A calculation method for intelligent online compensation of yaw static error of megawatt-class wind turbines

Abstract

The present invention relates to the field of wind turbine control, and in particular to a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine. The method comprises the following steps: calculating the ratio of the assumed wind wheel inflow wind speed to the anemometer output value; calculating the real-time power coefficient according to the ratio of the assumed wind wheel inflow wind speed to the anemometer output value; calculating the axial induction factor according to the real-time power coefficient; calculating the line speed ratio value at the wind vane; and calculating the instantaneous wind direction deviation according to the axial induction factor and the line speed ratio at the wind vane. Through algorithm calculation, the wind direction measurement deviation is judged in real time, and the deviation is intelligently corrected, thereby solving the measurement problem of the traditional anemometer and achieving the purpose of increasing the power generation of the wind turbine without increasing the hardware cost.

Description

Technical Field

[0001] The invention relates to the field of wind turbine control, and in particular to a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine set. Background Art

[0002] At present, China's wind power installed capacity has maintained the world's first place for many years, and wind power accounts for a considerable proportion in the power industry. Lean development is imperative, and the economic benefits of using new technologies to increase the power generation per unit installed capacity are very considerable. Driven by the grid parity strategy, the current key task of the wind power industry is to increase the wind power utilization rate of wind power equipment by improving the control algorithm without increasing or reducing the input cost, thereby increasing power generation.

[0003] The development direction of the fan control algorithm is to coordinate the site-based control with the intelligent algorithm improvement, requiring the fan to automatically calibrate the deficiencies of its own collected data, make judgments and corrections, and achieve the effect of self-correction liberalization. The fan is required to use historical data to determine the optimal parameter range of its own control, perform self-correction, and gradually optimize; the fan is required to coordinate control with adjacent fans, purposefully sacrificing the optimal effect of part of its own control to achieve the optimal control effect of the whole field. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine, so as to solve the problem of affecting power generation due to the existence of measurement deviation.

[0005] The technical solution of the present invention to solve the above technical problem is as follows: A calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine generator system comprises the following steps:

[0006] Calculate the ratio of the assumed wind speed in the wind turbine to the anemometer output value;

[0007] Calculate the real-time power coefficient based on the ratio of the assumed wind speed at the wind turbine inlet to the output value of the anemometer;

[0008] Calculate the axial induction factor based on the real-time power coefficient;

[0009] Calculate the linear speed ratio at the wind vane;

[0010] The instantaneous wind direction deviation is calculated based on the axial induction factor and the linear speed ratio at the wind vane.

[0011] Furthermore, the calculation formula for the ratio of the assumed wind wheel inflow wind speed to the anemometer output value is:

[0012]

[0013] V0: assumed wind speed at the inflow of the wind wheel, ω: wind speed of the wind wheel, h: installation height of the anemometer, a: axial induction factor, k: ratio of the assumed wind speed at the inflow of the wind wheel to the output value of the anemometer, V c : Anemometer output value.

[0014] Furthermore, the calculation formula of the real-time power coefficient is:

[0015]

[0016] Among them, C P : Wind turbine power coefficient, V0: Assumed wind speed at the rotor, P: Generator power, A: Rotor area, ρ: Air density, V c : Anemometer output value, P Gen : Generator power measurement value.

[0017] Furthermore, the calculation formula of the axial induction factor is:

[0018] a=0.15C P 3 +0.34C P

[0019] Among them, C P : fan power coefficient, a: axial induction factor.

[0020] Further, the calculation formula of the linear speed ratio at the wind vane is:

[0021]

[0022] Where, x: Linear speed ratio at the wind vane, K GearBox : gearbox ratio; h: installation height of anemometer.

[0023] Furthermore, the calculation formula of the instantaneous wind direction deviation is:

[0024]

[0025] Where, θ: instantaneous wind direction deviation, x: linear speed ratio at the wind vane, k: ratio of assumed wind wheel inflow wind speed to anemometer output value, a: axial induction factor.

