Control method for optimizing frequency response secondary drop of offshore wind power flexible direct current system

Abstract

The invention discloses a control method for optimizing frequency response secondary drop of an offshore wind power flexible direct current system. According to the method, modeling is carried out on an offshore wind power flexible direct current system, frequency response characteristics of a fan slowly exiting a frequency modulation system are deeply analyzed, and double-layer optimization is carried out on fan exiting frequency modulation parameters in combination with a particle swarm algorithm under the condition that fan response time delay is considered. Gradually increasing the time delay, and repeatedly implementing optimization to obtain an optimal fan slow quit frequency modulation parameter under different time delays until the time delay reaches a threshold value; and comparing to obtain the optimal time delay and the fan slow quit frequency modulation parameter. According to the method, the frequency response secondary drop is optimized for the offshore wind power flexible direct current system, the effectiveness and applicability of the control strategy in the offshore wind power plant environment are ensured, and the method has universality. According to the method, the response delay of the fan is fully considered in the control strategy, and the effective control of the frequency secondary drop is realized by slowly adjusting the active power of the fan, so that the frequency stability and reliability of the power grid are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of frequency control of new power systems, and in particular relates to a control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current transmission system. Background Art

[0003] After large-scale access to the offshore wind farm through flexible DC grid connection, it will replace some synchronous generators, resulting in a reduction in the inertia of the AC system, affecting the overall frequency regulation capability of the system. When the power system frequency changes significantly due to machine shedding or load mutation, the rotor kinetic energy of the offshore wind turbine needs to be restored to its initial state as soon as possible after releasing the rotor kinetic energy to provide frequency support. In this process, since the offshore wind turbine cannot operate at the maximum power tracking point, if there is no additional power to make up for this shortfall, the recovery process may cause a secondary drop in the system frequency. If the speed recovery control strategy is not set reasonably, the secondary frequency drop may be even more serious than the first drop.

[0004] In existing research, the issue of frequency response of offshore flexible direct current transmission systems is particularly prominent. Since the geographical location and operating conditions of offshore wind turbines are significantly different from those of onshore wind turbines, their impact on grid frequency is more complex and unpredictable. However, existing technologies often fail to fully consider the potential impact of the rotor recovery process on system frequency stability in this scenario, and lack effective control strategies to prevent or mitigate the secondary frequency drop caused thereby. Therefore, the present invention proposes a frequency response secondary drop optimization control strategy based on an offshore wind power flexible direct current transmission system, which optimizes the behavior of offshore wind turbines in an offshore flexible direct current transmission system when exiting active frequency support, so as to reduce the impact of secondary frequency drop on the grid and ensure the reliability and stability of the system. Summary of the invention

[0005] The present invention provides a control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system, so as to solve the problem of secondary drop of power grid frequency caused by traditional wind power inertia control technology. The present invention improves the way of exiting frequency modulation of wind turbines, considers the response time delay of wind turbines and can keep the initial support power of wind turbines unchanged, so that the wind turbines can naturally transition to the maximum power point tracking mode by slowly reducing the active power, thereby optimizing the speed and amplitude of the secondary drop.

[0006] To achieve the above object, the present invention provides a control method for optimizing the frequency response secondary drop of an offshore wind power flexible direct current system, comprising the following steps:

[0007] Step 1: Mathematically model the typical frequency support system for offshore wind power flexible direct current transmission to obtain a model of the typical frequency support system for offshore wind power flexible direct current transmission. The typical frequency support system for offshore wind power flexible direct current transmission includes a receiving-end converter, a sending-end converter, a machine-side converter, a grid-side converter, a direct-drive wind turbine, a synchronous generator speed regulator system and its additional frequency support control system.

[0008] Step 2: Based on the established power system frequency response model with typical frequency support for flexible direct current transmission of offshore wind power, calculate the frequency response characteristics of the system.

[0009] For the typical frequency support system of offshore wind power flexible direct current transmission, the system frequency is not only affected by the dynamics of the converter, but also needs to be analyzed in combination with an additional frequency support control system. Combining the general frequency response model and the transfer function model of the typical frequency support system of offshore wind power flexible direct current transmission, a power system frequency response model containing the typical frequency support of offshore wind power flexible direct current transmission is established:

[0010]

[0011] Where Δf s (s) is the electromagnetic power deviation and system frequency deviation during the frequency response of the power system with typical frequency support for flexible direct current transmission of offshore wind power, s is the Laplace operator, ΔP is the load disturbance, H is the equivalent inertia constant of the offshore wind farm, D is the equivalent damping coefficient of the offshore wind farm, G gov (s) is the transfer function of the synchronous generator speed regulator system, which is the feedback branch of the frequency response model. K1 is the frequency modulation coefficient of the receiving-end converter, K2 is the frequency modulation coefficient of the sending-end converter, K3 is the frequency-torque command frequency modulation coefficient of the machine-side converter, G PMSG (s) is the transfer function of the output power caused by the change of the fan power torque command value, which is regarded as the equivalent speed regulator link of the system and serves as the feedback path of the frequency response model.

