A frequency adaptive control method for wind turbines taking into account power generation loss

Abstract

The present invention discloses a method for adaptive frequency control of a wind turbine generator set taking into account power generation loss. In order to solve the problems of low operating efficiency and large power generation loss of wind turbine generator sets in the prior art, the present invention adopts the following steps: according to the operating characteristics of the wind turbine generator set, a static power mathematical model of the wind turbine generator set is established; according to the requirements of the power grid frequency regulation standard, the frequency regulation response value ΔP corresponding to different power grid frequency feedback signals f is calculated; to meet the frequency regulation requirements of the unit, the unit is subjected to load shedding at the pitch angle for power standby; a Lagrange multiplier method program is written on Matlab to solve the output power at different output power points P s , different grid frequency points f n The pitch angle reference value θ(s, n) under the condition of frequency modulation is obtained; the bilinear interpolation method is used to perform the frequency modulation adaptive online parameter search work to perform real-time frequency modulation response to the wind turbine. Advantages: It improves the online parameter search efficiency, reduces the power generation loss, and has strong frequency modulation adaptability and robustness.

Description

Technical Field

[0001] The present invention relates to the technical field of power system stability control, and in particular to a frequency adaptive control method for a wind turbine generator set taking power generation loss into account. Background Art

[0002] As renewable energy is connected to the power system, the proportion of traditional generators in the power system continues to decline. The high penetration of renewable energy reduces the inertia of the power system and endangers the frequency stability of the system. Power grids with large-scale renewable energy are extremely vulnerable to disturbance faults and power shortages, and may even lead to tripping, cascading failures and power outages.

[0003] In order to enable wind turbines to participate in the primary frequency regulation of the power grid when the frequency is unstable, the units generally need to reduce load and use standby active power. Wind turbines generally operate on the optimal power tracking curve, and can reduce load by reducing the wind energy utilization coefficient. The wind energy utilization coefficient is related to the tip speed ratio and the pitch angle, that is, the power output can be reduced by adjusting the two. On the basis of the wind turbine obtaining standby power through load reduction control, the introduction of additional power control links enables the wind turbine to have the ability to participate in the primary frequency regulation of the power system.

[0004] The traditional frequency control strategy is to make the wind turbine run in a limited power state by modifying the target speed, and calculate the frequency target value according to the frequency deviation signal and its frequency droop characteristics, and send it to the wind turbine as an active power control instruction. In a large number of actual engineering applications, although the traditional frequency control strategy can participate in the primary frequency regulation of the power system, due to the randomness, intermittency and volatility of wind speed fluctuations, the initial power target value of the wind turbine needs to be limited to a lower level to enable it to have long-term frequency regulation capabilities, so that the wind turbine needs to be in a low power operation level for a long time, which increases the power generation loss of the unit and reduces the profit of the wind farm.

[0005] For example, a "method for optimizing the combination of power system units considering the frequency regulation control of wind turbines" disclosed in Chinese patent documents, with announcement number CN112803487A and publication date of May 14, 2021, includes the invention of a method for optimizing the combination of power system units considering the frequency regulation control of wind turbines, which belongs to the field of power systems; the invention adopts overspeed load reduction and virtual inertia control for wind turbines, and takes the wind turbine frequency regulation factors into consideration in the study of the combination strategy of power system units under dynamic frequency constraints. When the combination mode of thermal power units under conventional constraints does not meet the frequency limit requirements, the wind turbine can be controlled within the range of wind turbine load reduction constraints, so that the wind turbine has frequency regulation capability and increases the system inertia. The invention cannot respond to the frequency regulation of wind turbines in real time and has weak frequency regulation adaptability, nor can it reduce the power generation loss of wind turbines. Summary of the invention

[0006] The present invention mainly solves the problems of low operating efficiency and large power generation loss of wind turbines in the prior art; provides a wind turbine frequency adaptive control method taking power generation loss into account, adopts the Lagrange multiplier method to extract the relationship between frequency-power-pitch angle offline, and improves the online parameter search efficiency; adopts the bilinear interpolation method to solve the wind turbine pitch angle given value to perform real-time frequency modulation response on the wind turbine, reduces power generation loss, and has strong frequency modulation adaptability and robustness.