[0026] The present invention provides a method for calculating the static error of yaw of a megawatt-class wind turbine set by intelligent online compensation, comprising the following steps:

[0027] Calculate the ratio of the assumed wind speed in the wind turbine to the anemometer output value;

[0028] Calculate the real-time power coefficient based on the ratio of the assumed wind speed at the wind turbine inlet to the output value of the anemometer;

[0029] Calculate the axial induction factor based on the real-time power coefficient;

[0030] Calculate the linear speed ratio at the wind vane;

[0031] The instantaneous wind direction deviation is calculated based on the axial induction factor and the linear speed ratio at the wind vane.

[0032] In this way, through algorithm calculation, the wind direction measurement deviation can be judged in real time and the deviation can be corrected intelligently, thereby solving the measurement problems of traditional anemometers and achieving the goal of increasing wind turbine power generation without increasing hardware costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine according to the present invention;

[0034] Figure 2 A schematic diagram of the wake change in a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine set according to the present invention;

[0035] Figure 3 The present invention provides a control algorithm flow chart for a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine set. DETAILED DESCRIPTION

[0036] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0037] like Figure 1 As shown, the present invention provides a calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine, comprising the following steps:

[0038] Calculate the ratio of the assumed wind speed in the wind turbine to the anemometer output value;

[0039] Calculate the real-time power coefficient based on the ratio of the assumed wind speed at the wind turbine inlet to the output value of the anemometer;

[0040] Calculate the axial induction factor based on the real-time power coefficient;

[0041] Calculate the linear speed ratio at the wind vane;

[0042] The instantaneous wind direction deviation is calculated based on the axial induction factor and the linear speed ratio at the wind vane.

[0043] In this way, through algorithm calculation, the wind direction measurement deviation can be judged in real time and the deviation can be corrected intelligently, thereby solving the measurement problems of traditional anemometers and achieving the goal of increasing wind turbine power generation without increasing hardware costs.

[0044] The calculation method of the megawatt-class wind turbine set intelligent online compensation yaw static error of the present invention is as follows: Figure 1 As shown, based on the technical solution described above, the calculation formula for the ratio of the assumed wind wheel inflow wind speed to the anemometer output value is:

[0045]

[0046] V0: assumed wind speed at the inflow of the wind wheel, ω: wind speed of the wind wheel, h: installation height of the anemometer, a: axial induction factor, k: ratio of the assumed wind speed at the inflow of the wind wheel to the output value of the anemometer, V c : Anemometer output value.

[0047] Thus, as shown in Figure X, the wind speed decomposition diagram at the location of the anemometer when viewed from directly above has the same triangular relationship as the extension of the wind speed wake running direction. It is obvious that the angle θ is the error between the wind direction measured by the anemometer and the actual wind direction, and satisfies the following relationship:

[0048]

[0049] Where, a': tangential induction factor, V θ : Tangential wind speed in the wind turbine wake.

[0050] According to the momentum theory of an ideal fan, the axial induction factor and the tangential induction factor satisfy the following relationship:

[0051] y 2 a'(1+a')=a(1-a) (2)

[0052] in, According to formula (2), we can get:

[0053]

[0054] Substituting (3) into formula (1), we get:

[0055]

[0056] make but Substituting into (4) we get:

[0057]

[0058] according to Figure 1 The geometric relationship shows that:

[0059] V c 2 =V θ 2 +V a 2

[0060] Right now

[0061]

[0062] Substituting (3) into (6), we get:

[0063]

[0064] therefore,

[0065]

[0066] Combined with the range of formula (8), we can get:

[0067]

[0068] Substituting the middle value -0.25 for the above formula, we get:

[0069] k≈1.15(9)

[0070] The above k value is obtained based on the estimated value of the theoretical value interval. To verify the rationality of the value, the statistical identification method of actual data is used. Now the laser radar anemometer is installed on the nacelle to measure the wind speed and direction 80m in front of the wind rotor, and this measured wind direction is considered to be the incoming wind V0. The wind speed data actually measured by the radar anemometer and the wind speed and direction meter are used to draw a distribution diagram of the ratio of the two. Figure 2 As shown in Figure 2, it can be seen that the ratio of the two is a normal distribution with a mathematical expectation of approximately 1.02 and a variance of 0.26, which is consistent with the theoretical value k = 1.15.