[0012] When considering the response time delay of the fan and the fan exiting the frequency modulation, the fan is slowly exiting the frequency modulation to slow down the secondary drop. The high-order frequency response model of the system when the fan slowly exits the frequency modulation can be expressed as:

[0013]

[0014] Among them, T d is the time delay of the fan response, K c Slowly exit the frequency regulation parameters for the fan.

[0015] When the inverse Laplace transform method is used to solve the high-order frequency response model of the system when the fan slowly exits the frequency modulation, it is difficult to obtain a specific function analytical expression. Therefore, the present invention adopts a system model reduction method to reduce the high-order frequency response model of the system when the fan slowly exits the frequency modulation power to a second-order frequency response system. Then when the fan slowly exits, the average frequency change rate RoCoF and the maximum frequency deviation Δf max and the steady-state frequency deviation Δf st can be expressed as c function.

[0016] Step 3: According to the optimization objectives and constraints, the particle swarm algorithm is used to optimize the wind turbine slow exit frequency modulation parameters.

[0017] The fitness of a particle is calculated by the following equation:

[0018] minQ(K c )=η1|RoCoF|+η2|Δf max |+η3|Δf st |;

[0019] Among them, η1, η2 and η3 are weight coefficients, ranging from 0 to 1 and η1+η2+η3=1.

[0020] The fan slowly exits the frequency modulation parameter K c The optimization needs to satisfy the constraints of maximum frequency deviation and steady-state frequency deviation, that is:

[0021] Δf st <Δf st,limit ,

[0022] Δf max <Δf max,limit ;

[0023] Where Δf max,limit is the maximum frequency deviation value, Δf st,limit is the maximum steady-state frequency deviation value.

[0024] Step 4: Gradually increase the delay, repeat steps 2 and 3, and obtain the optimal wind turbine slow exit frequency modulation parameters under different delays until the delay reaches the threshold.

[0025] In the process of optimizing the system frequency modulation parameters, an initial fan response time delay T0 is first set, and then the delay value is gradually increased at a fixed time interval ΔT to search for different response time delays T d In each iteration, we look for the optimal slow exit parameter K. c, to determine which parameter can provide the best system frequency response secondary drop and system stability under the current delay. After each round of iteration, the iteration counter d is updated to increase by 1, the time delay value is updated, and the next round of parameter optimization is prepared until the time delay reaches the threshold, that is:

[0026] T d =T0+d*ΔT;

[0027] Where d is the number of iterations, T0 is the initial fan delay response time, and ΔT is the time increment.

[0028] Step 5: Compare all T d The fitness function Q(K c ), and obtain the minimum fitness function minQ(K c ), and then get the optimal response time delay T d and the optimal slow exit frequency modulation parameter K c .

[0029] The beneficial effects of the present invention are as follows:

[0030] The present invention proposes a secondary drop control strategy for optimizing the frequency response of an offshore wind power flexible direct current system. By modeling the offshore wind power flexible direct current system and deeply analyzing the frequency response characteristics of the wind turbine slowly exiting the frequency modulation system, the wind turbine exit frequency modulation parameters are double-layer optimized in combination with a particle swarm algorithm under consideration of the wind turbine response time delay. The improvements and advantages of the present invention over the prior art are as follows:

[0031] 1. The present invention optimizes the secondary drop of frequency response for offshore wind power flexible direct current systems, ensuring the effectiveness and applicability of the control strategy in offshore wind farm environments, and has universal applicability.

[0032] 2. The present invention fully considers the response delay of the wind turbine in the control strategy, and realizes effective control of the secondary frequency drop by slowly adjusting the active power of the wind turbine, thereby ensuring the frequency stability and reliability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of a control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system provided by an embodiment of the present invention;

[0034] Figure 2 This is a block diagram of a typical frequency support control system for flexible direct current transmission of offshore wind power provided by an embodiment of the present invention;

[0035] Figure 3 It is a high-order frequency response model block diagram of a typical frequency support control system for flexible direct current transmission of offshore wind power provided by an embodiment of the present invention;

[0036] Figure 4 It is a block diagram of a frequency response model of a power system including typical frequency support for flexible direct current transmission of offshore wind power provided by an embodiment of the present invention;

[0037] Figure 5 It is an iterative process of the optimal fan slow exit frequency modulation parameter under the optimal fan response time delay provided by the embodiment of the present invention;

[0038] Figure 6 It is the frequency change response result under the optimal fan slow exit frequency modulation parameter and the optimal fan response delay provided by the embodiment of the present invention;

[0039] Figure 7 It is the wind power output response result under the optimal wind turbine slow exit frequency modulation parameters and the optimal wind turbine response delay provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1 , Figure 1 The present invention provides a flow chart of a method for controlling a secondary drop in frequency response of an offshore wind power flexible direct current system. The method for controlling a secondary drop in frequency of the optimized system includes:

[0042] S1. Obtaining the unit parameters, control parameters and operating status of the wind farm and synchronous units;

[0043] S2. When the system frequency drops for the second time, the frequency response characteristics of the system are obtained based on the real-time monitored power disturbance signal and the current time delay;

