Wind power auxiliary frequency modulation optimization method based on optimal system frequency trajectory

Abstract

The invention provides a wind power auxiliary frequency modulation optimization method based on system frequency trajectory optimization. The method comprises the steps that key operation parameters and frequency modulation parameters of a wind turbine generator and a traditional generator are collected respectively, a small signal analysis method is used for deducing a wind turbine generator power frequency transfer function considering working point deviation, and a system frequency response model containing the wind turbine generator and the traditional generator is established; based on the system frequency response model, constructing a discretized optimal system frequency trajectory optimization model by taking the lowest point of the maximized system frequency as a target function; and solving the discretized optimal system frequency trajectory optimization model by using a commercial solver to obtain an additional frequency modulation power signal, and applying the additional frequency modulation power signal as an additional control signal to virtual inertia control to obtain a system frequency optimal control effect. According to the method, the additional frequency modulation power can be obtained by considering accuracy and efficiency, the advantages of rapidness, flexibility and high plasticity of fan power adjustment are fully utilized, and the system frequency response dynamic characteristic is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine frequency regulation strategies, and in particular to a wind power auxiliary frequency regulation optimization method based on optimal system frequency trajectory. Background Art

[0002] After large-scale wind power access, it is difficult to actively respond to system frequency changes, which significantly weakens the overall inertia level of the power system. Under large power shortage disturbances, low-inertia power systems seriously threaten the frequency stability and safe operation of the power grid. However, wind power generally does not have power reserve, and its frequency regulation capability is restricted by the stored rotor kinetic energy. Therefore, it is urgent to fully tap the frequency regulation potential of wind turbines, coordinate with traditional units, and improve the system frequency response characteristics.

[0003] The wind power frequency regulation methods in the prior art designed according to the established active power function include: virtual inertia control, step inertia control and inertia control based on limit torque. When there is an active load shortage, the above wind power frequency regulation method designs different forms of wind turbine active power reference trajectories by adjusting relevant parameters to provide active support for the power system, which is convenient for implementation and deployment. However, unreasonable control parameter optimization and active reference trajectory design not only limit the frequency regulation capability of wind turbines, but also may cause the rotor speed of wind turbines to be too low, causing the unit to exit frequency regulation, resulting in a secondary drop in frequency, and even affecting the operating stability of the unit.

[0004] At present, the improvement methods for traditional wind power frequency control in the existing technology can be divided into two categories: one is to improve on the basis of the traditional wind power frequency regulation method, based on the differentiated demand for wind power virtual inertia in different intervals of system frequency response, and use fuzzy control algorithm to adaptively adjust the comprehensive inertia control parameters, reasonably optimize the support active power distribution, and promote the rapid restoration of system frequency. The shortcomings of this method include: it does not give full play to the frequency support capacity of wind turbines.

[0005] The second is a control method based on the optimal system frequency trajectory, which solves the optimal output of wind turbines in the time domain based on the particle swarm algorithm. The shortcomings of this method include: the method does not start from the traditional virtual inertia control idea, take into account the accuracy and efficiency of solving the optimal output, and improve the dynamic characteristics of the system frequency response. Summary of the invention

[0006] The embodiment of the present invention provides a wind power assisted frequency regulation optimization method based on the optimal system frequency trajectory, so as to improve the frequency security guarantee capability of the power system and ensure the economic operation efficiency of the wind turbine generator set.

[0007] In order to achieve the above object, the present invention adopts the following technical scheme.

[0008] According to one aspect of the present invention, a wind power assisted frequency regulation optimization method based on optimal system frequency trajectory is provided, comprising:

[0009] The key operating parameters and frequency modulation parameters of wind turbines and traditional units as well as the disturbance size are collected respectively, and the power-frequency transfer function of the wind turbines taking into account the working point offset is derived using the small signal analysis method. Based on the power-frequency transfer function of the wind turbines and the frequency response model of the traditional units, a system frequency response model including both wind turbines and traditional units is established;

[0010] Based on the system frequency response model, maximizing the lowest point of the system frequency is taken as the objective function, and the additional frequency modulation power is taken as the decision variable. A discretized optimal system frequency trajectory optimization model is constructed by using the first-order forward Euler difference method.

[0011] The discretized optimal system frequency trajectory optimization model is solved by a commercial solver to obtain an additional frequency-modulated power signal, and the additional frequency-modulated power signal is applied as an additional control signal to virtual inertia control to obtain an optimal control effect of the system frequency.

[0012] Preferably, the key operating parameters and frequency modulation parameters of the wind turbine generator set and the traditional turbine generator set as well as the disturbance size are collected respectively, and the power-frequency transfer function of the wind turbine generator set taking into account the working point offset is derived by using a small signal analysis method. According to the power-frequency transfer function of the wind turbine generator set and the frequency response model of the traditional turbine generator set, a system frequency response model including both the wind turbine generator set and the traditional turbine generator set is established, including:

[0013] Acquire the operating parameters of the wind turbine generator set, and according to the operating parameters, acquire the mechanical power captured by the wind turbine generator set under a given wind speed scenario and the active power output by the wind turbine generator set under a maximum power point tracking working mode, and establish the motion equation expression of the wind turbine generator set rotor and the power-frequency transfer function of the wind turbine generator set taking into account the working point offset;

[0014] Obtain the frequency modulation parameters of the traditional unit and establish the frequency response transfer function expression of the traditional unit;

[0015] The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency change, and the output after calculation is the output increment of the traditional turbine when the frequency is modulated; the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation, and the output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment based on the total capacity of the traditional turbine; the input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation.

[0016] Preferably, the key operating parameters and frequency modulation parameters of the wind turbine generator set and the traditional turbine generator set as well as the disturbance size are collected respectively, and the power-frequency transfer function of the wind turbine generator set taking into account the working point offset is derived by using a small signal analysis method. According to the power-frequency transfer function of the wind turbine generator set and the frequency response model of the traditional turbine generator set, a system frequency response model including both the wind turbine generator set and the traditional turbine generator set is established, including:

[0017] Acquire the operating parameters of the wind turbine generator set, and acquire the mechanical power captured by the wind turbine generator set under a given wind speed scenario according to the operating parameters; wm for:

[0018]

[0019] Where: ρ, R, v are air density, wind wheel radius and wind speed respectively; β, ω r and C p They are pitch angle, wind turbine rotor speed and wind energy utilization coefficient respectively;

[0020] The active power P output by the wind turbine in the maximum power point tracking mode we for:

[0021]

[0022] Where: opt , C pmax and k opt They are respectively the optimal tip speed ratio, the maximum wind energy utilization coefficient and the optimal power coefficient under a certain wind speed, and they are generally taken as fixed values ​​under rated wind speed;