[0007] The above technical problems of the present invention are mainly solved by the following technical solutions:

[0008] The present invention comprises the following steps:

[0009] Step 1: According to the operating characteristics of the wind turbine, a static power mathematical model of the wind turbine is established;

[0010] Step 2: According to the grid frequency regulation standard requirements, calculate the frequency regulation response value ΔP corresponding to different grid frequency feedback signals f;

[0011] Step 3: Perform pitch angle load shedding on the unit for power standby;

[0012] Step 4: Write a Lagrange multiplier method program on the software to solve the output power at different points P s , different grid frequency points f n The pitch angle reference value θ(s,n) under

[0013] Step 5: Extract the relationship between frequency, power and pitch angle from step 4 and import it into the core controller of the wind turbine. When the main controller receives the grid frequency and wind turbine power information (f(t), P(t)) at time t, the bilinear interpolation method is used to perform frequency adaptive online parameter search to perform real-time frequency response for the wind turbine.

[0014] This solution can improve the efficiency of online parameter search, reduce power generation losses, and has strong frequency regulation adaptability and robustness.

[0015] Preferably, the mechanical power P in step 1 m and wind energy utilization coefficient C p The relationship between (λ, β) is as follows:

[0016]

[0017] Among them, ρ is the air density, R is the blade radius, λ is the tip speed ratio, ν is the wind speed, ω is the rotation speed, β is the pitch angle, c1~c6 are the blade aerodynamic inherent characteristic parameters, and λ1 is the blade aerodynamic dynamic characteristic parameter.

[0018] Preferably, the algorithm for calculating the frequency modulation response value ΔP in step 2 is as follows:

[0019] ΔP=(f--f0±f d )×k×Pn / 50

[0020] Among them, f0 is the rated frequency of the power grid, f d is the frequency dead zone value, Pb is the rated capacity of the unit, and k is the frequency regulation limiting coefficient.

[0021] Preferably, in step 3, in addition to performing load shedding of the unit for power standby at the pitch angle, in order to ensure that the pitch angle change is minimized to increase the adjustment rate and reduce mechanical wear, an objective function is constructed to obtain the minimum pitch angle adjustment amount:

[0022] F(ω ref , β ref )=min|β0-β ref |.

[0023] Preferably, the step 4 also requires the output power P m ∈(P min , P max ) Take P1,…,P s …, P max Multiple power points, grid frequency feedback signal f∈(f min , f max ) Take f1,…,f n …, f max Multiple frequency points, and ω ref , β ref , speed adjustment time, etc. to perform equality constraints and inequality constraints.

[0024] Preferably, in step 4, the Lagrange multiplier method is used to solve the global optimal solution of the objective function, and the specific solution steps are as follows:

[0025] Step 4.1: Analyze the operating characteristics of the wind turbine pitch angle load reduction power reserve, and extract the nonlinear equality constraints and inequality constraints of the objective function corresponding to step 3. The specific constraints are as follows:

[0026]

[0027] Among them, T r is the speed adjustment time, ΔP n is the frequency f n The corresponding frequency modulation response power value, Δt ω is the speed adjustment time; Step 4.2: For the objective function F(ω ref , β ref) performs Lagrangian transformation to obtain the unconstrained optimization function, and establishes the Lagrangian function L under inequality constraints, as shown in the following formula:

[0028]

[0029] Where X = (ω ref , β ref ), h(X) is the equality constraint, X=(ω ref , β ref ) is the independent variable of the objective function, γ j is the corresponding constraint coefficient, g(X) is the inequality constraint, u k is the corresponding constraint coefficient;

[0030] Step 4.3: To obtain the objective function F(ω ref , β ref ) also needs to satisfy the Carlo-Kuhn-Tucker condition:

[0031]

[0032] Among them, X * Indicates the minimum value point of the independent variable X;

[0033] Step 4.4: For the objective function that satisfies the Carlo-Kuhn-Tucker condition, the global optimal solution (ω ref , β ref ), record different output power points P s , different grid frequency points f n The corresponding relationship between the pitch angle reference value θ(s, n) under .