[0044] S3, using particle swarm algorithm to optimize the fan slow exit frequency modulation parameters according to the optimization objectives and constraints;

[0045] S4, gradually increase the time delay, repeat S2 and S3, and obtain the optimal wind turbine slow exit frequency modulation parameters under different time delays until the time delay reaches the threshold;

[0046] S5. Compare the best system performance indicators under all time delays, so as to obtain the optimal time delay and wind turbine slow exit frequency modulation parameters;

[0047] The embodiment of the present invention provides a control method for optimizing the frequency response secondary drop of an offshore wind power flexible direct current system. By modeling a typical frequency support system for offshore wind power flexible direct current transmission and deeply analyzing the frequency response characteristics of the wind turbine slowly exiting the frequency modulation system, a double-layer optimization strategy is adopted, namely, optimizing the wind turbine exit frequency modulation parameters and adjusting the wind turbine response time, which effectively copes with the secondary drop problem of the system frequency. It has a simple structure, is easy to implement, and can respond quickly and effectively to fluctuations in the system frequency, thereby significantly improving the stability and response speed of the system.

[0048] The specific method is as follows:

[0049] Step 1: Obtain the unit parameters, control parameters and operating status of the wind farm and synchronous units, model the typical frequency support system for offshore wind power flexible direct current transmission, and obtain the model of the typical frequency support system for offshore wind power flexible direct current transmission. The typical frequency support system for offshore wind power flexible direct current transmission includes a receiving-end converter, a sending-end converter, a machine-side converter, a grid-side converter, a direct-drive wind turbine, a synchronous generator speed regulator system and its additional frequency support control system. The structure of the typical frequency support system for offshore wind power flexible direct current transmission of the present invention is as follows: Figure 2 As shown. The receiving-end converter and the sending-end converter of the conventional frequency support control strategy adopt dual-loop control, and the typical frequency support control strategy combines conventional frequency support control and additional frequency support control. This control strategy adds a mapping relationship between the receiving-end converter-DC capacitor-machine-side converter on the basis of the conventional frequency support control strategy, and transmits the frequency disturbance information on the onshore AC power grid side to the AC bus side of the offshore wind turbine. At the same time, the frequency regulation control strategy of the direct-drive wind turbine is added to the control of the machine-side converter. After the grid-side converter obtains the frequency information of the offshore wind power AC bus through the phase-locked loop of the wind turbine, the torque command of the machine-side converter is changed to achieve system frequency support.

[0050] The DC voltage reference value under the additional frequency support control can be obtained by the following formula, namely:

[0051] U dcref =K1(f-f0)+U dcref0 ;

[0052] Where f is the onshore AC grid frequency detected by the grid-connected phase-locked loop, f0 is the rated frequency of the system, K1 is the frequency modulation coefficient of the receiving-end converter, and U dcref0 is the DC voltage reference value for conventional frequency support control, U dcref It is the DC voltage reference value for typical frequency support control.

[0053] The frequency reference value of the offshore AC power grid under the additional frequency support control can be obtained by the following formula, namely:

[0054] f ref=K2(U dc -U dcref )+f0;

[0055] Among them, U dc is the voltage of DC transmission, K2 is the frequency modulation coefficient of the converter at the sending end, f ref Frequency reference value of offshore AC bus controlled by conventional frequency support.

[0056] The reference value of the torque command of the generator-side converter under the additional frequency support control can be obtained by the following formula:

[0057] T ncmd =T cmd +K3Δf;

[0058] Among them, Δf is the difference between the system frequency obtained by the grid-side converter phase-locked loop and the rated frequency, K3 is the frequency-torque command frequency modulation coefficient, T cmd is the torque command value of conventional frequency support control, T ncmd It is the torque command value for conventional frequency support control.

[0059] The additional frequency support control system model can be expressed as:

[0060] ΔP add (s) = K1*K2*K3*G PMSG (s)*Δf

[0061] Among them, ΔP add (s) Power support provided for additional frequency support control systems.

[0062] In summary, the typical frequency support system model of offshore wind power flexible direct current transmission is as follows: Figure 3 As shown, it can be expressed as:

[0063]

[0064] Wherein, Δf(s) is the electromagnetic power deviation and system frequency deviation during the frequency response of the power system supported by the typical frequency of offshore wind power flexible direct current transmission, s is the Laplace operator, ΔP is the load disturbance, H is the equivalent inertia constant of the conventional frequency support system of offshore wind power flexible direct current transmission, D is the equivalent damping coefficient of the conventional frequency support system of offshore wind power flexible direct current transmission, G is the equivalent inertia constant of the conventional frequency support system of offshore wind power flexible direct current transmission, PMSG (s) is the transfer function of the output power caused by the change of the fan power torque command value, J w is the moment of inertia of the direct drive fan, ω r0 is the initial value of the direct-drive wind turbine speed, ρ is the air density, r is the radius of the wind turbine blade rotor, v is the wind speed, C P(λ, β) is the wind energy utilization coefficient, λ is the wind turbine tip speed ratio, and β is the wind turbine blade pitch angle. Combining the general frequency response model and the transfer function model of the typical frequency support system for offshore wind power flexible direct current transmission, the frequency response model of the power system with typical frequency support for offshore wind power flexible direct current transmission can be obtained, as shown in Figure 4 As shown, the frequency response characteristics of the system can be expressed as:

[0065]

[0066]

[0067] Among them, ΔG gov (s) is the transfer function of the synchronous generator speed regulator system, which is used as the feedback branch of the frequency response model. R is the frequency regulation coefficient of the synchronous generator speed regulator system, and F HP is the power coefficient of the high-voltage cylinder of the synchronous generator speed regulator system, T G is the rotor action time constant of the synchronous generator speed regulator system, T CH is the time constant of high pressure steam volume effect of synchronous generator speed governor system, T RH is the time constant of the reheat steam volume effect of the synchronous generator governor system.

[0068] Step 2: When the offshore wind turbine receives the instruction to exit the frequency regulation, that is, the offshore wind turbine no longer participates in the frequency regulation of the power grid, the frequency of the offshore wind power flexible direct current system will drop for the second time. The frequency response characteristics of the system are obtained based on the real-time monitored power disturbance signal and the current time delay.

[0069] When the fan exits the frequency modulation, the fan slowly exits the frequency modulation to slow down the secondary drop. The high-order frequency response model of the system can be expressed as:

[0070]

[0071] Among them, T d is the fan response time, K c Slowly exit the frequency regulation parameters for the fan.

[0072] Based on the classical system frequency response model, it can be known that the frequency response under power disturbance can be expressed as a second-order frequency domain model consisting of two real poles or a pair of conjugate complex poles. Therefore, the present invention uses the second-order frequency domain model to reduce the order of the high-order power system frequency response model of the wind turbine slowly exiting the frequency modulation. The reduced-order expression is:

[0073]

[0074] Among them, λ1 and λ2 are the numerator polynomial coefficients of the reduced-order frequency response model, and λ3 and λ4 are the denominator polynomial coefficients of the reduced-order frequency response model.

[0075] Performing an inverse Laplace transform on the reduced-order frequency response model, we can obtain:

[0076]

[0077] Where: Δf(t) is Δf s (s), t is time, α1, α2 and β1, β2 are intermediate variables containing the numerator and denominator polynomial coefficients of the time domain expression of the reduced-order frequency response.

[0078]

[0079] Taking the derivative of Δf(t) and setting it equal to 0, we can get the time t0 corresponding to the lowest frequency point:

[0080]

[0081] Substituting t0 into the time domain expression Δf(t), we can obtain the average frequency change rate RoCoF and the maximum frequency deviation Δf max The function analysis of is:

[0082]

[0083] According to the final value theorem of Laplace transform, the steady-state frequency deviation Δf can be obtained st The function analysis of is:

[0084]

[0085] Therefore, the average frequency change rate RoCoF and the maximum frequency deviation Δf max and the steady-state frequency deviation Δf st can be expressed as a function of λ. λ is the parameter K of the fan slow exit frequency modulation. c is a function of, so RoCoF, Δf max and Δf st It can be expressed as the fan slow exit frequency modulation parameter K c function.

[0086] Step 3: According to the optimization objectives and constraints, the particle swarm algorithm is used to optimize the wind turbine slow exit frequency modulation parameters.

[0087] The single parameter optimization process based on the particle swarm algorithm is as follows:

[0088] Step (3-1) sets the number of particles, initial particle positions, initial particle speeds, inertia weights, particle speed limits, particle position limits, cognitive and social acceleration constants, number of iterations, and convergence conditions.

[0089] The position of the particle represents the solution, and the speed of the particle represents the search speed, which determines the particle's search ability in space. The position and speed of the particle can be expressed as:

[0090] N i,t =[X i,t ,V i,t ,Q i,t ],i=1,2,3,···,N,

[0091]

[0092] Where N is the number of particles, t is the number of iterations, D is the dimension of the particles, X i,t is the position information of the particle. The position information of each particle represents a possible K c Value, x i,t is the position information of the particle in a certain dimension, V i,t is the velocity information of the particle, v i,t is the velocity information of the particle in a certain dimension, Q i,t is the fitness value of the particle.

[0093] Step (3-2) calculates the fitness of the particles and defines the constraints.

[0094] According to step 2, the frequency response characteristics of the power system can be evaluated using three indicators: maximum frequency deviation, frequency change rate, and steady-state frequency deviation. The fitness of the particle can be calculated by the following equation:

[0095] minQ(K c )=η1|RoCoF|+η2|Δf max |+η3|Δf st |;

[0096] Among them, η1, η2 and η3 are weight coefficients ranging from 0 to 1 and η1+η2+η3=1.

[0097] The maximum frequency deviation and the steady-state frequency deviation can characterize the magnitude of the frequency drop. If the frequency drop is too large, the operation of the low-frequency load reduction device will be triggered. Therefore, in order to ensure that the frequency operates within a safe range, the fan slowly exits the frequency modulation parameter K. c The optimization needs to satisfy the constraints of maximum frequency deviation and steady-state frequency deviation, that is:

[0098] Δf st <Δf st,limit ,

[0099] Δf max <Δf max,limit ;

[0100] Where Δf max,limit is the maximum frequency deviation, Δf st,limit is the maximum steady-state frequency deviation value.