[0023] P wm is nonlinear, P wm The expression is fitted to a quadratic polynomial with rotational speed:

[0024]

[0025] Where: a, b, c are fitting coefficients;

[0026] Based on the small signal analysis method, the mechanical power variation ΔP captured by the wind turbine wm It is expressed as:

[0027] ΔP wm =(2aω r0 +b)Δω r =k m Δω r (4)

[0028] Where: r0 is the initial value of the wind turbine rotor speed; Δω r Indicates the change in wind turbine rotor speed; k mTo capture the coefficient of mechanical power variation;

[0029] P we It is nonlinear. Based on the small signal analysis method, the change in active power output by the wind turbine is ΔP we for:

[0030]

[0031] Where: k t is the output active power variation coefficient, and the additional frequency modulation power is recorded as ΔP add ;

[0032] The motion equation of the wind turbine rotor is expressed as:

[0033]

[0034] Where: H w is the inertia time constant of the wind turbine rotor;

[0035] In summary, the power-frequency transfer function of the wind turbine taking into account the working point offset is:

[0036]

[0037] Where ΔP we1 (s) is the output power increment of the wind turbine when participating in frequency regulation; s is the Laplace operator;

[0038] Obtain the frequency modulation parameters of the traditional unit. The frequency response transfer function expression of the traditional unit is:

[0039]

[0040] In the formula, F H 、T R 、T ch 、T g and R are respectively the work ratio of the high-pressure cylinder of the turbine, the time constant of the reheater, the volume effect constant of the turbine, the time constant of the governor and the adjustment coefficient; ΔP SG (s) is the output increment of the traditional unit during frequency regulation; Δf(s) is the system frequency change;

[0041] The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency variation, and the output is the output increment of the traditional turbine frequency modulation after calculation by formula (8); the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation by formula (7). The output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment ΔP based on the total capacity of the traditional turbine. we (s); The input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation, H sys and D sys is the system inertia time constant and damping coefficient; ΔP L and η are the system power disturbance and wind power penetration rate respectively, and the benchmark value is the total capacity of traditional units.

[0042] Preferably, based on the system frequency response model, maximizing the lowest point of the system frequency is used as the objective function, the additional frequency modulation power is used as the decision variable, and a first-order forward Euler difference method is used to construct a discretized optimal system frequency trajectory optimization model, including:

[0043] The decision variable is set as the additional frequency modulation power, and the objective function is to maximize the lowest point of the system frequency. The dynamic equation of the system frequency response is established, and the unit output limit and safe and stable operation constraints and wind turbine unit operation state constraints are set.

[0044] The expressions of system frequency dynamic constraints, traditional unit frequency response dynamic constraints and wind turbine frequency response dynamics are established. Based on the expressions of the above constraints, a discretized optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is constructed based on the first-order forward Euler difference.

[0045] Preferably, based on the system frequency response model, maximizing the lowest point of the system frequency is used as the objective function, and the additional frequency modulation power is used as the decision variable. A first-order forward Euler difference method is used to construct a discretized optimal system frequency trajectory optimization model, including:

[0046] Set the decision variable to be the additional frequency modulation power ΔP add , set the optimization goal to maximize the lowest point of system frequency Δf(t):

[0047]

[0048] The system frequency response dynamic equation is:

[0049]

[0050] The unit output limit and safe and stable operation constraints are as follows:

[0051]

[0052] Where ΔP SG,min and ΔP SG,max They are the minimum and maximum permissible values ​​of output increment when the conventional unit is frequency modulated; ΔP we1,min and ΔP we1,max They are the minimum and maximum permissible values ​​of the output power increment when the wind turbine participates in frequency regulation; ω rmin and ω rmax They are the minimum and maximum permissible values ​​of the wind turbine rotor speed respectively;

[0053] The operating state constraints of wind turbines are as follows:

[0054]

[0055] Where, t st and t end They represent the frequency modulation start time and speed recovery end time respectively;

[0056] The optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is expressed as:

[0057]

[0058] Based on the first-order forward Euler difference, a discretized optimal system frequency trajectory optimization model is constructed;

[0059] The differential expression of the system frequency dynamic constraint (10) is:

[0060]

[0061] In the formula, the subscript i indicates the corresponding i-th variable, and n indicates the total number of variables, which depends on t st ,t end and the difference step length Δt;

[0062] The differential expression of the traditional unit frequency response dynamic constraint (8) is:

[0063]

[0064] Where: ΔP SG,1,i , ΔP SG,2,i , ΔP SG,3,i , ΔP SG,4,i , ΔP SG,5,i , ΔP SG,i and Δf i It is the intermediate variable added after the power-frequency transfer function of the traditional unit is differentiated;

[0065] The differential expression of the wind turbine frequency response dynamic constraint (7) is:

[0066]

[0067] In the formula, ΔP we1,1,i , ΔP we1,2,i , ΔP we1,i , ΔP add,i and Δω r,i It is the intermediate variable added after the power-frequency transfer function of the wind turbine is differentiated;

[0068] The discrete optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is expressed as:

[0069]

[0070] Preferably, the method of using a commercial solver to solve the discretized optimal system frequency trajectory optimization model to obtain an additional frequency modulation power signal, and applying the additional frequency modulation power signal as an additional control signal to virtual inertia control to obtain the optimal control effect of the system frequency includes:

[0071] A discrete optimal system frequency trajectory optimization model including auxiliary frequency modulation of wind turbines is constructed in MATLAB, and the commercial solver GUROBI is used to solve the discrete optimal system frequency trajectory optimization model. The GUROBI solver outputs the optimal solution of the discrete optimal system frequency trajectory optimization model, and the optimal solution includes the optimal system frequency trajectory and an additional frequency modulation power signal, wherein the additional frequency modulation power signal is a set of discrete sequences that vary with time, and the power value at each discrete moment represents the optimal additional frequency modulation power of the system at the corresponding moment;

[0072] The additional frequency modulation power signal is used as an additional control signal and introduced into the virtual inertia control of the outer loop power of the actual wind turbine generator set. When a load disturbance occurs, the additional frequency modulation power signal takes effect and the wind turbine generator set increases its output.

[0073] The additional frequency modulated power signal ΔP add As a virtual inertia signal, it is added to the original active power reference signal of the wind turbine. we_ref , when a load disturbance occurs, the active power reference signal is updated to P we_ref +P add , the wind turbine adjusts its actual power output active power according to the new reference value, and cooperates with the output of the traditional unit to maximize the lowest point of the system frequency;

[0074] When the additional frequency modulated power signal ΔP add When it changes to 0, the wind turbine will automatically exit the frequency regulation mode and enter the normal operation mode.

