Method and device for consistent frequency control of deep-sea wind farm based on damping signal optimization

Abstract

The present application relates to new energy control technology field, specifically for a kind of far sea wind farm consistency frequency control method and device based on restraint signal optimization, method steps include: obtaining the power system parameter containing wind farm;The wind farm restraint consistency control topology is constructed, and wind farm restraint consistency frequency controller is set for each wind turbine generator, according to the state of wind turbine generator itself, adjacent unit state and restraint signal, the active power reference value of corresponding wind turbine generator is calculated to control the rotor kinetic energy release of wind turbine generator;Frequency security is considered, and the restraint control signal frequency modulation stage length optimization problem is constructed, and the optimization problem is solved, and the optimal restraint signal is obtained compared with prior art, the present application considers the wind speed distribution difference of offshore wind farm, realizes the frequency modulation state consistency of wind farm internal unit, effectively reduces frequency secondary drop, improves frequency support effect, and has important significance to the power system frequency security containing offshore wind farm.

Description

Technical Field

[0001] This invention relates to the field of new energy control technology, and in particular to a method for consistent frequency control of deep-sea wind farm distribution based on traction signal optimization. Background Technology

[0002] In recent years, new energy sources, represented by wind power and photovoltaics, have experienced rapid development in my country. The increased proportion of new energy has profoundly changed the dynamic characteristics of the power system. New energy sources are generally connected to the grid through converters, and their output power is decoupled from the system frequency, resulting in near-zero inertia. However, wind turbines have poor tolerance to voltage fluctuations and weak active and reactive power regulation capabilities. Therefore, the large-scale integration of new energy sources poses challenges to system safety and stability. To ensure system frequency security, regulations stipulate that grid-connected wind and photovoltaic power should have a certain frequency regulation capability. Offshore wind power resources are abundant, with high operating efficiency, making it suitable for large-scale development and application. It is a key area for wind power development in my country. As of the end of November 2024, my country's cumulative grid-connected offshore wind power capacity had reached 39.1 million kilowatts. Offshore wind power operates under more severe conditions, with high signal measurement and transmission costs and large communication delays. Reducing signal acquisition and transmission requirements is an important factor to consider when designing control schemes. Researching frequency control technology for deep-sea wind power is of great significance for ensuring system frequency security.

[0003] Wind power frequency regulation methods can be divided into two categories: those based on load shedding and those based on rotor kinetic energy. Due to the former's drawbacks such as slow response speed, poor economic efficiency, and severe mechanical wear, rotor kinetic energy-based frequency regulation methods are commonly used. Integrated inertial control is a control method based on rotor kinetic energy. After a disturbance occurs, the wind turbines in the wind farm release rotor kinetic energy at the same rate. However, due to the limited nature of rotor kinetic energy and the distributed characteristics of wind speed, the available rotor kinetic energy for each turbine is different, and their exit times from frequency regulation are also inconsistent. During the frequency regulation process, the turbines will gradually exit frequency regulation, and each exit will lead to a corresponding "secondary frequency drop," increasing the risk of frequency instability.

[0004] For example, Chinese patent application CN202410356212.7 proposes a scheme for achieving consistent power adjustment within a wind farm and among multiple wind farms using a consensus algorithm. Some scholars have also proposed using distributed consensus algorithms for wind power frequency regulation control. Based on integrated inertial control, a consensus algorithm control is introduced, and the two are superimposed with the maximum power tracking power of the wind turbines to obtain the active power reference value of the leader turbine, achieving state consistency among wind turbines within the farm. Optimizing the integrated inertial control of the leader turbine can improve control performance and suppress the risk of secondary frequency drops. However, integrated inertial control and consensus control are coupled, and optimizing only the integrated inertial control component is insufficient to ensure optimal control performance. Summary of the Invention

[0005] The purpose of this invention is to overcome the problems of existing wind power frequency regulation control that do not take into account wind speed distribution characteristics, have the risk of secondary frequency drop, and have unsatisfactory distribution consistency control effect, and to propose a deep-sea wind farm distribution consistency frequency control method based on restraint signal optimization.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] As a first aspect of the present invention, a method for consistent frequency control of deep-sea wind farms based on traction signal optimization is provided, comprising the following steps:

[0008] Obtain power system parameters, including those from wind farms;

[0009] Construct a wind farm tethering and consistency control topology, set a leader unit to generate tethering signals, and the other wind turbines in the wind farm receive the tethering signals and communicate with adjacent wind turbines to exchange states.