[0101] Step (3-3) finds the individual optimal position of each particle and the global optimal position of all particles.

[0102] After completing the fitness calculation of all particles and defining the constraints during initialization, it is necessary to update the individual optimal position of each particle and the global optimal position of all particles. For each particle, if the current fitness Q i,t (K c ) is better than the individual historical optimal fitness of the particle (the fitness value is the smallest), then the individual optimal position is updated, which can be expressed by the following formula:

[0103]

[0104] in, is the optimal position of the individual particle, indicating the optimal K found by a single particle c value, is the historical optimal fitness of individual particles.

[0105] Traverse all particles and determine the particle with the best individual optimal fitness. If the individual optimal fitness of the particle is better than the current global optimal fitness, update the global optimal position, which can be expressed by the following formula:

[0106]

[0107] in, is the global optimal position, indicating the best K found among all particles c value, is the optimal position of the best individual with the best fitness.

[0108] Step (3-4) updates the velocity and position information of each particle.

[0109] The individual optimal fitness Q of each particle i,t (K c ) is when the algorithm is initialized, according to its initial position K c The calculated fitness value. As the algorithm iterates, each particle will move to a new position according to the speed update formula and recalculate the fitness value of the new position. The speed and position information update process of each particle can be described by the following formula:

[0110]

[0111] Among them, V i,t+1 is the updated velocity of particle i at time t+1, v i,t+1 is the updated velocity of particle i at time t+1 in a certain dimension, v i,t is the current velocity of particle i at time t in a certain dimension, w t+1 is the inertia weight, c1 and c2 are cognitive and social acceleration constants, r1 and r2 are random numbers in the range of 0-1, used to simulate the random search process, d = 1, 2, 3, ..., D, x i,t+1 is the updated position of particle i at time t+1 in a certain dimension, x i,t is the current position of particle i at time t in a certain dimension;

[0112] Step (3-5) repeats step (3-2) to step (3-4) until the maximum number of cycles of a single optimization is met or the error converges, and the fan slowly exits the frequency modulation parameter K corresponding to the final global optimal position is obtained. c .

[0113] Step 4: Gradually increase the time delay, repeat steps 2 and 3, and obtain the optimal fan slow exit frequency modulation parameter K under different time delays. c , until the delay reaches the threshold. Starting from the initial delay T0, gradually increase the delay ΔT to search for different delays T d The optimal frequency modulation parameters under the condition of d , do the following:

[0114] Step (4-1) Set the current delay to T d =T0+d*ΔT, where T d is the current latency level.

[0115] Step (4-2) executes steps 2 and 3, that is, calculates the fitness and updates the individual optimum and the global optimum to obtain the optimal solution at the current delay T d The optimal fan slow exit frequency modulation parameter K under c .

[0116] Step (4-3) updates the iteration counter d=d+1 and prepares for the next round of iteration.

[0117] Step 5: Compare all T d The fitness function Q(K c ), and then get the minimum fitness function minQ(K c ), thereby obtaining the optimal time delay and the optimal fan slow exit frequency regulation parameters.

[0118] The present invention proposes a method for optimizing the frequency response secondary drop control of an offshore wind power flexible direct current transmission system. The method comprehensively considers the response time delay and frequency modulation exit mode of the wind turbine, and accurately calculates and determines the optimal wind turbine response time delay and wind turbine slow frequency modulation exit parameters through a particle swarm algorithm, effectively alleviating and avoiding the secondary drop problem of the power grid frequency. The method is simple to operate, efficient in calculation, and has good versatility, and can significantly improve the stability and response performance of the power grid when facing the exit of wind turbine frequency modulation.

[0119] A simulation example is used to verify the effectiveness of the secondary drop method for optimizing the frequency response of the offshore wind power flexible direct current transmission system. Table 1 shows the MATLAB / Simulink simulation parameter design. f0 is the rated frequency of the system in steady state operation; H g is the inertia time constant of the synchronous machine; P L is the maximum disturbance power that may occur in the distribution network system; P PMSG is the installed capacity of the wind farm; P base is the installed capacity of the synchronous machine; v is the wind speed; Δf max,limit Δf is the maximum frequency deviation allowed during the second drop; st,limit is the maximum allowable frequency steady-state deviation; ΔT is the time increment; η1, η2, η3 are the weight coefficients of the optimization objective function.