[0075] According to another aspect of the present invention, a wind power assisted frequency regulation optimization device based on optimal system frequency trajectory is provided, comprising:

[0076] The system frequency response model building module is used to collect the key operating parameters and frequency regulation parameters of wind turbines and traditional units, as well as the disturbance size, and use the small signal analysis method to derive the power-frequency transfer function of the wind turbine taking into account the working point offset. According to the power-frequency transfer function of the wind turbine and the frequency response model of the traditional unit, a system frequency response model including both wind turbines and traditional units is established;

[0077] An optimal system frequency trajectory optimization model construction module is used to construct a discretized optimal system frequency trajectory optimization model based on the system frequency response model, taking maximizing the lowest point of the system frequency as the objective function and the additional frequency modulation power as the decision variable, using a first-order forward Euler difference method;

[0078] The system frequency optimal control module is used to solve the discretized optimal system frequency trajectory optimization model using a commercial solver to obtain an additional frequency-modulated power signal, and apply the additional frequency-modulated power signal as an additional control signal to the virtual inertia control to obtain the system frequency optimal control effect.

[0079] Preferably, the system frequency response model building module is used to obtain the operating parameters of the wind turbine generator set, obtain the mechanical power captured by the wind turbine generator set under a given wind speed scenario and the active power output by the wind turbine generator set under the maximum power point tracking working mode according to the operating parameters, and establish the motion equation expression of the wind turbine generator set rotor and the power-frequency transfer function of the wind turbine generator set taking into account the working point offset;

[0080] Obtain the frequency modulation parameters of the traditional unit and establish the frequency response transfer function expression of the traditional unit;

[0081] The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency change, and the output after calculation is the output increment of the traditional turbine when the frequency is modulated; the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation, and the output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment based on the total capacity of the traditional turbine; the input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation.

[0082] Preferably, the optimal system frequency trajectory optimization model building module is used to set the decision variable as the additional frequency modulation power, take maximizing the lowest point of the system frequency as the objective function, establish the system frequency response dynamic equation, set the unit output limit and safe and stable operation constraints and wind turbine unit operation state constraints;

[0083] The expressions of system frequency dynamic constraints, traditional unit frequency response dynamic constraints and wind turbine frequency response dynamics are established. Based on the expressions of the above constraints, a discretized optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is constructed based on the first-order forward Euler difference.

[0084] Preferably, the system frequency optimal control module is used to construct a discretized optimal system frequency trajectory optimization model including auxiliary frequency modulation of wind turbines in MATLAB, and use the commercial solver GUROBI to solve the discretized optimal system frequency trajectory optimization model. The GUROBI solver outputs the optimal solution of the discretized optimal system frequency trajectory optimization model, and the optimal solution includes the optimal system frequency trajectory and the additional frequency modulation power signal, wherein the additional frequency modulation power signal is a set of discrete sequences that vary with time, and the power value at each discrete moment represents the optimal additional frequency modulation power of the system at the corresponding moment;

[0085] The additional frequency modulation power signal is used as an additional control signal and introduced into the virtual inertia control of the outer loop power of the actual wind turbine generator set. When a load disturbance occurs, the additional frequency modulation power signal takes effect and the wind turbine generator set increases its output.

[0086] The additional frequency modulated power signal ΔP add As a virtual inertia signal, it is added to the original active power reference signal of the wind turbine. we_ref , when a load disturbance occurs, the active power reference signal is updated to P we_ref +P add , the wind turbine adjusts its actual power output active power according to the new reference value, and cooperates with the output of the traditional unit to maximize the lowest point of the system frequency;

[0087] When the additional frequency modulated power signal ΔP add When the frequency changes to 0, the wind turbine sets will actively exit the frequency modulation and enter the normal operation mode. It can be seen from the technical solutions provided by the above embodiments of the present invention that the wind power auxiliary frequency modulation optimization method based on the optimal system frequency trajectory provided by the present invention can take into account both accuracy and efficiency to obtain additional frequency modulation power, and make full use of the advantages of fast, flexible and strong plasticity of wind turbine power regulation to effectively improve the dynamic characteristics of system frequency response. At the same time, the advantages of traditional virtual inertia control are brought into play, avoiding the additional design of different operating mode triggering and switching mechanisms, and being easy to deploy and implement.

[0088] Additional aspects and advantages of the present invention will be given in part in the following description, which will become obvious from the following description, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0090] Figure 1 A flow chart of a method for optimizing wind power-assisted frequency regulation based on optimal system frequency trajectory provided by an embodiment of the present invention;

[0091] Figure 2 A schematic diagram of a system frequency response model including a wind turbine generator system provided in an embodiment of the present invention;

[0092] Figure 3 A schematic diagram of the working principle of an actual doubly-fed wind turbine generator set with virtual inertia provided in an embodiment of the present invention;

[0093] Figure 4 A schematic diagram of a simulation result provided by an embodiment of the present invention;

[0094] Figure 5 A structural diagram of a wind power assisted frequency regulation optimization device based on optimal system frequency trajectory provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0095] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0096] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or coupling. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0097] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0098] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0099] Example 1

[0100] A flow chart of a wind power assisted frequency regulation optimization method based on optimal system frequency trajectory provided by an embodiment of the present invention is as follows: Figure 1 As shown, the processing steps include the following:

[0101] Step S1: respectively collect key operating parameters and frequency modulation parameters of wind turbines and traditional units as well as disturbance magnitude, wherein the traditional unit in the present invention refers to a traditional steam turbine unit. Use a small signal analysis method to derive a wind turbine power-frequency transfer function taking into account the working point offset, and establish a system frequency response model including both wind turbines and traditional units based on the wind turbine power-frequency transfer function and the traditional unit frequency response model.

[0102] Step S2: Based on the above system frequency response model, with maximizing the lowest point of the system frequency as the objective function and the additional frequency modulation power as the decision variable, a discretized optimal system frequency trajectory optimization model is constructed using the first-order forward Euler difference method.

[0103] Step S3: Use a commercial solver to solve the above discretized optimal system frequency trajectory optimization model to obtain an additional frequency-modulated power signal, and apply the additional frequency-modulated power signal as an additional control signal to the virtual inertia control to obtain the optimal control effect of the system frequency.

[0104] Specifically, the above step S1 includes: respectively collecting key operating parameters and frequency modulation parameters of wind turbines and traditional turbines and the size of disturbances, deriving the power-frequency transfer function of the wind turbine taking into account the working point offset by using a small signal analysis method, and establishing a system frequency response model including the wind turbine by integrating the frequency response model of the traditional turbine; this step includes the following steps:

[0105] Obtain key operating parameters of wind turbines.