[0034] This solution uses the Lagrange multiplier method to extract the relationship between frequency, power and pitch angle offline, thereby improving the efficiency of online parameter search.

[0035] Preferably, in step 5, when the master controller receives the grid frequency and wind turbine power information (f(t), P(t)) at time t, a bilinear interpolation method is used to perform frequency modulation adaptive online parameter search, and the specific parameter search steps are as follows:

[0036] Step 5.1: According to the relationship between frequency, power and pitch angle recorded in step 4, extract four adjacent points that satisfy the relationship f′≤f(t)≤f″, P′≤P(t)≤P″, and proceed to the next step. If they do not exist, proceed to step 5.6, where f′ and f″ are both frequency points, which are f1, ..., f n …, f max Two adjacent points, P′ and P″, are power points, which are P1,…,P s …, Pmax Two adjacent points in the middle;

[0037] Step 5.2: Mark the pitch angles corresponding to the four points in step 5.1 as θ from left to right and from top to bottom. 11 ,θ 12 ,θ 21 ,θ 22 ;

[0038] Step 5.3: Use bilinear interpolation to calculate the given pitch angle θ of the wind turbine at time t. The calculation formula is as follows:

[0039]

[0040] Step 5.4: Feedback the pitch angle given degree θ calculated at time t to the pitch actuator to perform a frequency modulation response;

[0041] Step 5.5: Enter the execution cycle at time t+1 and return to step 5.1;

[0042] Step 5.6: When f(t)≤f1, then take f(t)=f1; when f(t)>f max , then f(t)=f max ; When P(t)≤P1, then P(t)=P1; When P(t)>P max , then P(t)=P max , return to step 5.1.

[0043] This scheme uses bilinear interpolation to solve the given value of the wind turbine pitch angle to perform real-time frequency regulation response on the wind turbine, reducing power generation loss and having strong frequency regulation adaptability and robustness.

[0044] The beneficial effects of the present invention are:

[0045] 1. The Lagrange multiplier method is used to extract the relationship between frequency, power and pitch angle offline, which improves the efficiency of online parameter search;

[0046] 2. The bilinear interpolation method is used to solve the given value of the wind turbine pitch angle to perform real-time frequency regulation response on the wind turbine, reducing the power generation loss and having strong frequency regulation adaptability and robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a structural schematic diagram of the present invention.

[0048] Figure 2 It is a curve diagram of the frequency regulation standard requirements of the wind turbine set of the present invention.

[0049] Figure 3This is a dynamic response curve diagram of the wind turbine system with improved frequency modulation control strategy under constant wind speed and frequency disturbance. Figure (a) is the wind speed, Figure (b) is the grid frequency, Figure (c) is the pitch angle given value, and Figure (d) is the output power.

[0050] Figure 4 This is a comparison diagram of the dynamic response of the wind turbine system with the improved frequency modulation control strategy and the traditional frequency modulation control strategy under turbulent wind conditions. Figure (a) is the wind speed, and Figure (b) is the output power.

[0051] In the figure, 1. actual output curve of wind turbine, 2. improved frequency modulation control strategy curve, 3. traditional frequency modulation control strategy curve. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0053] Example:

[0054] The wind turbine frequency adaptive control method of this embodiment taking into account the power generation loss fully considers the defects of the traditional frequency modulation technology, establishes a static power mathematical model of the wind turbine from the perspective of the wind turbine operation benefit and economy, calculates the frequency modulation response value corresponding to the frequency modulation standard requirements, and uses the Lagrange multiplier method to extract the relationship between frequency-power-pitch angle offline, thereby improving the online parameter search efficiency. The wind turbine core controller receives the frequency information from the power grid and the power information of the wind turbine, and uses the bilinear interpolation method to solve the wind turbine pitch angle given value to perform real-time frequency modulation response on the wind turbine, thereby reducing the power generation loss and having strong frequency modulation adaptability and robustness.