[0120] Table 1 Simulation parameter design

[0121] <![CDATA[f0=50Hz]]> <![CDATA[H g =6s]]> <![CDATA[P L =1MW]]> <![CDATA[P PMSG =4MW]]> <![CDATA[P base =6MW]]> v=8m / s <![CDATA[Δf max,limit =0.4Hz]]> <![CDATA[Δf st,limit =0.2Hz]]> ΔT=0.05s <![CDATA[η1=0.5]]> <![CDATA[η2=0.2]]> <![CDATA[η3=0.3]]>

[0122] According to step 1, the frequency response transfer function model of the power system with typical frequency support of offshore wind power flexible direct current transmission can be obtained as follows:

[0123]

[0124] According to step 2, the frequency response transfer function model of the power system including the typical frequency support of offshore wind power flexible direct current transmission is reduced in order;

[0125] According to step 3, the initial fan response delay time T0 is set to 0.1s, and the particle swarm algorithm is used for optimization iteration. The number of single iterations is 50 times, and the optimal fan slow exit parameters under the response delay time can be obtained;

[0126] According to step 4, the response delay time increment ΔT is gradually increased until the maximum response delay time is set to 0.5s, and the slow exit parameters and fitness functions of all fans that meet the restriction conditions are obtained;

[0127] According to step 5, compare all delay times T d The fitness function Q(K c ), take the minimum fitness function minQ(Kc ), so that the optimal fan slow exit parameter and fan response delay time under the response delay time can be obtained as: K c =1.2, T d =0.2.

[0128] Figure 5 This is the iterative process of the optimal fan slow exit frequency modulation parameter under the optimal fan response time delay provided by the embodiment of the present invention. The specific simulation results of the method proposed by the present invention are as follows Figure 6 and Figure 7 shown. Figure 6 The frequency change of the grid connection point under the optimal wind turbine slow exit frequency modulation parameters and the optimal wind turbine response delay proposed by the general control method and the present invention is compared; Figure 7 The fan power output is compared between the general control method and the fan power output under the optimal fan slow exit frequency modulation parameters and the optimal fan response delay. The simulation results show that when the fan exits the frequency modulation at 15s, the control strategy proposed by the invention can effectively reduce the secondary frequency drop that may be caused by the fan exiting the frequency modulation.

[0129] The above contents are further detailed descriptions of the present invention in combination with specific / preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, they can also make several substitutions or modifications to these described embodiments without departing from the concept of the present invention, and these substitutions or modifications should be regarded as belonging to the protection scope of the present invention.

[0130] Parts of the present invention that are not described in detail belong to the well-known technologies of those skilled in the art.

Claims

1. A control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system, characterized in that: The steps include: Step 1: mathematically model the typical frequency support system for offshore wind power flexible direct current transmission to obtain a model of the typical frequency support system for offshore wind power flexible direct current transmission, wherein the typical frequency support system for offshore wind power flexible direct current transmission includes a receiving-end converter, a sending-end converter, a machine-side converter, a grid-side converter, a direct-drive wind turbine, a synchronous generator speed regulator system and its additional frequency support control system; Step 2: Calculate the frequency response characteristics of the system based on the established power system frequency response model containing typical frequency support for flexible direct current transmission of offshore wind power; Step 3: Use the particle swarm algorithm to optimize the wind turbine slow exit frequency modulation parameters according to the optimization objectives and constraints; Step 4: gradually increase the time delay, repeat steps 2 and 3, and obtain the optimal wind turbine slow exit frequency modulation parameters under different time delays until the time delay reaches the threshold; Step 5: Compare all T d The fitness function Q(K c ), and obtain the minimum fitness function minQ(K c ), and then get the optimal response time delay T d and the optimal slow exit frequency modulation parameter K c .

2. According to claim 1, a control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system is characterized in that: Step 1: Obtain the unit parameters, control parameters and operating status of the wind farm and synchronous units, model the typical frequency support system of offshore wind power flexible direct current transmission, and obtain the model of the typical frequency support system of offshore wind power flexible direct current transmission, wherein the typical frequency support system of offshore wind power flexible direct current transmission includes a receiving-end converter, a sending-end converter, a machine-side converter, a grid-side converter, a direct-drive wind turbine, a synchronous generator speed regulator system and its additional frequency support control system; The receiving-end converter and the sending-end converter of the conventional frequency support control strategy adopt dual-loop control. The typical frequency support control strategy combines conventional frequency support control and additional frequency support control. This control strategy adds a mapping relationship between the receiving-end converter, DC capacitor and machine-side converter on the basis of the conventional frequency support control strategy, and transmits the frequency disturbance information on the onshore AC power grid to the AC bus side of the offshore wind turbine. At the same time, the frequency regulation control strategy of the direct-drive wind turbine is added to the control of the machine-side converter. After the grid-side converter obtains the frequency information of the offshore wind power AC bus through the phase-locked loop of the wind turbine, the torque command of the machine-side converter is changed to achieve system frequency support. The DC voltage reference value under the additional frequency support control can be obtained by the following formula, namely: U dcref =K1(f-f0)+U dcref0 ; Where f is the onshore AC grid frequency detected by the grid-connected phase-locked loop, f0 is the rated frequency of the system, K1 is the frequency modulation coefficient of the receiving-end converter, and U dcref0 is the DC voltage reference value for conventional frequency support control, U dcref is the DC voltage reference value for typical frequency support control; The frequency reference value of the offshore AC power grid under the additional frequency support control can be obtained by the following formula, namely: f ref =K2(U dc -IN dcref )+f0; Among them, U dc is the voltage of DC transmission, K2 is the frequency modulation coefficient of the converter at the sending end, f ref Frequency reference value of offshore AC bus controlled by conventional frequency support; The reference value of the torque command of the generator-side converter under the additional frequency support control can be obtained by the following formula: T ncmd =T cmd +K3Δf; Among them, Δf is the difference between the system frequency obtained by the grid-side converter phase-locked loop and the rated frequency, K3 is the frequency-torque command frequency modulation coefficient, T cmd is the torque command value of conventional frequency support control, T ncmd It is the torque command value of conventional frequency support control; The additional frequency support control system model can be expressed as: ΔP add (s)=K1*K2*K3*G PMSG (s)*Δf Among them, ΔP add (s) Power support for additional frequency support control systems; In summary, the typical frequency support system model of offshore wind power flexible direct current transmission can be expressed as: Wherein, Δf(s) is the electromagnetic power deviation and system frequency deviation during the frequency response of the power system supported by the typical frequency of offshore wind power flexible direct current transmission, s is the Laplace operator, ΔP is the load disturbance, H is the equivalent inertia constant of the conventional frequency support system of offshore wind power flexible direct current transmission, D is the equivalent damping coefficient of the conventional frequency support system of offshore wind power flexible direct current transmission, G is the equivalent inertia constant of the conventional frequency support system of offshore wind power flexible direct current transmission, PMSG (s) is the transfer function of the output power caused by the change of the fan power torque command value, J w is the moment of inertia of the direct drive fan, ω r0 is the initial value of the direct-drive wind turbine speed, ρ is the air density, r is the radius of the wind turbine blade rotor, v is the wind speed, C P (λ,β) is the wind energy utilization coefficient, λ is the tip speed ratio of the wind turbine, and β is the blade pitch angle of the wind turbine.

