval to form a power database under different air density conditions. For example, the range of 0.75 - 0.85 kg / m3 is classified into the database under the condition of air density 0.8 kg / m3;

[0105] S3-2-2 Construction of the turbulence intensity characteristic database

[0106] Classify the operating power data of the wind turbine according to the different magnitudes of turbulence intensity. In the actual turbulence intensity range, use 2% as the data division interval to form a power database under different turbulence intensity conditions. For example, the range of 11% - 13% is classified into the characteristic database under the condition of turbulence intensity 12%;

[0107] S3-2-3 Construction of the yaw error characteristic database

[0108] Classify the operating power data of the wind turbine according to the different magnitudes of yaw error. In the actual yaw error range, use 8° as the data division interval to form a power database under different yaw error conditions.

[0109] S3-3 Generate the air density characteristic power curve library, turbulence intensity characteristic power curve library, and yaw error characteristic power curve library respectively using the interval averaging method based on the air density, turbulence intensity, and yaw error characteristic database, and combine with the historical initial wind speed-power characteristic curve to calculate the corresponding influence factor values under different air density, turbulence intensity, and yaw error conditions. Specifically:

[0110] S3-3-1 Construction of the air density characteristic power curve library and calculation of the corresponding influence factor values

[0111] Based on the historical operating power and the wind speed corresponding to the operating power in each air density condition interval, construct the wind speed-power characteristic curve for each air density condition interval. Taking a 2MW wind turbine as an example, Figure 5 The operating power curves of the wind turbine under different air density conditions are given;

[0112] Calculate the correlation coefficients between the wind speed-power characteristic curves of each air density condition interval and the historical initial wind speed-power characteristic curve in turn as the influence factor values corresponding to different air density conditions.

[0113] Furthermore, based on the influence factor values corresponding to different air density conditions, construct the influence factor value matrix corresponding to the air density conditions. Therefore, the power curve of the wind turbine considering the air density conditions can be described by the following mathematical expression:

[0114]

[0115] In the formula, P is the average output power, C P is the power coefficient, ρ0 is the standard air density, A is the wind turbine swept area, v is the average wind speed, C ρ is the influence factor value matrix corresponding to the air density conditions.

[0116] S3-3-2 Construction of the turbulence intensity characteristic power curve library and calculation of the corresponding influence factor values

[0117] Based on the historical operating power and the wind speed corresponding to the operating power in each turbulence intensity condition interval, construct the wind speed-power characteristic curve for each turbulence intensity condition interval. Taking a certain 2MW wind turbine as an example, Figure 6 The operating power curves of the wind turbine under different turbulence intensity conditions are given;

[0118] Calculate the correlation coefficients between the wind speed-power characteristic curves of each turbulence intensity condition interval and the historical initial wind speed-power characteristic curve in turn as the influence factor values corresponding to different conditions.

[0119] Further, based on the influence factor values corresponding to different turbulence intensity conditions, an influence factor value matrix corresponding to the turbulence intensity conditions is constructed. Therefore, the power curve of the wind turbine constructed considering the turbulence intensity conditions can be described by the following mathematical expression:

[0120]

[0121] In the formula, P is the average output power, C P is the power coefficient, ρ0 is the standard air density, A is the swept area of the wind turbine rotor, v is the average wind speed, C TI is the influence factor value matrix corresponding to the turbulence intensity conditions.

[0122] Construction of the power curve library of the yaw error characteristic S3-3-3 and calculation of the corresponding influence factor values

[0123] Based on the historical operating power and the wind speed corresponding to the operating power in each yaw error condition interval, a wind speed-power characteristic curve for each yaw error condition interval is constructed. Taking a 2MW wind turbine as an example, Figure 7 the operating power curves of the wind turbine under different yaw error conditions are given;

[0124] The correlation coefficients between the wind speed-power characteristic curves of each yaw error condition interval and the historical initial wind speed-power characteristic curve are calculated in sequence as the influence factor values corresponding to different yaw error conditions.

[0125] Further, based on the influence factor values corresponding to different yaw error conditions, an influence factor value matrix corresponding to the yaw error conditions is constructed. Therefore, the power curve of the wind turbine constructed considering the yaw error conditions can be described by the following mathematical expression:

[0126]

[0127] In the formula, P is the average output power, C P is the power coefficient, ρ0 is the standard air density, A is the swept area of the wind turbine rotor, v is the average wind speed, C yaw is the influence factor value matrix corresponding to the yaw error conditions.