[0010] A wind farm traction consistency frequency controller is set up for each wind turbine. The traction consistency frequency controller calculates the active power reference value of the corresponding wind turbine based on the wind turbine's own state, the state of adjacent turbines and the traction signal in order to control the release of rotor kinetic energy of the wind turbine.

[0011] A problem is constructed to optimize the duration of the frequency modulation phase of the restraint control signal, taking into account frequency security. The optimal restraint signal is obtained by solving the optimization problem.

[0012] As a preferred technical solution, obtaining the power system parameters includes:

[0013] Wind speed, rated capacity, and inertia time constant of the wind turbine, as well as the minimum speed of the wind turbine;

[0014] The wind farm network connection matrix and wind farm collector network parameters include the capacity, turns ratio and short-circuit reactance of the transformer at the common coupling point, the capacity, turns ratio and short-circuit reactance of the box-type transformer, and the collector network impedance.

[0015] As a preferred technical solution, the wind farm constraint consistency control topology is configured as follows:

[0016] The virtual machine is set up as the leader unit, which is used to generate control signals, and the control signals generated are connected to the wind turbines in the field.

[0017] All other wind turbines in the wind farm are follower turbines; each wind turbine calculates its own state variable x. i It communicates with adjacent units to exchange states, ultimately causing the states of all units to converge towards the constraint signal, wherein the wind turbine state variable x i for:

[0018]

[0019] In the formula: ω i For wind turbine G wi rotational speed; ω i,0 For wind turbine G wi Initial rotational speed; ω min The minimum permissible speed of a wind turbine.

[0020] As a preferred technical solution, the aforementioned frequency controller for maintaining consistency is specifically implemented as follows:

[0021] Based on the wind turbine's own status x i Adjacent unit status x j and restraint signal x ref Calculate the power ΔP generated by releasing rotor kinetic energy. ci :

[0022]

[0023] In the formula: k p k i These are the proportional coefficient and integral coefficient for consistent control, respectively; a ij Indicates the information transmission status between wind turbine units i and j; g i This indicates the status of wind turbine traction signal reception;

[0024] Wind turbine G calculated based on wind speed wi Captured mechanical power P m,i :

[0025] P m,i =0.5ρπR 2 v 3 C p (λ,β)

[0026] In the formula: ρ and R are the air density and rotor radius, respectively; v and β are the wind speed and blade pitch angle, respectively; λ and C are the wind speed and blade pitch angle, respectively. p These are the tip speed ratio and the wind energy utilization coefficient, respectively.

[0027] In wind turbine G wi Captured mechanical power P m,i On top of this, a constraint consistency control component ΔP is superimposed. c,i Get wind turbine G wi Active reference value P ref,i .

[0028] As a preferred technical solution, the restraining signal x ref The expression for (t) is:

[0029]

[0030] In the formula: t1 is the fault start time; t2 is the dividing point between the frequency modulation stage and the recovery stage, and t2-t1 is denoted as T. c t3 is the time when the frequency modulation control exits; a, b, θ and T c The parameter 'a' represents the constraint signal parameter; the value of parameter 'a' determines the constraint signal 'x'. ref The minimum value of (t); parameter b is a positive number used to control the speed recovery rate; θ is used to ensure x ref (t) is a decimal that remains continuous at time t2, θ = 1 - a - (1 + e 40b ) -1 ;T c The value of determines the period of the sine function during the frequency modulation phase.

[0031] As a preferred technical solution, considering frequency security, a frequency security index set η is constructed, wherein the frequency security index includes: the initial frequency change rate R. cof That is, the rate of frequency change within a set time after the disturbance; the minimum frequency drop value f. nad ; and the steady-state frequency f after the fault ss ;

[0032] The system frequency security constraints are described as follows:

[0033]

[0034] In the formula, f is the maximum initial frequency change rate; min and f ss,min These are the minimum allowable drop value and the minimum steady-state frequency value for system frequency safety, respectively.