3. A control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system according to claim 2, characterized in that: Step 2: For the typical frequency support system of offshore wind power flexible direct current transmission, the system frequency is not only affected by the dynamics of the converter, but also needs to be analyzed in combination with the additional frequency support control system; combining the general frequency response model and the transfer function model of the typical frequency support system of offshore wind power flexible direct current transmission, a power system frequency response model containing the typical frequency support of offshore wind power flexible direct current transmission is established: Where Δf s (s) is the electromagnetic power deviation and system frequency deviation during the frequency response of the power system with typical frequency support for flexible direct current transmission of offshore wind power, s is the Laplace operator, ΔP is the load disturbance, H is the equivalent inertia constant of the offshore wind farm, D is the equivalent damping coefficient of the offshore wind farm, G gov (s) is the transfer function of the synchronous generator speed regulator system, which is the feedback branch of the frequency response model. K1 is the frequency modulation coefficient of the receiving-end converter, K2 is the frequency modulation coefficient of the sending-end converter, K3 is the frequency-torque command frequency modulation coefficient of the machine-side converter, G PMSG (s) is the transfer function of the output power caused by the change of the wind turbine power torque command value, which is regarded as the equivalent speed regulator link of the system and serves as the feedback path of the frequency response model; When considering the response time delay of the fan and the fan exiting the frequency modulation, the fan is slowly exiting the frequency modulation to slow down the secondary drop. The high-order frequency response model of the system when the fan slowly exits the frequency modulation can be expressed as: Among them, T d is the time delay of the fan response, K c Slowly exit the frequency modulation parameters for the fan; When the inverse Laplace transform method is used to solve the high-order frequency response model of the system when the wind turbine slowly exits the frequency modulation, it is difficult to obtain a specific function analytical expression; therefore, the system model reduction method is used to reduce the high-order frequency response model of the system when the wind turbine slowly exits the frequency modulation power to a second-order frequency response system; then when the wind turbine slowly exits, the system's average frequency change rate RoCoF and maximum frequency deviation Δf max and the steady-state frequency deviation Δf st can be expressed as c function.

4. A control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system according to claim 3, characterized in that: The high-order power system frequency response model of wind turbines slowly exiting frequency regulation is reduced in order with the help of the second-order frequency domain model. The reduced-order expression is: Among them, λ1 and λ2 are the numerator polynomial coefficients of the reduced-order frequency response model, and λ3 and λ4 are the denominator polynomial coefficients of the reduced-order frequency response model; Performing an inverse Laplace transform on the reduced-order frequency response model, we can obtain: Where: Δf(t) is Δf s (s) is a time domain expression, t is time, α1, α2 and β1, β2 are intermediate variables containing the coefficients of the numerator and denominator polynomials of the time domain expression of the reduced-order frequency response; Taking the derivative of Δf(t) and setting it equal to 0, we can get the time t0 corresponding to the lowest frequency point: Substituting t0 into the time domain expression Δf(t), we can obtain the average frequency change rate RoCoF and the maximum frequency deviation Δf max The function analysis of is: According to the final value theorem of Laplace transform, the steady-state frequency deviation Δf can be obtained st The function analysis of is: Therefore, the average frequency change rate RoCoF and the maximum frequency deviation Δf max and the steady-state frequency deviation Δf st can be expressed as a function of λ; λ is the parameter K of the fan slow exit frequency modulation. c is a function of, so RoCoF, Δf max and Δf st It can be expressed as the fan slow exit frequency modulation parameter K c function.