[0106] Under a given wind speed scenario, the wind turbine captures mechanical power P wm The expression is:

[0107]

[0108] Where: ρ, R, v are air density, wind wheel radius and wind speed respectively; β, ω r and C p They are pitch angle, wind turbine rotor speed and wind energy utilization coefficient respectively.

[0109] Output active power P under maximum power point tracking working mode we The expression is:

[0110]

[0111] Where: opt , C pmax and k opt They are respectively the optimal tip speed ratio, maximum wind energy utilization coefficient and optimal power coefficient under a certain wind speed, and are generally taken as fixed values ​​under rated wind speed.

[0112] P wm is nonlinear, P wm The expression is fitted to a quadratic polynomial with rotational speed:

[0113]

[0114] Where: a, b, c are fitting coefficients.

[0115] Based on the small signal analysis method, the wind turbine captures the mechanical power change ΔP wm It can be expressed as:

[0116] ΔP wm =(2aω r0 +b)Δω r =k mΔω r (4)

[0117] Where: r0 is the initial value of the wind turbine rotor speed; Δω r Indicates the change in wind turbine rotor speed; k m To capture the coefficient of mechanical power variation.

[0118] P we It is nonlinear. Based on the small signal analysis method, the output active power change ΔP we for:

[0119]

[0120] Where: k t is the output active power variation coefficient.

[0121] The additional frequency modulation power is recorded as ΔP add .

[0122] The wind turbine rotor motion equation is expressed as:

[0123]

[0124] Where: H w is the wind turbine rotor inertia time constant.

[0125] In summary, the power-frequency transfer function of the wind turbine taking into account the working point offset can be obtained:

[0126]

[0127] In the formula, ΔP we1 (s) is the output power increment of the wind turbine when it participates in frequency regulation; s is the Laplace operator.

[0128] Get the frequency modulation parameters of the traditional unit, the frequency response transfer function expression of the traditional unit:

[0129]

[0130] In the formula, F H , T R , T ch , T g and R are respectively the work ratio of the high-pressure cylinder of the turbine, the time constant of the reheater, the volume effect constant of the turbine, the time constant of the governor and the adjustment coefficient; ΔP SG (s) is the output increment of the traditional unit during frequency regulation; Δf(s) is the system frequency change.

[0131] Obtain the disturbance size and construct a system frequency response model that includes both wind turbines and traditional turbines. Figure 2 shown. Figure 2 In the above, the system frequency response model consists of three modules, namely: module 1—traditional unit frequency regulation module, module 2—wind turbine frequency regulation module, and module 3—rotor dynamics module. Among them, the input of module 1 is the system frequency change, and the output is the output increment of the traditional unit frequency regulation after formula (8); the output of module 2 is the output power increment when the wind turbine participates in frequency regulation after formula (7). The output of module 2 is converted by the system penetration rate to obtain the wind turbine output power increment ΔP based on the total capacity of the traditional unit. we (s); Module 3 inputs the system power difference, and outputs the system frequency change through the system rotor motion equation. sys and D sys is the system inertia time constant and damping coefficient; ΔP L and η are system power disturbance and wind power penetration rate respectively, and the benchmark value is the total capacity of traditional units.

[0132] Specifically, the above step S2 includes: based on the system frequency response model including the wind turbine generator set, taking maximizing the lowest point of the system frequency as the objective function and the additional frequency modulation power as the decision variable, using the first-order forward Euler difference method to construct a discretized optimal system frequency trajectory optimization model; this step may include the following steps:

[0133] The decision variable is the additional frequency modulation power ΔP add , the optimization goal is to maximize the lowest point of system frequency Δf(t):

[0134]

[0135] The system frequency response dynamic equation is:

[0136] ΔP L (s)-ΔP SG (s)-ΔP we1 (s)=2H sys sΔf(s)+D sys Δf(s)(10)

[0137] The unit output limit and safe and stable operation constraints are as follows:

[0138]

[0139] Where ΔP SG,min and ΔP SG,max They are the minimum and maximum permissible values ​​of output increment when the conventional unit is frequency modulated; ΔP we1,min and ΔP we1,max They are the minimum and maximum permissible values ​​of the output power increment when the wind turbine participates in frequency regulation; ω rmin and ω rmaxThey are the minimum and maximum allowable values ​​of the wind turbine rotor speed respectively.

[0140] The operating state constraints of wind turbines are as follows:

[0141]

[0142] In the formula, t st and t end They respectively represent the start time of frequency modulation and the end time of speed recovery.

[0143] The optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation can be expressed as follows:

[0144]

[0145] Based on the first-order forward Euler difference, a discretized optimal system frequency trajectory optimization model is constructed.

[0146] The differential expression of the system frequency dynamic constraint (10) is:

[0147]

[0148] In the formula, the subscript i indicates the corresponding i-th variable, and n indicates the total number of variables, which depends on t st ,t end and the difference step size Δt.

[0149] The differential expression of the traditional unit frequency response dynamic constraint (8) is:

[0150]

[0151] Where: ΔP SG,1,i , ΔP SG,2,i , ΔP SG,3,i , ΔP SG,4,i , ΔP SG,5,i , ΔP SG,i and Δf i It is an intermediate variable added after the power-frequency transfer function of the traditional unit is differentiated.

[0152] The differential expression of the wind turbine frequency response dynamic constraint (7) is:

[0153]

[0154] In the formula, ΔP we1,1,i , ΔP we1,2,i , ΔP we1,i , ΔP add,i and Δω r,i It is the intermediate variable added after the power-frequency transfer function of the wind turbine is differentiated.

[0155] The discrete optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation can be expressed as follows:

[0156]

[0157] Specifically, the above step S3 includes: based on the discretized optimal system frequency trajectory optimization model, an integer linear programming model is directly solved using a commercial solver to obtain an additional frequency modulation power trajectory, and the additional frequency modulation power trajectory is applied to the virtual inertia control as an additional control signal, thereby achieving the desired system frequency optimal control effect; this step may include the following steps:

[0158] A discrete optimal system frequency trajectory optimization model including auxiliary frequency modulation of wind turbines is constructed in MATLAB. The commercial solver GUROBI is used to solve the discrete optimal system frequency trajectory optimization model to obtain the additional frequency modulation power signal.

[0159] In the process of using the GUROBI solver to solve the discretized optimal system frequency trajectory optimization model, the specific processing steps are as follows:

[0160] Firstly, the discretized optimal system frequency trajectory optimization model (including objective function and constraints) is converted into a form that can be recognized and processed by MATLAB and solver and input into MATLAB;

[0161] Secondly, configure the solver interface. Since MATLAB provides an interface with commercial solvers, select the GUROBI solver in MATLAB and set the relevant parameters of the GUROBI solver, including the number of iterations, time limit, convergence accuracy, etc.