[0071] Furthermore, the calculation formula of the real-time power coefficient is:

[0072]

[0073] Among them, C P : Wind turbine power coefficient, V0: Assumed wind speed at the rotor, P: Generator power, A: Rotor area, ρ: Air density, V c : Anemometer output value, P Gen : Generator power measurement value.

[0074] Thus, from formula (4), it can be seen that the calculation of the deviation θ requires not only the wind wheel speed ω and the wind speed V output by the anemometer: c In addition, an axial induction factor a is also required.

[0075] According to the power factor C p From the definition of and the momentum theory of an ideal fan, we know

[0076]

[0077] Numerical processing of the axial induction factor equation of wind energy utilization

[0078] According to the Betz limit, C P The theoretical maximum value of is 0.593, at which the axial induction factor a is equal to 0.3. Therefore, after limiting the interval of the induction factor a to (0.1, 0.3), the trigonometric function formula (11) can be used to fit formula (10):

[0079] f(a)=0.6sin(5a) (11)

[0080] Since the inverse trigonometric function arcsin(x) can be expressed as formula (12) after Taylor series expansion:

[0081]

[0082] Combining equation (10), equation (11) and equation (12), we can get:

[0083] a=0.15C P 3 +0.34C P (13)

[0084] And C P Calculated by formula (13)

[0085]

[0086] At this point, the derivation of the yaw error tangential induction factor compensation algorithm has been completed

[0087] Control process of online intelligent compensation algorithm for yaw error

[0088] In order to make the real-time control implementation process clear, the computer implementation process is summarized as follows:

[0089] Input wind turbine state variables: generator power measurement value P Gen , unit kW; anemometer collects wind speed value V c . Generator speed acquisition value ω Gen , unit rpm; current air density value ρ.

[0090] (1) Calculate the real-time power factor:

[0091]

[0092] Among them: k is 1.15.

[0093] (2) Calculate the linear speed ratio x at the wind vane.

[0094]

[0095] Where: K GearBox : gearbox ratio; k: actual installation height of anemometer.

[0096] (3) Calculate the axial induction factor.

[0097] a=0.15C P 3 +0.34C P (17)

[0098] (4) Calculate the instantaneous wind direction deviation that needs to be compensated.

[0099]

[0100] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine, characterized in that: The following steps are included: Calculate the ratio of the assumed wind speed in the wind turbine to the anemometer output value; Calculate the real-time power coefficient based on the ratio of the assumed wind speed at the wind turbine inlet to the output value of the anemometer; Calculate the axial induction factor based on the real-time power coefficient; Calculate the linear speed ratio at the wind vane; Calculate the instantaneous wind direction deviation based on the axial induction factor and the linear speed ratio at the wind vane; The calculation formula of the instantaneous wind direction deviation is: Where, θ: instantaneous wind direction deviation, x: linear speed ratio at the wind vane, k: ratio of assumed wind wheel inflow wind speed to anemometer output value, a: axial induction factor.

2. The calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine according to claim 1 is characterized by: The calculation formula for the ratio of the assumed wind wheel inflow wind speed to the anemometer output value is: V0: assumed wind speed at the inflow of the wind wheel, ω: wind speed of the wind wheel, h: installation height of the anemometer, a: axial induction factor, k: ratio of the assumed wind speed at the inflow of the wind wheel to the output value of the anemometer, V c : Anemometer output value.

3. The calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine according to claim 2 is characterized by: The calculation formula of the real-time power coefficient is: Among them, C P : Wind turbine power coefficient, V0: Assumed wind speed at the rotor, P: Generator power, A: Rotor area, ρ: Air density, V c : Anemometer output value, P Gen : Generator power measurement value.

4. The calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine according to claim 3 is characterized by: The calculation formula of the axial induction factor is: a=0.15C P 3 +0.34C P Among them, C P : fan power coefficient, a: axial induction factor.

5. The calculation method for intelligent online compensation of yaw static error of a megawatt-class wind turbine according to claim 1 is characterized by: The calculation formula of the linear speed ratio at the wind vane is: Where, x: Linear speed ratio at the wind vane, K GearBox : gearbox ratio; h: installation height of anemometer; ω Gen : Generator speed acquisition value; V c : Anemometer output value.

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