[0035] As a preferred technical solution, the problem of optimizing the duration of the frequency modulation stage of the restraint control signal is specifically described as follows:

[0036]

[0037] In the formula: F is the comprehensive performance evaluation index of frequency control; ρ1 and ρ2 are the weighting coefficients of the penalty functions related to the initial frequency change rate and the minimum frequency drop constraint, respectively; z is the system state variable; y is the algebraic variable; f and g are the differential and algebraic equations of the power system, respectively; T c and The variables to be optimized are T. c The lower and upper bound values.

[0038] As a preferred technical solution, the solution process for optimizing the duration of the frequency modulation phase of the restraint control signal is as follows:

[0039] In the variable T to be optimized cThe lower and upper bound intervals Multiple Ts with equal inner spacing c value;

[0040] Calculate different T c The frequency control comprehensive performance evaluation index F of the objective function under the given values ​​is taken as T, and the value corresponding to the minimum frequency control comprehensive performance evaluation index F is taken as T. c As the optimal parameter for the restraining signal;

[0041] If the optimal parameter T is obtained by solving the optimization problem c If the corresponding frequency response curve still cannot meet the frequency safety constraints, then wind power frequency regulation needs to be coordinated with other measures.

[0042] As a second aspect of the present invention, an electronic device is provided, characterized in that it comprises:

[0043] One or more processors;

[0044] Memory, used to store one or more programs;

[0045] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described method for optimizing the uniform frequency control of deep-sea wind farms based on restraint signals.

[0046] As a third aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it implements the steps of the deep-sea wind farm uniform frequency control method based on the restraint signal optimization described above.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1) This invention considers the differences in rotor kinetic energy caused by wind speed distribution in offshore wind farms and proposes a constraint-consistency algorithm for frequency control. By designing and optimizing the constraint signal, the rotor kinetic energy release rate during frequency regulation is directly optimized based on the system's frequency regulation requirements and the available kinetic energy of the turbine. Furthermore, through consistency control, the consistent change in rotor kinetic energy of wind turbines with different rotational speeds within the wind farm is achieved, enabling the orderly release of rotor kinetic energy and thus optimizing wind power frequency support. The constraint-consistency algorithm proposed in this invention significantly improves the overall performance of wind power frequency regulation control, effectively suppresses the problem of secondary frequency drops, and enhances the frequency security of the power system.

[0049] 2) The method of the present invention fully considers the system requirements of each stage of disturbance and the frequency regulation potential of wind turbine, designs a general restraint signal function, and optimizes the restraint signal parameters to achieve a smooth transition between the frequency regulation stage and the recovery stage of wind turbine, and reduces the communication requirements in the control process, thereby improving the overall performance of frequency control. Attached Figure Description

[0050] Figure 1 A schematic diagram of the invention process provided for an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of a constraint and consistency control topology based on a virtual leader machine provided in an embodiment of the present invention;

[0052] Figure 3 A schematic diagram of a frequency controller for controlling the consistency of deep-sea wind farms provided in an embodiment of the present invention.

[0053] Figure 4 A schematic diagram of the design of the restraint signal function based on the characteristics of each stage after the disturbance is provided for an embodiment of the present invention;

[0054] Figure 5 A schematic diagram of a power system including a deep-sea wind farm, provided for an embodiment of the present invention;

[0055] Figure 6 The diagram shows the rotational speed curves of different wind turbine units under the traction and consistent control provided in the embodiments of the present invention. In this diagram, the thick solid line, thick dashed line, thick dotted line, solid line, dashed line, and dotted line represent wind turbines 1 to 6, respectively.

[0056] Figure 7 This is a schematic diagram of the frequency response curves under different restraint signals in an embodiment of the present invention, wherein the solid line T... c 25s, dashed line T c For 30 seconds, point-line T c It lasts for 35 seconds.

[0057] Figure 8 The diagram shows frequency response curves under different control strategies provided in the embodiments of the present invention. The solid line represents the method proposed in the present invention, and the dashed line represents the integrated inertial control method. Detailed Implementation

[0058] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0059] Example 1

[0060] To overcome the problems of existing wind power frequency regulation control that do not take into account wind speed distribution characteristics, have the risk of secondary frequency drop, and have unsatisfactory distribution consistency control effect, this invention proposes a frequency control method for distribution consistency of deep-sea wind farms based on the optimization of restraint signals.

[0061] To achieve the above-mentioned objectives, the present invention adopts the following technical solution.