[0128] S3-4 Based on the influence factor values corresponding to the different air density, turbulence intensity and yaw error conditions, determine the influence factor values corresponding to the current air density, turbulence intensity and yaw error conditions respectively.

[0129] S3-5 Based on the influence factor values corresponding to the current air density, turbulence intensity and yaw error conditions respectively, construct a power composite influence factor matrix. Specifically:

[0130] Initialize and generate a 3*3 matrix;

[0131] Fill the first row of the matrix with the influence factor value corresponding to the current air density, 0, and 0 in sequence;

[0132] Fill the second row of the matrix with 0, the influence factor value corresponding to the current turbulence intensity, and 0 in sequence;

[0133] Fill the third row of the matrix with 0, 0, and the influence factor value corresponding to the current yaw error in sequence;

[0134] The filling order of the matrix is not limited to the above scheme, and different order transformations can also be performed.

[0135] S4 Revise the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the current wind turbine power characteristic curve. The expression of the power thermal curve is as follows:

[0136]

[0137] In the formula: P is the operating power of the wind turbine, C p is the power coefficient, ρ0 is the standard air density, A is the swept area of the wind turbine rotor, v is the average wind speed, α ρ is the influence factor value corresponding to the current air density condition, α TI is the influence factor value corresponding to the current turbulence intensity condition, α yaw is the influence factor value corresponding to the current yaw error condition, ρ represents the air density, TI represents the turbulence intensity, and yaw represents the yaw error.

[0138] Example 2:

[0139] This embodiment of the present invention discloses a system for constructing a wind turbine power characteristic curve, as Figure 2 shown, including:

[0140] A data acquisition module for obtaining the operating data and historical operating data of the wind turbine within a current period of time; the operating data includes: operating power, the wind speed corresponding to the operating power, and preset influencing factors;

[0141] An initial power curve construction module for constructing an initial wind speed-power characteristic curve within a current period of time based on the current operating power and the wind speed corresponding to the operating power;

[0142] A composite influence factor matrix construction module for constructing a power composite influence factor matrix based on the historical operating data and the current influencing factors;

[0143] A composite power curve construction module for revising the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the wind turbine power characteristic curve within a current period of time;

[0144] The influencing factors include: air density, turbulence intensity, and yaw error; the power composite influence factor matrix is constructed by the influence factor values corresponding to different influencing factor conditions; the influence factor value is the correlation coefficient between the wind speed-power characteristic curve and the initial wind speed-power characteristic curve under different influencing factor conditions.

[0145] Preferably, the initial power curve construction module includes:

[0146] The wind speed data division sub-module is used to divide the operating power and the wind speed data corresponding to the operating power within a current period of time based on a preset wind speed interval.

[0147] The interval data calculation sub-module is used to calculate the average wind speed and the average output power of each interval respectively based on the operating power of each interval and the wind speed corresponding to the operating power.

[0148] The initial power curve fitting sub-module is used to construct the initial wind speed-power characteristic curve within a current period of time based on the average wind speed and the average output power of each interval.

[0149] Preferably, the composite influence factor matrix construction module includes:

[0150] The historical influence factor value calculation sub-module is used to calculate the influence factor values corresponding to different influencing factor conditions in sequence based on historical operation data.

[0151] The current influence factor value determination sub-module is used to determine the influence factor values corresponding to the current influencing factor conditions respectively based on the influence factor values corresponding to different influencing factor conditions.

[0152] The matrix construction sub-module is used to construct the power composite influence factor matrix based on the influence factor values corresponding to the current influencing factor conditions respectively.

[0153] Preferably, the historical influence factor value calculation sub-module includes:

[0154] The historical initial power curve construction unit is used to construct the historical initial wind speed-power characteristic curve based on the historical operating power and the wind speed corresponding to the operating power.

[0155] The different air density influence factor value calculation unit is used to calculate the correlation coefficient between the wind speed-power characteristic curve and the historical initial wind speed-power characteristic curve under different air density conditions based on the historical operating power, wind speed, air density, and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different air density conditions.

[0156] A calculation unit for influence factor values of different turbulence intensities, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve under different turbulence intensity conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, and take it as the influence factor value corresponding to different turbulence intensity conditions;

[0157] A calculation unit for influence factor values of different yaw errors, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve under different yaw error conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, and take it as the influence factor value corresponding to different yaw error conditions.