[0055] In order to achieve the above purpose, the specific design steps of a wind turbine frequency adaptive control method taking into account power generation loss are as follows:

[0056] Step 1: According to the operating characteristics of the wind turbine, a mathematical model of the static power of the wind turbine is established, where the mechanical power P m and wind energy utilization coefficient C p The relationship between (λ, β) is as follows:

[0057]

[0058] Among them, ρ is air density, R is blade radius, λ is tip speed ratio, λ is wind speed, ω is rotation speed, β is pitch angle, c1~c6 are blade aerodynamic inherent characteristic parameters, λ1 is blade aerodynamic dynamic characteristic parameter;

[0059] Step 2: According to the grid frequency regulation standard requirements, calculate the frequency regulation response value ΔP corresponding to different grid frequency feedback signals f:

[0060] ΔP=(f-f0±f d )×k×Pn / 50

[0061] Among them, f0 is the rated frequency of the power grid, f d is the frequency dead zone value, Pn is the rated capacity of the unit, and k is the frequency regulation limit coefficient;

[0062] Step 3: To meet the frequency regulation requirements of the unit, the unit is subjected to load shedding for power standby. At the same time, to ensure that the pitch angle change is minimized to increase the regulation rate and reduce mechanical wear, an objective function is constructed to obtain the minimum pitch angle adjustment amount:

[0063] F(ω ref , β ref )=min|β0-β ref |ω ref is the speed reference value, β ref is the pitch angle reference value, β0 is the pitch angle initial value;

[0064] Step 4: Set the output power P m ∈(P min , P max ) Take P1,…,P s …, P max Multiple power points, grid frequency feedback signal f∈(f min , f max ) Take f1,…,f n …, f max Multiple frequency points, and ω ref , β ref , speed adjustment time, etc.; write a Lagrange multiplier method program on Matlab to solve the output power at different points P s , different grid frequency points f n The pitch angle reference value θ(s, n) under the condition is used, and the Lagrange multiplier method is used to solve the global optimal solution of the objective function. The specific solution steps are as follows:

[0065] Step 4.1: Analyze the operating characteristics of the wind turbine pitch angle load reduction power reserve, and extract the nonlinear equality constraints and inequality constraints of the objective function corresponding to step 3. The specific constraints are as follows:

[0066]

[0067] Among them, T r is the speed adjustment time, ΔP n is the frequency f n The corresponding frequency modulation response power value, Δt ωis the speed adjustment time; Step 4.2: For the objective function F(ω ref , β ref ) is transformed into an unconstrained optimization problem, and the Lagrangian function L under inequality constraints is established as follows:

[0068]

[0069] Where X = (ω ref , β ref ), h(X) is the equality constraint, X=(ω ref , β ref ) is the independent variable of the objective function, γ j is the corresponding constraint coefficient, g(X) is the inequality constraint, u k is the corresponding constraint coefficient;

[0070] Step 4.3: To obtain the objective function F(ω ref , β ref ) also needs to satisfy the Carlo-Kuhn-Tucker condition:

[0071]

[0072] Among them, X * Indicates the minimum value point of the independent variable X;

[0073] Step 4.4: For the objective function that satisfies the Carlo-Kuhn-Tucker condition, the global optimal solution (ω ref , β ref ), record different output power points P s , different grid frequency points f n The corresponding relationship between the pitch angle reference value θ(s, n) under θ;

[0074] Step 5: Extract the relationship between frequency, power and pitch angle obtained by offline parameter search in step 4, and import it into the core controller of the wind turbine. When the main controller receives the grid frequency and wind turbine power information (f(t), P(t)) at time t, the bilinear interpolation method is used to perform frequency modulation adaptive online parameter search to perform real-time frequency modulation response on the wind turbine. The specific parameter search steps are as follows:

[0075] Step 5.1: According to the relationship between frequency, power and pitch angle recorded in step 4, extract four adjacent points that satisfy the relationship f′≤f(t)≤f″, P′≤P(t)≤P″, and proceed to the next step. If they do not exist, proceed to step 5.6, where f′ and f″ are both frequency points, which are f1, ..., f n …, f maxTwo adjacent points, P′ and P″, are power points, which are P1,…,P s …, P max Two adjacent points in the middle;

[0076] Step 5.2: Mark the pitch angles corresponding to the four points in step 5.1 as θ from left to right and from top to bottom. 11、 θ 12 ,θ 21 ,θ 22 ;

[0077] Step 5.3: Use bilinear interpolation to calculate the given pitch angle θ of the wind turbine at time t. The calculation formula is as follows:

[0078]

[0079] Step 5.4: Feedback the pitch angle given degree θ calculated at time t to the pitch actuator to perform a frequency modulation response;

[0080] Step 5.5: Enter the execution cycle at time t+1 and return to step 5.1;

[0081] Step 5.6: When f(t)≤f1, then take f(t)=f1; when f(t)>f ma x, then f(t) = f ma x; when P(t)≤P1, then P(t)=P1; when P(t)>P max , then P(t)=P max , return to step 5.1.

[0082] The first three steps of the present invention respectively provide algorithms for power, frequency, and pitch angle, providing parameter support for the Lagrange multiplier method in step 4 and the bilinear interpolation method in step 5, and also facilitating the step 4 to obtain the relationship between frequency, power, and pitch angle. The present invention improves the operating efficiency of the wind turbine generator set, reduces economic losses, and improves economic benefits by adopting the Lagrange multiplier method and the bilinear interpolation method.

[0083] It should be understood that the embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope limited by the appended claims of the application.

Claims

1. A method for adaptive frequency control of a wind turbine generator set taking into account power generation loss, characterized in that: The following steps are involved: Step 1: According to the operating characteristics of the wind turbine, a static power mathematical model of the wind turbine is established; Step 2: According to the grid frequency regulation standard requirements, calculate the frequency regulation response value △P corresponding to different grid frequency feedback signals f; Step 3: Perform pitch angle load shedding on the unit for power standby; Step 4: Write a Lagrange multiplier method program on the software to solve the output power at different points P s , different grid frequency points f n The pitch angle reference value θ(s,n) under θ; Step 5: Extract the relationship between frequency, power and pitch angle from step 4 and import it into the core controller of the wind turbine. When the main controller receives the grid frequency and wind turbine power information (f(t), P(t)) at time t, the bilinear interpolation method is used to perform frequency modulation adaptive online parameter search to perform real-time frequency modulation response for the wind turbine. Step 5.1: Take 4 points that are less than or equal to f(t), greater than or equal to f(t), less than or equal to P(t), and greater than or equal to P(t) and are adjacent. If they do not exist, when f(t) is less than or equal to the first frequency point f1, take f(t) as f1; when f(t) is greater than the maximum frequency point f max , take f(t) as f max ; When P(t) is less than or equal to the first power point P1, take P(t) as P1; when P(t) is greater than the maximum power point P max , take P(t) as P max , then take 4 points; Step 5.2: Mark the pitch angles corresponding to the four points from left to right and from top to bottom, use bilinear interpolation to calculate the given degree of the wind turbine pitch angle at time t, and feed it back to the variable pitch actuator for frequency modulation response, enter the execution cycle at time t+1, and return to step 5.

1.

2. A method for adaptive frequency control of wind turbines taking into account power generation loss according to claim 1, characterized in that: In step 1, the mechanical power P m and wind energy utilization coefficient C p The relationship between (λ,β) is as follows: Among them, ρ is the air density, R is the blade radius, λ is the tip speed ratio, ν is the wind speed, ω is the rotation speed, β is the pitch angle, c1~c6 are the blade aerodynamic inherent characteristic parameters, and λ1 is the blade aerodynamic dynamic characteristic parameter.