[0062] A method for consistent frequency control of deep-sea wind farm distribution based on constraint signal optimization includes the following steps:

[0063] Step 1: Obtain power system parameters, including those for deep-sea wind farms;

[0064] Step 2: Construct a frequency controller for deep-sea wind farms to maintain consistency.

[0065] Step 3: Design the restraint signal function based on the characteristics of each stage after the disturbance;

[0066] Step 4: Comprehensive assessment of frequency security and optimization of restraint signal parameters.

[0067] Specifically, the process of obtaining power system parameters, including those from deep-sea wind farms, in step (1) is as follows:

[0068] Obtain wind turbine G wi wind speed v wi Rated capacity S wi and inertial time constant H wi And the minimum speed ω of the wind turbine min Where i = 1, 2, ..., n w The numbering of the wind turbine unit, n w The number of wind turbines in the wind farm is given; the parameters of the consistency controller and the network connection matrix of the deep-sea wind farm are obtained, where the proportional coefficient and integral coefficient of the controller are k and k respectively. p k i The network connectivity matrix is ​​A = [a ij ], where a ij This represents network node connection information, where i = 1, 2, ..., n w j = 1, 2, ..., n w If wind turbine G wj Wind turbine G wi If information is transmitted, then a ij =1, otherwise a ij =0; Obtain wind farm collector network parameters, including the transformer capacity at the point of common coupling (PCC). Transformer and short-circuit reactance Box-type transformer capacity S WT Transformer ratio K WT and short-circuit reactance X WT and collector network impedance R WL +jX WL .

[0069] The process of constructing the deep-sea wind farm traction consistency frequency controller described in step (2) is as follows:

[0070] The frequency support method for deep-sea wind farms based on constrained consistency control applies a constrained state signal to the lead turbine. Each turbine in the wind farm communicates and exchanges states with its neighbors, interacting with each other until the state of all turbines tends towards the constrained signal. Turbines with higher rotational speeds should release more rotor kinetic energy to achieve frequency support. The wind turbine state variable x is defined. i for:

[0071]

[0072] In the formula: i For wind turbine G wi rotational speed; ω min The minimum permissible speed of a wind turbine is generally taken as 0.75 pu;

[0073] ω i,0 For G wi Initial rotational speed; x i Reflects G wi The proportion of remaining adjustable kinetic energy to total adjustable kinetic energy is related to ω. i In a one-to-one correspondence, during the frequency control process of a wind farm based on a constraint consensus algorithm, the x of each unit... i To maintain consistency means that the rate at which the units release kinetic energy will be the same, and they will simultaneously reach the minimum speed and enter the speed recovery phase.

[0074] The topology design of the tie-in consensus controller for deep-sea wind farms is as follows: assuming the leader unit is a virtual machine G. vir Its function is solely to generate a restraining signal x. ref (t), but does not possess the physical functions of a wind turbine generator; its generated restraint signal is connected to the wind turbine generators within the site. For example... Figure 2 The diagram shows a constrained consistency control topology based on a virtual leader machine. When fan G... wi Received restraint signal x ref When (t), g i =1; otherwise g i =0; All other units in the wind farm are follower units, and all wind turbines calculate their own state variables x. i It also communicates with adjacent units.

[0075] like Figure 3 As shown, the constrained consistency controller determines its state based on its own state, the states of adjacent units, and the constrained signal x. ref (t) Calculate the power ΔP generated by releasing the rotor kinetic energy. ci :

[0076]

[0077] In the formula: k p k i These are the proportional coefficient and integral coefficient for consistency control, respectively.

[0078] Wind turbine G wi Captured mechanical power P m,i for:

[0079] P m,i =0.5ρπR 2 v 3 C p (λ,β) (3)

[0080] In the formula: ρ and R are the air density and rotor radius, respectively; v and β are the wind speed and blade pitch angle, respectively, and β is generally 0 under frequency regulation based on rotor kinetic energy; λ and C p These are the tip speed ratio and wind energy utilization coefficient, respectively; in wind turbine G wi Captured mechanical power P m,i On top of this, a constraint consistency control component ΔP is superimposed. c,i Get wind turbine G wi Active reference value P ref,i :

[0081] P ref,i =P m,i +ΔP c,i (4)

[0082] Due to wind turbine G wi P m,i and ΔP ci All depend on its rotational speed ω i Therefore, by optimizing the speed change curve of the wind turbine during frequency regulation, the orderly release of rotor kinetic energy can be achieved, thereby improving the frequency safety of the system.