5. The control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system according to claim 3 is characterized in that: The fitness of a particle is calculated by the following equation: minQ(K c )=η1|RoCoF|+η2|Δf max |+η3|Δf st |; Among them, η1, η2 and η3 are weight coefficients, ranging from 0 to 1 and η1+η2+η3=1; The fan slowly exits the frequency modulation parameter K c The optimization needs to satisfy the constraints of maximum frequency deviation and steady-state frequency deviation, that is: Δf st <Δf st,limit , Δf max <Δf max,limit ; Where Δf max,limit is the maximum frequency deviation, Δf st,limit is the maximum steady-state frequency deviation value.

6. A control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system according to claim 5, characterized in that: The single parameter optimization process based on the particle swarm algorithm is as follows: Step (3-1) setting the number of particles, particle initial position, particle initial velocity, inertia weight, particle velocity limit, particle position limit, cognitive and social acceleration constants, number of iterations and convergence conditions; The position of the particle represents the solution, and the speed of the particle represents the search speed. Both determine the particle's search ability in space. The position and speed of the particle can be expressed as: N i,t =[X i,t ,V i,t ,Q i,t ],i=1,2,3,···,N, Where N is the number of particles, t is the number of iterations, D is the dimension of the particles, X i,t is the position information of the particle. The position information of each particle represents a possible K c Value, x i,t is the position information of the particle in a certain dimension, V i,t is the velocity information of the particle, v i,t is the velocity information of the particle in a certain dimension, Q i,t is the fitness value of the particle; Step (3-2) calculates the fitness of the particle and defines the constraints; According to step 2, the frequency response characteristics of the power system can be evaluated using three indicators: maximum frequency deviation, frequency change rate, and steady-state frequency deviation; the fitness of the particle can be calculated by the following equation: min Q(K c )=η1|RoCoF|+η2|Δf max |+η3|Δf st |; Wherein, η1, η2 and η3 are weight coefficients ranging from 0 to 1 and η1+η2+η3=1; The fan slowly exits the frequency modulation parameter K c The optimization needs to satisfy the constraints of maximum frequency deviation and steady-state frequency deviation, that is: Δf st <Δf st,limit , Δf max <Δf max,limit ; Where Δf max,limit is the maximum frequency deviation, Δf st,limit is the maximum steady-state frequency deviation value; Step (3-3) finds the individual optimal position of each particle and the global optimal position of all particles; After completing the fitness calculation of all particles and defining the constraints during initialization, it is necessary to update the individual optimal position of each particle and the global optimal position of all particles; for each particle, if the current fitness Q i,t (K c ) is better than the individual historical optimal fitness of the particle, then the individual optimal position is updated, which can be expressed by the following formula: in, is the optimal position of the individual particle, indicating the optimal K found by a single particle c value, is the historical optimal fitness of individual particles; Traverse all particles and determine the particle with the best individual optimal fitness. If the individual optimal fitness of the particle is better than the current global optimal fitness, update the global optimal position, which can be expressed by the following formula: in, is the global optimal position, indicating the best K found among all particles c value, The optimal position for the best individual's optimal fitness; Step (3-4) updates the speed and position information of each particle; The individual optimal fitness Q of each particle i,t (K c ) is when the algorithm is initialized, according to its initial position K c The calculated fitness value; as the algorithm iterates, each particle will move to a new position according to the speed update formula and recalculate the fitness value of the new position; the speed and position information update process of each particle can be described by the following formula: Among them, V i,t+1 is the updated velocity of particle i at time t+1, v i,t+1 is the updated velocity of particle i at time t+1 in a certain dimension, v i,t is the current velocity of particle i at time t in a certain dimension, w t+1 is the inertia weight, c1 and c2 are cognitive and social acceleration constants, r1 and r2 are random numbers in the range of 0-1, used to simulate the random search process, d = 1, 2, 3, ..., D, x i,t+1 is the updated position of particle i at time t+1 in a certain dimension, x i,t is the current position of particle i at time t in a certain dimension; Step (3-5) repeats step (3-2) to step (3-4) until the maximum number of cycles of a single optimization is met or the error converges, and the fan slowly exits the frequency modulation parameter K corresponding to the final global optimal position is obtained. c .

7. A control method for optimizing the secondary drop of frequency response of an offshore wind power flexible direct current system according to claim 5 or 6, characterized in that: Step 4: During the system frequency modulation parameter optimization process, an initial fan response time delay T0 is first set, and then the delay value is gradually increased at a fixed time interval ΔT to search for different response time delays T0. d In each iteration, we look for the optimal slow exit parameter K. c , to determine which parameter can provide the best system frequency response secondary drop and system stability under the current delay; After each round of iteration, the iteration counter d is updated to increase by 1, the time delay value is updated, and the next round of parameter optimization is prepared until the time delay reaches the threshold, that is: T d =T0+d*ΔT; Where d is the number of iterations, T0 is the initial fan delay response time, and ΔT is the time increment.

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