[0162] Then the GUROBI solver is called to solve the problem. The GUROBI solver uses the built-in optimization algorithm to iteratively solve the discretized optimal system frequency trajectory optimization model and gradually approaches the optimal solution. During the solution process, the GUROBI solver will automatically select or adjust the optimization method according to the objective function and constraints until the optimal solution is found.

[0163] Finally, the GUROBI solver outputs the optimal solution, which includes the optimal system frequency trajectory and the additional frequency modulation power signal, where the additional frequency modulation power signal is a set of discrete sequences that vary with time, and the power value at each discrete moment represents the optimal additional frequency modulation power of the system at the corresponding moment.

[0164] Example 2

[0165] The embodiment of the present invention provides a structure diagram of a wind power auxiliary frequency regulation optimization device based on the optimal system frequency trajectory. Figure 5 As shown, it includes the following modules:

[0166] The system frequency response model building module 51 is used to respectively collect the key operating parameters and frequency modulation parameters of the wind turbine and the traditional unit as well as the disturbance size, derive the power-frequency transfer function of the wind turbine taking into account the working point offset by using the small signal analysis method, and establish a system frequency response model including both the wind turbine and the traditional unit according to the power-frequency transfer function of the wind turbine and the frequency response model of the traditional unit;

[0167] An optimal system frequency trajectory optimization model building module 52 is used to build a discretized optimal system frequency trajectory optimization model based on the system frequency response model, taking maximizing the lowest point of the system frequency as the objective function and the additional frequency modulation power as the decision variable by using a first-order forward Euler difference method;

[0168] The system frequency optimal control module 53 is used to use a commercial solver to solve the discretized optimal system frequency trajectory optimization model to obtain an additional frequency-modulated power signal, and apply the additional frequency-modulated power signal as an additional control signal to the virtual inertia control to obtain the system frequency optimal control effect.

[0169] Preferably, the system frequency response model building module 51 is used to obtain the operating parameters of the wind turbine generator set, and obtain the mechanical power captured by the wind turbine generator set under a given wind speed scenario according to the operating parameters; wm for:

[0170]

[0171] Where: ρ, R, v are air density, wind wheel radius and wind speed respectively; β, ω r and C p They are pitch angle, wind turbine rotor speed and wind energy utilization coefficient respectively;

[0172] The active power P output by the wind turbine in the maximum power point tracking mode we for:

[0173]

[0174] Where: opt , C pmax and k opt They are respectively the optimal tip speed ratio, the maximum wind energy utilization coefficient and the optimal power coefficient under a certain wind speed, and they are generally taken as fixed values ​​under rated wind speed;

[0175] P wm is nonlinear, P wm The expression is fitted to a quadratic polynomial with rotational speed:

[0176]

[0177] Where: a, b, c are fitting coefficients;

[0178] Based on the small signal analysis method, the mechanical power variation ΔP captured by the wind turbine wm It is expressed as:

[0179] ΔP wm =(2aω r0 +b)Δω r =k m Δω r (4)

[0180] Where: r0 is the initial value of the wind turbine rotor speed; Δω r Indicates the change in wind turbine rotor speed; k m To capture the coefficient of mechanical power variation;

[0181] P we It is nonlinear. Based on the small signal analysis method, the change in active power output by the wind turbine is ΔP we for:

[0182]

[0183] Where: k t is the output active power variation coefficient, and the additional frequency modulation power is recorded as ΔP add ;

[0184] The motion equation of the wind turbine rotor is expressed as:

[0185]

[0186] Where: H w is the inertia time constant of the wind turbine rotor;

[0187] In summary, the power-frequency transfer function of the wind turbine taking into account the working point offset is:

[0188]

[0189] In the formula, ΔP we1 (s) is the output power increment of the wind turbine when participating in frequency regulation; s is the Laplace operator;

[0190] Obtain the frequency modulation parameters of the traditional unit. The frequency response transfer function expression of the traditional unit is:

[0191]

[0192] In the formula, F H , T R , T ch , T gand R are respectively the work ratio of the high-pressure cylinder of the turbine, the time constant of the reheater, the volume effect constant of the turbine, the time constant of the governor and the adjustment coefficient; ΔP SG (s) is the output increment of the traditional unit during frequency regulation; Δf(s) is the system frequency change;

[0193] The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency variation, and the output is the output increment of the traditional turbine frequency modulation after calculation by formula (8); the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation by formula (7). The output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment ΔP based on the total capacity of the traditional turbine. we (s); The input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation, H sys and D sys is the system inertia time constant and damping coefficient; ΔP L and η are the system power disturbance and wind power penetration rate respectively, and the benchmark value is the total capacity of traditional units.

[0194] The optimal system frequency trajectory optimization model building module 52 is used to set the decision variable to the additional frequency modulation power ΔP add , set the optimization goal to maximize the lowest point of system frequency Δf(t):

[0195]

[0196] The system frequency response dynamic equation is:

[0197]

[0198] The unit output limit and safe and stable operation constraints are as follows:

[0199]

[0200] Where ΔP SG,min and ΔP SG,max They are the minimum and maximum permissible values ​​of output increment when the conventional unit is frequency modulated; ΔP we1,min and ΔP we1,max They are the minimum and maximum permissible values ​​of the output power increment when the wind turbine participates in frequency regulation; ω rmin and ω rmax They are the minimum and maximum permissible values ​​of the wind turbine rotor speed respectively;

[0201] The operating state constraints of wind turbines are as follows:

[0202]

[0203] Where, t st and t end They represent the frequency modulation start time and speed recovery end time respectively;

[0204] The optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is expressed as:

[0205]

[0206] Based on the first-order forward Euler difference, a discretized optimal system frequency trajectory optimization model is constructed;

[0207] The differential expression of the system frequency dynamic constraint (10) is:

[0208]

[0209] In the formula, the subscript i indicates the corresponding i-th variable, and n indicates the total number of variables, which depends on t st ,t end and the difference step length Δt;

[0210] The differential expression of the traditional unit frequency response dynamic constraint (8) is:

[0211]

[0212] Where: ΔP SG,1,i , ΔP SG,2,i , ΔP SG,3,i , ΔP SG,4,i , ΔP SG,5,i , ΔP SG,i and Δf i It is the intermediate variable added after the power-frequency transfer function of the traditional unit is differentiated;

[0213] The differential expression of the wind turbine frequency response dynamic constraint (7) is:

[0214]