[0083] The implementation process of designing the restraint signal function based on the characteristics of each stage after the disturbance in step (3) is as follows:

[0084] Under restraint control, the state variables x of the units in the wind farm i With restraint signal x ref (t) are equal, for wind turbine speed and x i Optimization means adjusting the restraint signal x. ref(t) is optimized. Taking low-frequency faults as an example, such as Figure 4 The kinetic energy release of the wind turbine rotor shown has the following characteristics in each stage of frequency regulation control: In the short period after the disturbance, the wind power should be increased as much as possible to slow down the frequency drop; as the frequency decreases, the primary frequency regulation power of the synchronous generator in the system increases accordingly, and the output power of the wind turbine can gradually decrease; when the state variable x... i When ω approaches zero, in order to delay the recovery phase as much as possible, ω should be made... i and x i The change should be as slow as possible, at which point the wind turbine's increased power output ΔP ci Approximately zero; in x i At time 0, the increased power generation changes from positive to negative, and the wind turbine enters the speed recovery phase. To mitigate the power surge caused by the switching, x should be... i During the initial recovery phase of the rotational speed, the increase should be as gradual as possible, i.e., the recovery rate should be slowed down to minimize the increase in power; once the frequency has recovered to a certain level, x can be gradually increased. i The recovery rate is maintained until the speed returns to steady state.

[0085] Based on the frequency modulation characteristics of each stage after the disturbance, a restraining signal x is designed. ref The general expression for (t) is:

[0086]

[0087] In the formula: t1 is the fault start time; t2 is the dividing point between the frequency modulation stage and the recovery stage, and t2-t1 is denoted as T. c t3 is the time when frequency modulation control exits; during the time interval [t1, t2], x ref (t) is a sine curve with a large initial rate of change, which gradually decreases until it reaches point x at t2. ref and All are zero; during the time interval [t2,t3], a, b, θ, and T are all zero. c The parameter 'a' is undetermined; the value of parameter 'a' determines x. ref The minimum value of (t) is generally 0 ≤ a ≤ 1. When the power deficit is large, all the adjustable kinetic energy of the fan needs to be released, so a = 1 can be taken; parameter b is a positive number used to control the speed recovery speed. The smaller b is, the slower the speed recovery. Generally, b = 0.1 can be taken; θ is used to ensure x ref (t) is a decimal that remains continuous at time t2, θ = 1 - a - (1 + e 40b ) -1 ;T c The value of T determines the period of the sine function during the frequency modulation phase. c The smaller the initial time x refThe faster the change in (t), the greater the released kinetic energy of the unit, and the greater the short-term power support provided by the wind turbine. The faster the kinetic energy is released, the shorter its duration. In practice, the requirements for short-term support power and duration in frequency control can be coordinated to address the issue of T. c The value of is optimized for calculation.

[0088] The frequency security comprehensive assessment and restraint signal parameter optimization described in step (4) are implemented as follows:

[0089] The frequency security index set η={R cof ,f nad ,f ss The system frequency security is evaluated, where R... cof f represents the initial frequency change rate, specifically the frequency change rate within 1 second after the disturbance. nad This represents the lowest frequency drop value; f ss The steady-state frequency after the fault; the system frequency security constraint can be described as:

[0090]

[0091] In the formula: The maximum initial frequency change rate is typically taken as 0.2 Hz / s; f min and f ss,min These are the minimum allowable drop values ​​and the minimum steady-state frequency values ​​for system frequency safety, respectively, which are generally 59.5Hz and 59.8Hz.

[0092] Based on the power system parameters, including those from offshore wind farms, obtained in step (1), experiments were conducted. Simulations showed that T c When the value is small, kinetic energy is released quickly, therefore R cof Smaller, but the lowest frequency point f nad Lower; while T c When it is large, f can be increased nad However, it will also increase R cof Since the wind turbine speed will return to its pre-disturbance value in steady state, T c Value pair f ss No impact; in order to balance the system's effect on R cof and f nad The requirements for the restraint control signal parameter T c To optimize this, the problem can be described as follows:

[0093]

[0094] In the formula: F is the comprehensive performance evaluation index of frequency control; ρ1 and ρ2 are the weighting coefficients of the penalty functions related to the initial frequency change rate and the minimum frequency drop constraint, respectively, and can generally be taken as... z represents the system state variables, such as power angle, speed, and electromotive force; y represents the algebraic variables, such as voltage and phase angle; f and g represent the differential and algebraic equations of the power system, respectively; T c and The variables to be optimized are T. c The lower and upper bound values.