[0158] Preferably, the calculation unit for influence factor values of different air densities includes:

[0159] An air density data division sub-unit, which is used to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset air density conditions;

[0160] An air density power curve construction sub-unit, which is used to construct the wind speed-power characteristic curves for each air density condition interval based on the historical operating power and the wind speed corresponding to the operating power in each air density condition interval;

[0161] An air density influence factor value calculation sub-unit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve of each air density condition interval and the historical initial wind speed-power characteristic curve in sequence, and take it as the influence factor value corresponding to different air density conditions.

[0162] Preferably, the calculation unit for influence factor values of different turbulence intensities includes:

[0163] A turbulence intensity data division sub-unit, which is used to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset turbulence intensity conditions;

[0164] A turbulence intensity power curve construction sub-unit, which is used to construct the wind speed-power characteristic curves for each turbulence intensity condition interval based on the historical operating power and the wind speed corresponding to the operating power in each turbulence intensity condition interval;

[0165] A turbulence intensity influence factor value calculation sub-unit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve of each turbulence intensity condition interval and the historical initial wind speed-power characteristic curve in sequence, and take it as the influence factor value corresponding to different turbulence intensity conditions.

[0166] Preferably, the calculation unit for influence factor values of different yaw errors includes:

[0167] A yaw error data division sub - unit, which is used to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on a preset yaw error condition;

[0168] A yaw error power curve construction sub - unit, which is used to construct the wind speed - power characteristic curves for each yaw error condition interval based on the historical operating power and the wind speed corresponding to the operating power in each yaw error condition interval;

[0169] A yaw error influence factor value calculation sub - unit, which is used to calculate the correlation coefficients between the wind speed - power characteristic curves of the yaw error condition intervals and the historical initial wind speed - power characteristic curves in sequence, and use them as the influence factor values corresponding to different yaw error conditions.

[0170] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer - usable storage media (including but not limited to disk storage, CD - ROM, optical storage, etc.) containing computer - usable program code.

[0171] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general - purpose computer, a special - purpose computer, an embedded processor, or other programmable data - processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data - processing devices generate means for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks specified in one block or multiple blocks.

[0172] These computer program instructions can also be stored in a computer - readable memory that can direct a computer or other programmable data - processing device to work in a specific manner, so that the instructions stored in the computer - readable memory generate a manufactured article including instruction means, and the instruction means implements the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks specified in one block or multiple blocks.

[0173] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the steps of the function specified in one process or a plurality of processes and / or boxes Figure 1 one process or a plurality of processes and / or boxes Figure 1 in one box or a plurality of boxes.

[0174] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application rather than to limit the scope of its protection. Although the present application has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: after reading the present application, those skilled in the art can still make various changes, modifications or equivalent replacements to the specific implementation manners of the application, but these changes, modifications or equivalent replacements are all within the scope of protection of the pending claims of the application.