[0215] Where ΔP we1,1,i , ΔP we1,2,i , ΔP we1,i , ΔP add,i and Δω r,i It is the intermediate variable added after the power-frequency transfer function of the wind turbine is differentiated;

[0216] The discrete optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is expressed as:

[0217]

[0218] The system frequency optimal control module 53 is used to construct a discretized optimal system frequency trajectory optimization model including auxiliary frequency modulation of wind turbines in MATLAB, and solve the discretized optimal system frequency trajectory optimization model using the commercial solver GUROBI. The GUROBI solver outputs the optimal solution of the discretized optimal system frequency trajectory optimization model, and the optimal solution includes the optimal system frequency trajectory and the additional frequency modulation power signal, wherein the additional frequency modulation power signal is a set of discrete sequences that vary with time, and the power value at each discrete moment represents the optimal additional frequency modulation power of the system at the corresponding moment;

[0219] The additional frequency modulation power signal is used as an additional control signal and introduced into the virtual inertia control of the outer loop power of the actual wind turbine generator set. When a load disturbance occurs, the additional frequency modulation power signal takes effect and the wind turbine generator set increases its output.

[0220] The additional frequency modulated power signal ΔP add As a virtual inertia signal, it is added to the original active power reference signal of the wind turbine. we_ref , when a load disturbance occurs, the active power reference signal is updated to P we_ref +P add , the wind turbine adjusts its actual power output active power according to the new reference value, and cooperates with the output of the traditional unit to maximize the lowest point of the system frequency;

[0221] When the additional frequency modulated power signal ΔP add When it changes to 0, the wind turbine will automatically exit the frequency regulation mode and enter the normal operation mode.

[0222] The specific process of using the device of the embodiment of the present invention to perform wind power assisted frequency regulation optimization based on the optimal system frequency trajectory is similar to the aforementioned method embodiment, and will not be repeated here.

[0223] Example 3

[0224] A schematic diagram of the working principle of an actual double-fed wind turbine generator set with virtual inertia provided by an embodiment of the present invention is shown in FIG. Figure 3 As shown. The additional frequency modulation power signal obtained above is introduced into Figure 3 In the actual wind turbine outer loop power control shown (taking a doubly-fed generator set as an example), when a load disturbance occurs, the additional frequency modulation power signal takes effect, the wind turbine increases its output, and improves frequency support for the power system. Figure 3In the figure, Qe is the reactive power output by the wind turbine; Qref is the reference value of the reactive power output by the wind turbine; Pwe_ref is the reference value of the active power output under the maximum power point tracking working mode; idr_ref, iqr_ref, idr, iqr are the reference value of the rotor d-axis current, the reference value of the rotor q-axis current, the rotor d-axis current and the rotor q-axis current respectively; vdr and iqr are the rotor d-axis voltage and the rotor q-axis voltage respectively; Lr, Lm and Ls are the rotor reactance, the mutual reactance between the stator and rotor windings and the stator reactance respectively; PI represents the proportional-integral controller.

[0225] When load disturbance occurs, the balance of system active power is broken and the system frequency deviates. In order to reduce the system frequency deviation, the output power of wind turbines needs to be adjusted to support the stability of system frequency. The additional frequency modulation power signal (i.e., ΔP add ) is added as a virtual inertia signal to the original active power reference signal of the wind turbine generator set P we_ref , at this time the active power reference signal is updated to P we_ref +P add , the wind turbine adjusts its actual power output active power according to the new reference value, thereby cooperating with the output of the traditional unit to maximize the lowest point of the system frequency and achieve a frequency control effect that is basically consistent with the optimal system frequency trajectory obtained by solving the optimization model.

[0226] When the additional frequency modulation power signal changes to 0, the wind turbine actively exits the frequency modulation and enters the normal operation mode. There is no need to detect the frequency modulation exit signal in real time, which avoids the additional design of different operation mode triggering and switching mechanisms, and is easy to deploy and implement.

[0227] In order to illustrate the effectiveness of the discretized optimal system frequency trajectory optimization model, a four-machine two-region simulation model was built on the MATLAB / Simulink simulation platform. Based on the standard model, the simulation model replaces one of the traditional units with a wind farm consisting of 450 1.5MW wind turbines. The total installed capacity of the traditional units is 2700MW, and the wind power penetration rate is 20%. Under the rated wind speed scenario, a 0.1pu active power shortage disturbance occurs at 5s. The additional frequency modulation power signal obtained by the optimal system frequency trajectory optimization model is applied to the detailed time domain model, and a comparative analysis is performed from three aspects: system frequency, wind turbine output and rotor speed.

[0228] A simulation result provided by an embodiment of the present invention is as follows Figure 4 As shown, the system frequency trajectory ( Figure 4 -a) Wind turbine rotor speed ( Figure 4 -c) and its output power ( Figure 4-d) is basically consistent with the detailed model, in which the lowest point of the system frequency is 49.70Hz. During the wind power frequency support process, the unit support power first increases for a short time and then gradually decreases to promote the recovery of the rotor speed. During this period, the lowest point of the system frequency remains unchanged. Figure 4 -b) is gradually reduced to 0, ensuring the smooth transition of the wind turbine from the frequency regulation mode to the normal operation mode, during which no secondary unbalanced active power shortage occurs.

[0229] In summary, the wind power auxiliary frequency regulation optimization method based on the optimal system frequency trajectory in the embodiment of the present invention takes into account the accuracy and efficiency of solving the additional frequency regulation power, while giving full play to the advantages of traditional virtual inertia control, avoiding the additional design of different operation mode triggering and switching mechanisms, and is easy to deploy and implement. It also gives full play to the frequency regulation potential of wind turbines, makes the system frequency present the optimal form, and effectively improves the system frequency response characteristics.

[0230] The present invention can take into account the advantages of traditional virtual inertia control at the same time, that is, there is no need to additionally design the triggering and switching mechanism of the two modes of optimal control and normal operation. The method of the present invention fully utilizes the frequency regulation potential of the unit, improves the dynamic response characteristics of the system frequency, and takes into account the accuracy and efficiency of solving the optimal output, which is of great significance for the reasonable guidance of the design of wind power and other new energy frequency control methods.

[0231] The method of the embodiment of the present invention can obtain additional frequency modulation power with both accuracy and efficiency, making full use of the advantages of fast, flexible and strong plasticity of wind turbine power regulation, effectively improving the dynamic additional characteristics of system frequency response. At the same time, it takes advantage of traditional virtual inertia control, avoids additional design of different operating mode triggering and switching mechanisms, and is easy to deploy and implement.

[0232] Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0233] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention or certain parts of the embodiments.