[0095] T c The value of T should take into account the limitation of the wind turbine power ramp rate. c If the wind power reference value is too high when the value is too small, it will cause the limiting circuit to activate, and the consistency control will fail to converge. Generally, T can be taken separately. c and The intervals are 25 seconds and 40 seconds. Solving the optimization problem described by equation (7) within the interval... Fifteen points are selected at equal intervals within the inner region, which are used as T. c The value of T varies for different T values. c The objective function F is calculated under the given values, and T is taken as the value corresponding to the minimum value of F. c As the optimal parameter for the restraining signal; if the optimal parameter T c If the corresponding frequency response curve still cannot meet the frequency security constraints described by equation (6), then it is necessary to consider the coordinated control of wind power frequency regulation and other measures.

[0096] The proposed consistent frequency control method was simulated based on the acquired system parameters to verify the effectiveness of frequency regulation based on the constrained consistency algorithm, specifically whether the turbines within the offshore wind farm achieve consistent frequency regulation using state variables and whether they simultaneously reach the minimum speed. A comprehensive evaluation of the system frequency response under different constraining signals was conducted to verify the effect of constraining signal parameter optimization on improving the overall frequency response performance. Simulations were performed to compare the traditional integrated inertial control method and the method proposed in this invention, comparing the overall frequency safety performance index {R}. cof ,f nad ,f ss The comparison results verified the effectiveness of the proposed method for consistent frequency control of deep-sea wind farm distribution based on traction signal optimization.

[0097] Example 2

[0098] This embodiment provides a specific implementation example of applying the above-described method for frequency control of deep-sea wind farm distribution based on tethering signal optimization to a power system including deep-sea wind farms, with the transmission network being a modified IEEE 3-machine 9-node system. Figure 5 As shown, the deep-sea wind farm consists of six identical doubly-fed wind turbines; the wind speed of the wind turbines is as follows: Figure 2The speeds are 12.0 m / s, 10.0 m / s, 9.5 m / s, 11.0 m / s, 10.5 m / s, and 8.5 m / s respectively. The wind turbines are connected to the PCC point via a box-type transformer and a collector network, and then connected to the transmission network via a step-up transformer. The power system parameters are detailed in Table 1.

[0099] Table 1 Power system parameters including deep-sea wind farms

[0100]

[0101] according to Figure 5 The wind farm topology shown is configured to allow neighboring turbines to exchange status information with the power collection network. Therefore, in this embodiment, the network connection matrix A = [a ij The settings are as follows:

[0102]

[0103] Constructing a traction frequency controller for deep-sea wind farms, such as Figure 3-4 As shown, the frequency support method for deep-sea wind farms based on constraint consistency control applies a constraint state signal to the lead unit, and each unit in the wind farm communicates and exchanges states with adjacent units, interacting with each other, and ultimately making the state of all units tend to the constraint signal.

[0104] Simulation experiments were conducted based on system parameters to verify the effectiveness of frequency regulation based on the constraint consensus algorithm, specifically whether the units within the offshore wind farm achieve consistent frequency regulation using state variables and whether they simultaneously reach the minimum speed. A comprehensive evaluation of the system frequency response under different constraint signals was performed to verify the effect of constraint signal parameter optimization on improving the overall frequency response performance. Simulations were conducted to compare the traditional integrated inertial control method and the method proposed in this invention, comparing the comprehensive frequency safety performance index {R}. cof ,f nad ,f ss This study verifies the effectiveness of the proposed method for consistent frequency control of deep-sea wind farm distribution based on traction signal optimization.

[0105] Suppose that the load at system node 5 suddenly increases by 35MW at 10s. Under the control of the constrained consensus algorithm, the speed curves of different wind turbine units are as follows: Figure 6 As shown, during the frequency regulation and recovery phases, the wind farm turbine speed changes under consistent frequency control exhibit excellent consistency. Within approximately 45 seconds, the turbines within the offshore wind farm can simultaneously reach their minimum speed and exit frequency regulation. The speed recovery is completed within approximately 110 seconds, verifying the effectiveness of the frequency regulation based on the constraint consistency algorithm proposed in this invention.