3. The method for adaptive frequency control of a wind turbine generator set taking into account power generation loss according to claim 1, characterized in that: The algorithm of the frequency modulation response value △P in step 2 is as follows: △P=(f-f0±f d )×k×Pn / 50 Among them, f0 is the rated frequency of the power grid, f d is the frequency dead zone value, Pn is the rated capacity of the unit, and k is the frequency regulation limiting coefficient.

4. The method for adaptive frequency control of a wind turbine generator set taking into account power generation loss according to claim 1, characterized in that: In step 3, in addition to performing pitch angle load shedding for the unit to provide power reserve, an objective function is constructed to obtain the minimum pitch angle adjustment amount: F(ω ref ,b ref )=min|β0-β ref | ω ref is the speed reference value, β ref is the reference value of the pitch angle, and β0 is the initial value of the pitch angle.

5. A method for adaptive frequency modulation control of a wind turbine generator system taking into account power generation loss according to claim 1, 2 or 4, characterized in that: The step 4 also needs to set the output power P m ∈(P min , P max ) Take P1,…,P s …, P max Multiple power points, grid frequency feedback signal f∈(f min , f max ) Take f1,…,f n …, f max Multiple frequency points, and ω ref , β ref , speed adjustment time, etc. to perform equality constraints and inequality constraints.

6. A method for adaptive frequency control of wind turbines taking into account power generation loss according to claim 5, characterized in that: In step 4, the Lagrange multiplier method is used to solve the global optimal solution of the objective function. The specific solution steps are as follows: Step 4.1: Analyze the operating characteristics of the wind turbine pitch angle load reduction power reserve, and extract the nonlinear equality constraints and inequality constraints of the objective function corresponding to step 3. The specific constraints are as follows: Among them, T r is the speed adjustment time, △P n is the frequency f n The corresponding frequency modulation response power value, Δt ω Adjust the time for the speed; Step 4.2: For the objective function F(ω ref ,β ref ) performs Lagrangian transformation to obtain the unconstrained optimization function, and establishes the Lagrangian function L under inequality constraints, as shown in the following formula: Where X = (ω ref ,β ref ), h(X) is the equality constraint, X=(ω ref ,β ref ) is the independent variable of the objective function, γ j is the corresponding constraint coefficient, g(X) is the inequality constraint, u k is the corresponding constraint coefficient; Step 4.3: In order to obtain the objective function F(ω ref ,β ref ) also needs to satisfy the Carlo-Kuhn-Tucker condition: Among them, X * Indicates the minimum value point of the independent variable X; Step 4.4: For the objective function that satisfies the Carlo-Kuhn-Tucker condition, the global optimal solution (ω ref ,β ref ), record different output power points P s , different grid frequency points f n The corresponding relationship between the pitch angle reference value θ(s,n) under .

7. A method for adaptive frequency control of wind turbines taking into account power generation loss according to claim 1, characterized in that: In step 5, when the main control receives the grid frequency and wind turbine power information (f(t), P(t)) at time t, the bilinear interpolation method is used to perform frequency modulation adaptive online parameter search. The specific parameter search steps are as follows: In step 5.1, extract the ′ ≤f(t)≤f″,P ′ ≤P(t)≤P″ and four adjacent points, f ′ and f″ are frequency points, which are f1,…,f n …, f max Two adjacent points in P ′ and P″ are power points, which are P1,…,P s …, P max Two adjacent points in the middle; Step 5.2: Mark the pitch angles corresponding to the four points in step 5.1 as θ from left to right and from top to bottom. 11 ,θ 12 ,θ 21 ,θ 22 ; The bilinear interpolation method is used to calculate the given pitch angle θ of the wind turbine at time t. The calculation formula is as follows:

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