[0234] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0235] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A wind power assisted frequency regulation optimization method based on optimal system frequency trajectory, characterized in that: include: The key operating parameters and frequency modulation parameters of wind turbines and traditional units as well as the disturbance size are collected respectively, and the power-frequency transfer function of the wind turbines taking into account the working point offset is derived using the small signal analysis method. Based on the power-frequency transfer function of the wind turbines and the frequency response model of the traditional units, a system frequency response model including both wind turbines and traditional units is established; Based on the system frequency response model, maximizing the lowest point of the system frequency is taken as the objective function, and the additional frequency modulation power is taken as the decision variable. A discretized optimal system frequency trajectory optimization model is constructed by using the first-order forward Euler difference method. The discretized optimal system frequency trajectory optimization model is solved by a commercial solver to obtain an additional frequency-modulated power signal, and the additional frequency-modulated power signal is applied as an additional control signal to virtual inertia control to obtain an optimal control effect of the system frequency.

2. The method according to claim 1, characterized in that The key operating parameters and frequency modulation parameters of the wind turbine and the traditional unit as well as the disturbance size are collected respectively, and the power-frequency transfer function of the wind turbine taking into account the working point offset is derived by using the small signal analysis method. According to the power-frequency transfer function of the wind turbine and the frequency response model of the traditional unit, a system frequency response model including both the wind turbine and the traditional unit is established, including: Acquire the operating parameters of the wind turbine generator set, and according to the operating parameters, acquire the mechanical power captured by the wind turbine generator set under a given wind speed scenario and the active power output by the wind turbine generator set under a maximum power point tracking working mode, and establish the motion equation expression of the wind turbine generator set rotor and the power-frequency transfer function of the wind turbine generator set taking into account the working point offset; Obtain the frequency modulation parameters of the traditional unit and establish the frequency response transfer function expression of the traditional unit; The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency change, and the output is the output increment of the traditional turbine when the frequency is modulated after calculation; the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation, and the output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment based on the total capacity of the traditional turbine; the input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation.

3. The method according to claim 2, characterized in that The key operating parameters and frequency modulation parameters of the wind turbine and the traditional unit as well as the disturbance size are collected respectively, and the power-frequency transfer function of the wind turbine taking into account the working point offset is derived by using the small signal analysis method. According to the power-frequency transfer function of the wind turbine and the frequency response model of the traditional unit, a system frequency response model including both the wind turbine and the traditional unit is established, including: Acquire the operating parameters of the wind turbine generator set, and acquire the mechanical power captured by the wind turbine generator set under a given wind speed scenario according to the operating parameters; wm for: Where: ρ, R, v are air density, wind wheel radius and wind speed respectively; β, ω r and C p They are pitch angle, wind turbine rotor speed and wind energy utilization coefficient respectively; The active power P output by the wind turbine in the maximum power point tracking mode we for: Where: opt , C pmax and k opt They are respectively the optimal tip speed ratio, the maximum wind energy utilization coefficient and the optimal power coefficient under a certain wind speed, and they are generally taken as fixed values ​​under rated wind speed; P wm is nonlinear, P wm The expression is fitted to a quadratic polynomial with rotational speed: Where: a, b, c are fitting coefficients; Based on the small signal analysis method, the mechanical power variation ΔP captured by the wind turbine wm It is expressed as: ΔP wm =(2aω r0 +b)See r =k m Give r (4) Where: r0 is the initial value of the wind turbine rotor speed; Δω r Indicates the change in wind turbine rotor speed; k m To capture the coefficient of mechanical power variation; P we It is nonlinear. Based on the small signal analysis method, the change in active power output by the wind turbine is ΔP we for: Where: k t is the output active power variation coefficient, and the additional frequency modulation power is recorded as ΔP add ; The motion equation of the wind turbine rotor is expressed as: Where: H w is the inertia time constant of the wind turbine rotor; In summary, the power-frequency transfer function of the wind turbine taking into account the working point offset is: Where ΔP we1 (s) is the output power increment of the wind turbine when participating in frequency regulation; s is the Laplace operator; Obtain the frequency modulation parameters of the traditional unit. The frequency response transfer function expression of the traditional unit is: In the formula, F H , T R , T ch , T g and R are respectively the work ratio of the high-pressure cylinder of the turbine, the time constant of the reheater, the volume effect constant of the turbine, the time constant of the governor and the adjustment coefficient; ΔP SG (s) is the output increment of the traditional unit during frequency regulation; Δf(s) is the system frequency change; The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency variation, and the output is the output increment of the traditional turbine frequency modulation after calculation by formula (8); the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation by formula (7). The output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment ΔP based on the total capacity of the traditional turbine. we (s); The input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation, H sys and D sys is the system inertia time constant and damping coefficient; ΔP L and η are the system power disturbance and wind power penetration rate respectively, and the benchmark value is the total capacity of traditional units.

4. The method according to claim 3, characterized in that Based on the system frequency response model, the objective function is to maximize the lowest point of the system frequency, the additional frequency modulation power is used as the decision variable, and the first-order forward Euler difference method is used to construct a discretized optimal system frequency trajectory optimization model, including: The decision variable is set as the additional frequency modulation power, and the objective function is to maximize the lowest point of the system frequency. The dynamic equation of the system frequency response is established, and the unit output limit and safe and stable operation constraints and wind turbine unit operation state constraints are set. The expressions of system frequency dynamic constraints, traditional unit frequency response dynamic constraints and wind turbine frequency response dynamics are established. Based on the expressions of the above constraints, a discretized optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is constructed based on the first-order forward Euler difference.

5. The method according to claim 4, characterized in that Based on the system frequency response model, the objective function is to maximize the lowest point of the system frequency, the additional frequency modulation power is used as the decision variable, and the first-order forward Euler difference method is used to construct a discretized optimal system frequency trajectory optimization model, including: Set the decision variable to be the additional frequency modulation power ΔP add , set the optimization goal to maximize the lowest point of system frequency Δf(t): The system frequency response dynamic equation is: The unit output limit and safe and stable operation constraints are as follows: Where ΔP SG,min and ΔP SG,max They are the minimum and maximum permissible values ​​of output increment when the traditional unit is frequency modulated; ΔP we1,min and ΔP we1,max They are the minimum and maximum permissible values ​​of the output power increment when the wind turbine participates in frequency regulation; ω rmin and ω rmax They are the minimum and maximum permissible values ​​of the wind turbine rotor speed respectively; The operating state constraints of wind turbines are as follows: Where, t st and t end They represent the frequency modulation start time and speed recovery end time respectively; The optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is expressed as: Based on the first-order forward Euler difference, a discretized optimal system frequency trajectory optimization model is constructed; The differential expression of the system frequency dynamic constraint (10) is: In the formula, the subscript i indicates the corresponding i-th variable, and n indicates the total number of variables, which depends on t st ,t end and the difference step length Δt; The differential expression of the traditional unit frequency response dynamic constraint (8) is: Where: ΔP SG,1,i , ΔP SG,2,i , ΔP SG,3,i , ΔP SG,4,i , ΔP SG,5,i , ΔP SG,i and Δf i It is the intermediate variable added after the power-frequency transfer function of the traditional unit is differentiated; The differential expression of the wind turbine frequency response dynamic constraint (7) is: Where ΔP we1,1,i , ΔP we1,2,i , ΔP we1,i , ΔP add,i and Δω r,i It is the intermediate variable added after the power-frequency transfer function of the wind turbine is differentiated; The discrete optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is expressed as:

6. The method according to claim 5, characterized in that The method of using a commercial solver to solve the discretized optimal system frequency trajectory optimization model to obtain an additional frequency modulation power signal, and applying the additional frequency modulation power signal as an additional control signal to virtual inertia control to obtain the optimal control effect of the system frequency includes: A discrete optimal system frequency trajectory optimization model including auxiliary frequency modulation of wind turbines is constructed in MATLAB, and the commercial solver GUROBI is used to solve the discrete optimal system frequency trajectory optimization model. The GUROBI solver outputs the optimal solution of the discrete optimal system frequency trajectory optimization model, and the optimal solution includes the optimal system frequency trajectory and an additional frequency modulation power signal, wherein the additional frequency modulation power signal is a set of discrete sequences that vary with time, and the power value at each discrete moment represents the optimal additional frequency modulation power of the system at the corresponding moment; The additional frequency modulation power signal is used as an additional control signal and introduced into the virtual inertia control of the outer loop power of the actual wind turbine generator set. When a load disturbance occurs, the additional frequency modulation power signal takes effect and the wind turbine generator set increases its output. The additional frequency modulated power signal ΔP add As a virtual inertia signal, it is added to the original active power reference signal of the wind turbine. we_ref , when a load disturbance occurs, the active power reference signal is updated to P we_ref +P add , the wind turbine adjusts its actual power output active power according to the new reference value, and cooperates with the output of the traditional unit to maximize the lowest point of the system frequency; When the additional frequency modulation power signal ΔP add When it changes to 0, the wind turbine will automatically exit the frequency regulation mode and enter the normal operation mode.

7. A wind power auxiliary frequency regulation optimization device based on the optimal system frequency trajectory, characterized in that: include: The system frequency response model building module is used to collect the key operating parameters and frequency regulation parameters of wind turbines and traditional units, as well as the disturbance size, and use the small signal analysis method to derive the power-frequency transfer function of the wind turbine taking into account the working point offset. According to the power-frequency transfer function of the wind turbine and the frequency response model of the traditional unit, a system frequency response model including both wind turbines and traditional units is established; An optimal system frequency trajectory optimization model construction module is used to construct a discretized optimal system frequency trajectory optimization model based on the system frequency response model, taking maximizing the lowest point of the system frequency as the objective function and the additional frequency modulation power as the decision variable, using a first-order forward Euler difference method; The system frequency optimal control module is used to solve the discretized optimal system frequency trajectory optimization model using a commercial solver to obtain an additional frequency-modulated power signal, and apply the additional frequency-modulated power signal as an additional control signal to the virtual inertia control to obtain the system frequency optimal control effect.

8. The device according to claim 7, characterized in that: The system frequency response model building module is used to obtain the operating parameters of the wind turbine generator set, obtain the mechanical power captured by the wind turbine generator set under a given wind speed scenario and the active power output by the wind turbine generator set under the maximum power point tracking working mode according to the operating parameters, and establish the motion equation expression of the wind turbine generator set rotor and the power-frequency transfer function of the wind turbine generator set taking into account the working point offset; Obtain the frequency modulation parameters of the traditional unit and establish the frequency response transfer function expression of the traditional unit; The disturbance size is obtained, and a system frequency response model including both wind turbines and traditional turbines is constructed. The system frequency response model includes a traditional turbine frequency modulation module, a wind turbine frequency modulation module and a rotor dynamics module. The input of the traditional turbine frequency modulation module is the system frequency change, and the output is the output increment of the traditional turbine when the frequency is modulated after calculation; the wind turbine frequency modulation module outputs the output power increment when the wind turbine participates in frequency modulation after calculation, and the output power increment when the wind turbine participates in frequency modulation is converted by the system penetration rate to obtain the wind turbine output power increment based on the total capacity of the traditional turbine; the input of the rotor dynamics module is the system power difference, and the system frequency change is output through the system rotor motion equation.

9. The device according to claim 8, characterized in that: The optimal system frequency trajectory optimization model building module is used to set the decision variable as the additional frequency modulation power, take maximizing the lowest point of the system frequency as the objective function, establish the system frequency response dynamic equation, set the unit output limit and safe and stable operation constraints and wind turbine unit operation state constraints; The expressions of system frequency dynamic constraints, traditional unit frequency response dynamic constraints and wind turbine frequency response dynamics are established. Based on the expressions of the above constraints, a discretized optimal system frequency trajectory optimization model including wind turbine auxiliary frequency regulation is constructed based on the first-order forward Euler difference.

10. The device according to claim 9, characterized in that: The system frequency optimal control module is used to construct a discretized optimal system frequency trajectory optimization model including auxiliary frequency modulation of wind turbines in MATLAB, and solve the discretized optimal system frequency trajectory optimization model using the commercial solver GUROBI. The GUROBI solver outputs the optimal solution of the discretized optimal system frequency trajectory optimization model, and the optimal solution includes the optimal system frequency trajectory and an additional frequency modulation power signal, wherein the additional frequency modulation power signal is a set of discrete sequences that vary with time, and the power value at each discrete moment represents the optimal additional frequency modulation power of the system at the corresponding moment; The additional frequency modulation power signal is used as an additional control signal and introduced into the virtual inertia control of the outer loop power of the actual wind turbine generator set. When a load disturbance occurs, the additional frequency modulation power signal takes effect and the wind turbine generator set increases its output. The additional frequency modulated power signal ΔP add As a virtual inertia signal, it is added to the original active power reference signal of the wind turbine. we_ref , when a load disturbance occurs, the active power reference signal is updated to P we_ref +P add , the wind turbine adjusts its actual power output active power according to the new reference value, and cooperates with the output of the traditional unit to maximize the lowest point of the system frequency; When the additional frequency modulation power signal ΔP add When it changes to 0, the wind turbine will automatically exit the frequency regulation mode and enter the normal operation mode.

Images