[0106] For different T cThe system frequency response is comprehensively evaluated based on the selected values, and the specific indicators are shown in Table 2, where the steady-state frequency f is... ss The frequency is 59.808 Hz, which meets the frequency security requirements. When T c When the value is 25s, the frequency drop extreme value is less than f. min Therefore, the weighting coefficients of the penalty function make F larger when T c When the time exceeds 33s, the system frequency response curve and F do not change significantly. In general, T c The larger the value, the slower the unit releases kinetic energy, the longer the duration, and the smaller the frequency drop, but the larger the frequency change rate. Therefore, in this embodiment, T is chosen based on F. c The duration is 40 seconds; partial frequency response curves are shown below. Figure 7 .

[0107] Table 2 Optimized values ​​for the reference signal for maintaining consistency

[0108]

[0109] A simulation comparison was performed between the traditional integrated inertial control method and the method proposed in this invention. The simulation results are as follows: Figure 8 As shown in Table 3, the frequency response indices under different control strategies are as follows. The results show that under integrated inertial control, due to the difference in rotor kinetic energy caused by wind speed distribution, each wind turbine in the field gradually exits frequency regulation during the dynamic process. Each exit triggers a secondary frequency drop. However, since the exit of a single unit has a small impact on the system, the amplitude of each drop is relatively small. Simulation results show that the minimum frequency drop under the integrated inertial control strategy is 59.495Hz, which does not meet the system frequency safety constraints. The method of this invention, by designing a reference signal, enables consistent frequency regulation of the units within the wind farm, effectively suppressing frequency drops. At the same time, by optimizing the reference signal, the frequency control effect is significantly improved. In summary, the method proposed in this invention is superior to the traditional integrated inertial control in terms of frequency change rate and minimum drop value, effectively improving the system frequency safety.

[0110] Table 3 Frequency response indices under different control strategies

[0111]

[0112] In summary, this invention proposes a frequency control method for the distribution consistency of deep-sea wind farms based on the optimization of the restraining signal. In a power system including deep-sea wind farms, a frequency controller for the restraining consistency of deep-sea wind farms is constructed. The restraining signal function is designed considering the characteristics of the frequency regulation and recovery phases after disturbances. The restraining signal parameters are optimized through a comprehensive frequency security evaluation index. Finally, a simulation comparison with the integrated inertial method verifies that the method of this invention can consider the differences in wind speed distribution in offshore wind farms, achieve consistent frequency regulation states of units within the wind farm, effectively reduce secondary frequency drops, and improve frequency support. This is of great significance for enhancing the frequency security of power systems including offshore wind farms.

[0113] Example 3

[0114] As a second aspect of the present invention, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the above-described method for consistent frequency control of deep-sea wind farms based on tethering signal optimization. In addition to the processors, memory, and interfaces described above, any data processing device in the embodiments may also include other hardware depending on the actual function of the data processing device, which will not be elaborated further.

[0115] Example 4

[0116] As a third aspect of the present invention, this application also provides a computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the aforementioned method for consistent frequency control of deep-sea wind farms based on tethering signal optimization. The computer-readable storage medium can be an internal storage unit of any data processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.

[0117] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for consistent frequency control of deep-sea wind farms based on constraint signal optimization, characterized by the following steps: include: Obtain power system parameters, including those from wind farms; A wind farm constrained consistency control topology is constructed, a leader unit is set to generate a constraining signal, and the remaining wind turbines in the wind farm receive the constraining signal and communicate with adjacent wind turbines to exchange states; the constraining signal... The expression is: In the formula: This is the moment the fault begins; This marks the boundary between the frequency modulation phase and the recovery phase. Recorded as ; This is the time when frequency modulation control exits; , , and For the restraint signal parameters; parameters The value of determines the restraint signal The minimum value; parameter It is a positive number used to control the speed recovery rate; To ensure exist Decimals that remain continuous at all times. ; The value of determines the period of the sine function during the frequency modulation phase; A wind farm traction consistency frequency controller is set up for each wind turbine. The traction consistency frequency controller calculates the active power reference value of the corresponding wind turbine based on the wind turbine's own state, the state of adjacent turbines and the traction signal in order to control the release of rotor kinetic energy of the wind turbine. A problem is constructed to optimize the duration of the frequency modulation phase of the restraint control signal, taking into account frequency security. The optimal restraint signal is obtained by solving the optimization problem.