Claims

1. A method for constructing a power characteristic curve of a wind turbine, characterized in that, Including: Obtaining the operation data and historical operation data of a wind turbine within a current period of time; the operation data includes: operation power, the wind speed corresponding to the operation power, and preset influencing factors; Based on the current operation power and the wind speed corresponding to the operation power, constructing an initial wind speed-power characteristic curve within a current period of time; Based on the historical operation data and current influencing factors, constructing a power composite influence factor matrix; Revising the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the wind turbine power characteristic curve within a current period of time; The influencing factors include: air density, turbulence intensity, yaw error; the power composite influence factor matrix is constructed by the influence factor values corresponding to different influencing factor conditions; the influence factor value is the correlation coefficient between the wind speed-power characteristic curve and the initial wind speed-power characteristic curve under different influencing factor conditions; the constructing of the initial wind speed-power characteristic curve within a current period of time based on the current operation power and the wind speed corresponding to the operation power includes: Dividing the operation power and the wind speed data corresponding to the operation power within a current period of time based on a preset wind speed interval; Based on the operation power and the wind speed corresponding to the operation power in each interval, respectively calculating the average wind speed and average output power of each interval; Based on the average wind speed and average output power of each interval, constructing an initial wind speed-power characteristic curve within a current period of time; The constructing of the power composite influence factor matrix based on the historical operation data and current influencing factors includes: Based on the historical operation data, successively calculating the influence factor values corresponding to different influencing factor conditions; Based on the influence factor values corresponding to different influencing factor conditions, determining the influence factor values respectively corresponding to the current influencing factor conditions; Based on the influence factor values respectively corresponding to the current influencing factor conditions, constructing a power composite influence factor matrix; The successively calculating the influence factor values corresponding to different influencing factor conditions based on the historical operation data includes: Based on the historical operation power and the wind speed corresponding to the operation power, constructing a historical initial wind speed-power characteristic curve; Based on the historical operation power, wind speed, air density, and the historical initial wind speed-power characteristic curve, calculating the correlation coefficient between the wind speed-power characteristic curve under different air density conditions and the historical initial wind speed-power characteristic curve as the influence factor value corresponding to different air density conditions; Based on the historical operation power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, calculating the correlation coefficient between the wind speed-power characteristic curve under different turbulence intensity conditions and the historical initial wind speed-power characteristic curve as the influence factor value corresponding to different turbulence intensity conditions; Based on the historical operation power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, calculating the correlation coefficient between the wind speed-power characteristic curve under different yaw error conditions and the historical initial wind speed-power characteristic curve as the influence factor value corresponding to different yaw error conditions.

2. The method according to claim 1, characterized in that, Calculating the correlation coefficient between the wind speed-power characteristic curves under different air density conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, air density, and the historical initial wind speed-power characteristic curve, and taking it as the influence factor value corresponding to different air density conditions, including: Dividing the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset air density conditions; Constructing the wind speed-power characteristic curves for each air density condition interval based on the historical operating power and the wind speed corresponding to the operating power in each air density condition interval; Calculating the correlation coefficient between the wind speed-power characteristic curves of each air density condition interval and the historical initial wind speed-power characteristic curve in sequence, and taking it as the influence factor value corresponding to different air density conditions.

3. The method according to claim 1, characterized in that, Calculating the correlation coefficient between the wind speed-power characteristic curves under different turbulence intensity conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, and taking it as the influence factor value corresponding to different turbulence intensity conditions, including: Dividing the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset turbulence intensity conditions; Constructing the wind speed-power characteristic curves for each turbulence intensity condition interval based on the historical operating power and the wind speed corresponding to the operating power in each turbulence intensity condition interval; Calculating the correlation coefficient between the wind speed-power characteristic curves of each turbulence intensity condition interval and the historical initial wind speed-power characteristic curve in sequence, and taking it as the influence factor value corresponding to different turbulence intensity conditions.

4. The method according to claim 1, characterized in that, Calculating the correlation coefficient between the wind speed-power characteristic curves under different yaw error conditions and the historical initial wind speed-power characteristic curve based on the historical operating power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, and taking it as the influence factor value corresponding to different yaw error conditions, including: Dividing the historical operating power and the wind speed data corresponding to the operating power into intervals based on the preset yaw error conditions; Constructing the wind speed-power characteristic curves for each yaw error condition interval based on the historical operating power and the wind speed corresponding to the operating power in each yaw error condition interval; Calculating the correlation coefficient between the wind speed-power characteristic curves of the yaw error condition interval and the historical initial wind speed-power characteristic curve in sequence, and taking it as the influence factor value corresponding to different yaw error conditions.

5. The method according to claim 1, characterized in that, The expression of the wind turbine power characteristic curve within the current period of time is as follows: Where: P is the operating power of the wind turbine, C p is the power coefficient, ρ0 is the standard air density, A is the swept area of the wind turbine rotor, v is the average wind speed, α ρ is the influence factor value corresponding to the current air density condition, α TI is the influence factor value corresponding to the current turbulence intensity condition, α yaw is the influence factor value corresponding to the current yaw error condition, ρ represents the air density, TI represents the turbulence intensity, and yaw represents the yaw error.