2. The method for consistent frequency control of deep-sea wind farms based on constraint signal optimization according to claim 1, characterized in that, Obtaining the power system parameters includes: Wind speed, rated capacity, and inertia time constant of the wind turbine, as well as the minimum speed of the wind turbine; The wind farm network connection matrix and wind farm collector network parameters include the capacity, turns ratio and short-circuit reactance of the transformer at the common coupling point, the capacity, turns ratio and short-circuit reactance of the box-type transformer, and the collector network impedance.

3. The method for consistent frequency control of deep-sea wind farms based on constraint signal optimization according to claim 1, characterized in that, The wind farm's constraint consistency control topology is configured as follows: The virtual machine is set up as the leader unit, which is used to generate control signals, and the control signals generated are connected to the wind turbines in the field. All other wind turbines in the wind farm are follower turbines, and each wind turbine calculates its own state variables. It communicates with adjacent units to exchange states, ultimately causing the states of all units to converge towards the constraint signal, and the wind turbine state variables... for: In the formula: For wind turbines The rotational speed; For wind turbines Initial rotational speed; The minimum permissible speed of a wind turbine.

4. The method for consistent frequency control of deep-sea wind farms based on constraint signal optimization according to claim 1, characterized in that, The specific implementation of the aforementioned frequency controller for maintaining consistency is as follows: Based on the condition of the wind turbine itself Status of adjacent units and restraint signals Calculate the power generated by releasing rotor kinetic energy. : In the formula: , These are the proportional coefficient and integral coefficient for consistency control, respectively. Indicates wind turbine i, j Information transmission status; This indicates the status of wind turbine traction signal reception; Wind turbine based on wind speed calculation Captured mechanical power : In the formula: , These are air density and wind turbine radius, respectively. , These are wind speed and propeller pitch angle, respectively. and These are the tip speed ratio and the wind energy utilization coefficient, respectively. In wind turbine Captured mechanical power On top of this, a constraint consistency control component is superimposed, that is, the power generated by releasing rotor kinetic energy. Get wind turbine Active reference value .

5. The method for consistent frequency control of deep-sea wind farms based on constraint signal optimization according to claim 1, characterized in that, To consider frequency security, a set of frequency security indicators has been constructed. The frequency security indicators include: initial frequency change rate. This refers to the rate of frequency change within a set time period after the disturbance; the minimum frequency drop value. ; and the steady-state frequency after the fault ; The system frequency security constraints are described as follows: In the formula, The maximum initial frequency change rate; and These are the minimum allowable drop value and the minimum steady-state frequency value for system frequency safety, respectively.

6. The method for consistent frequency control of deep-sea wind farms based on restraint signal optimization according to claim 5, characterized in that, The specific description of the problem of optimizing the duration of the frequency modulation phase of the restraint control signal is as follows: In the formula: As a comprehensive performance evaluation index for frequency control; , The weighting coefficients of the penalty functions related to the initial rate of change of frequency and the minimum frequency drop constraint, respectively; For system state variables; For algebraic variables; , These are the differential and algebraic equations of the power system, respectively. and The variables to be optimized are respectively The lower and upper bound values.

7. The method for consistent frequency control of deep-sea wind farms based on constraint signal optimization according to claim 6, characterized in that, The solution process for the problem of optimizing the duration of the frequency modulation phase of the restraint control signal is as follows: In the variable to be optimized The lower and upper bound intervals Multiple inner equal intervals value; Calculations are different Comprehensive performance evaluation index of frequency control of objective function under different values Select the comprehensive performance evaluation index of frequency control. The minimum corresponding As the optimal parameter for the restraining signal; If the optimal parameters are obtained by solving the optimization problem If the corresponding frequency response curve still cannot meet the frequency safety constraints, then wind power frequency regulation needs to be coordinated with other measures.

8. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for optimizing the uniform frequency control of deep-sea wind farms based on the restraint signal as described in any one of claims 1-7.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the deep-sea wind farm uniform frequency control method based on the restraint signal optimization as described in any one of claims 1-7.

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