6. A system for constructing a power characteristic curve of a wind turbine, characterized in that,Including: A data acquisition module for acquiring the operating data and historical operating data of the wind turbine within the current period of time; the operating data includes: operating power, the wind speed corresponding to the operating power, and preset influencing factors; An initial power curve construction module for constructing the initial wind speed-power characteristic curve within the current period of time based on the current operating power and the wind speed corresponding to the operating power; A composite influence factor matrix construction module for constructing a power composite influence factor matrix based on the historical operating data and the current influencing factors. A composite power curve construction module, which is used to revise the initial wind speed-power characteristic curve based on the power composite influence factor matrix to obtain the wind turbine power characteristic curve within a current period of time; The influencing factors include: air density, turbulence intensity, and yaw error; the power composite influence factor matrix is constructed by the influence factor values corresponding to different influencing factor conditions; the influence factor value is the correlation coefficient between the wind speed-power characteristic curve and the initial wind speed-power characteristic curve under different influencing factor conditions; the initial power curve construction module includes: A wind speed data division sub-module, which is used to divide the operating power and the wind speed data corresponding to the operating power within a current period of time based on a preset wind speed interval; An interval data calculation sub-module, which is used to calculate the average wind speed and the average output power of each interval respectively based on the operating power of each interval and the wind speed corresponding to the operating power; An initial power curve fitting sub-module, which is used to construct the initial wind speed-power characteristic curve within a current period of time based on the average wind speed and the average output power of each interval; The composite influence factor matrix construction module includes: A historical influence factor value calculation sub-module, which is used to calculate the influence factor values corresponding to different influencing factor conditions in sequence based on historical operation data; A current influence factor value determination sub-module, which is used to determine the influence factor values corresponding to the current influencing factor conditions respectively based on the influence factor values corresponding to different influencing factor conditions; A matrix construction sub-module, which is used to construct a power composite influence factor matrix based on the influence factor values corresponding to the current influencing factor conditions respectively; The historical influence factor value calculation sub-module includes: A historical initial power curve construction unit, which is used to construct a historical initial wind speed-power characteristic curve based on historical operating power and the wind speed corresponding to the operating power; A different air density influence factor value calculation unit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve and the historical initial wind speed-power characteristic curve under different air density conditions based on historical operating power, wind speed, air density, and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different air density conditions; A different turbulence intensity influence factor value calculation unit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve and the historical initial wind speed-power characteristic curve under different turbulence intensity conditions based on historical operating power, wind speed, turbulence intensity, and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different turbulence intensity conditions; A different yaw error influence factor value calculation unit, which is used to calculate the correlation coefficient between the wind speed-power characteristic curve and the historical initial wind speed-power characteristic curve under different yaw error conditions based on historical operating power, wind speed, yaw error, and the historical initial wind speed-power characteristic curve, and use it as the influence factor value corresponding to different yaw error conditions.

7. The system according to claim 6, wherein, The different air density influence factor value calculation unit includes: An air density data division sub-unit, which is used to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on preset air density conditions; An air density power curve construction subunit, configured to construct a wind speed-power characteristic curve for each air density condition interval based on the historical operating power and the wind speed corresponding to the operating power in each air density condition interval; An air density influence factor value calculation subunit, configured to sequentially calculate the correlation coefficients between the wind speed-power characteristic curves of the respective air density condition intervals and the historical initial wind speed-power characteristic curve, as the influence factor values corresponding to different air density conditions.

8. The system according to claim 6, wherein, The different turbulence intensity influence factor value calculation unit includes: A turbulence intensity data division subunit, configured to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on a preset turbulence intensity condition; A turbulence intensity power curve construction subunit, configured to construct a wind speed-power characteristic curve for each turbulence intensity condition interval based on the historical operating power and the wind speed corresponding to the operating power in each turbulence intensity condition interval; A turbulence intensity influence factor value calculation subunit, configured to sequentially calculate the correlation coefficients between the wind speed-power characteristic curves of the respective turbulence intensity condition intervals and the historical initial wind speed-power characteristic curve, as the influence factor values corresponding to different turbulence intensity conditions.

9. The system according to claim 6, wherein, The different yaw error influence factor value calculation unit includes: A yaw error data division subunit, configured to divide the historical operating power and the wind speed data corresponding to the operating power into intervals based on a preset yaw error condition; A yaw error power curve construction subunit, configured to construct a wind speed-power characteristic curve for each yaw error condition interval based on the historical operating power and the wind speed corresponding to the operating power in each yaw error condition interval; A yaw error influence factor value calculation subunit, configured to sequentially calculate the correlation coefficients between the wind speed-power characteristic curves of the yaw error condition intervals and the historical initial wind speed-power characteristic curve, as the influence factor values corresponding to different yaw error conditions.

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