Damping control method and damping control system for grid-connected pumped storage-wind power generation interconnection system

Abstract

The present invention belongs to the field of damping control, and specifically discloses a damping control method and a damping control system of a grid-connected pumped storage-wind power generation interconnection system, which includes: a dual damping controller captures the unit speed signal of the grid-connected pumped storage-wind power generation interconnection system, and feeds back the output voltage signal to perform damping control on the grid-connected pumped storage-wind power generation interconnection system; the dual damping controller includes a shaft damping controller for controlling the wind power generator set, and an excitation damping controller for controlling the pumped storage unit; the parameter determination method of the dual damping controller is: constructing a fitness function based on the deviation between the unit speed and a preset reference value after applying a disturbance, constructing an optimization model with the minimum fitness function value as the optimization target, and solving the optimization model to obtain the dual damping controller parameters. The dual damping controller of the present invention can enhance the stability and damping characteristics of the grid-connected pumped storage-wind power generation interconnection system, and effectively suppress low-frequency oscillations.

Description

Technical Field

[0001] The present invention belongs to the field of damping control, and more specifically, relates to a damping control method and a damping control system of a grid-connected pumped storage-wind power generation interconnection system. Background Art

[0002] The grid-connected pumped storage-wind power generation interconnection system has the advantages of complementary power and frequency. However, the uncertainty and unique dynamic characteristics of wind power generation have brought new challenges to large-scale penetration. The low inertia and short-circuit strength of the converter interface, the small stability margin and control interaction greatly weaken the stability of the power grid. The unreasonable setting of the speed regulator parameters and the long-distance transmission of electricity make the low-frequency oscillation phenomenon of the new energy power system occur frequently. Solving the low-frequency oscillation problem is of great significance to the safe and stable operation of the grid-connected pumped storage-wind power generation interconnection system.

[0003] The existing grid-connected pumped storage-wind power generation interconnection system damping controller is mainly designed for wind power generation, pumped storage power generation and conventional power system low-frequency oscillation suppression. No efficient damping enhancement method for the pumped storage-wind power generation interconnection system has been proposed, and no research on the dual damping controller of the shaft system and excitation has been carried out. In addition, the existing optimization algorithms inevitably have the disadvantages of local optimality, poor optimization efficiency and convergence speed. Therefore, it is urgent to improve the existing optimization algorithms to realize the dual damping control of the shaft system and excitation and solve the above problems. Summary of the invention

[0004] In view of the above defects or improvement needs of the prior art, the present invention provides a damping control method and a damping control system for a grid-connected pumped storage-wind power generation interconnection system, the purpose of which is to enhance the damping performance of the grid-connected pumped storage-wind power generation interconnection system and suppress the low-frequency oscillation of the system.

[0005] To achieve the above object, according to one aspect of the present invention, a damping control method for a grid-connected pumped storage-wind power generation interconnection system is proposed, comprising the following steps:

[0006] The dual damping controller captures the unit speed signal of the grid-connected pumped storage-wind power generation interconnection system, and then feeds back the output voltage signal to perform damping control on the grid-connected pumped storage-wind power generation interconnection system;

[0007] The dual damping controller includes a shaft damping controller for controlling the wind turbine generator set, and an excitation damping controller for controlling the pumped storage unit;

[0008] The parameter determination method of the dual damping controller is as follows: constructing a fitness function based on the deviation between the unit speed and a preset reference value after the disturbance is applied, constructing an optimization model with the minimum fitness function value as the optimization target, and solving the optimization model to obtain the dual damping controller parameters.

[0009] As a further preferred embodiment, the expression of the shaft system damping controller is:

[0010]

[0011] Among them, ω r is the speed signal of the wind turbine generator set, K s1 is the gain of the shaft damping controller amplification link, T 10 is the filter time constant of the shaft damping controller, T 11 and T 12 is the time constant of the lead-lag compensation link of the shaft damping controller, V 11 is the intermediate variable of the shaft damping controller, V PSS1 is the output voltage of the shaft damping controller, ω t is the wind turbine speed, T t is the mechanical torque of the wind turbine, T e is the electromagnetic torque of the wind turbine, H t and H g is the inertia constant of the wind turbine and generator, θ sh is the wind turbine shaft torsion angle, K sh and D sh is the wind turbine shaft stiffness coefficient and damping coefficient, ω b is the reference angular velocity, t is the time;

[0012] The expression of the excitation damping controller is:

[0013]

[0014] Among them, x t is the speed signal of the pumped storage unit, K s2 is the gain of the excitation damping controller amplifier, T 20 is the time constant of the filter link of the excitation damping controller, T 21 and T 22 is the time constant of the lead-lag compensation link of the excitation damping controller, V 21 is the intermediate variable of the excitation damping controller, V PSS2 is the output voltage of the excitation damping controller, E fd is the excitation system voltage, K A is the gain of the excitation system amplification link, T A is the time constant of the excitation system, V g and V grefis the voltage and reference value of the pumped storage unit.

[0015] As a further preferred embodiment, the shaft damping controller captures the wind turbine generator speed signal ω r , feedback output voltage signal V PSS1 The excitation damping controller captures the speed signal x of the pumped storage unit and transmits it to the shaft system of the wind turbine generator set for damping control; t , feedback output voltage signal V PSS2 Transmitted to the pumped storage unit excitation system for damping control; the dual damping controller parameters to be determined include K s1 ,T 10 ,T 11 ,T 12 ,K s2 ,T 20 ,T 21 and T 22 .

[0016] As a further preferred embodiment, the fitness function Fit is:

[0017] Fit=∫|ω r -ω rref |+|x t -x tref |dt

[0018] Among them, ω r ,ω rref are the wind turbine speed signal and the preset reference value, respectively, t 、x tref are the speed signal of the pumped storage unit and the preset reference value respectively, and t is the time.

[0019] As a further preferred embodiment, a sparrow search algorithm is used to solve the optimization model to obtain the dual damping controller parameters.

[0020] As a further preferred embodiment, when the sparrow search algorithm is used to solve the optimization model, the observer position is updated by a random walk strategy in each iteration.

[0021] As a further preferred method, updating the observer position by a random walk strategy includes the following steps:

[0022] Define the dispersion factor, expressed as:

[0023]

[0024] Among them, DF T is the dispersion factor at the Tth iteration, T max is the maximum number of iterations;

[0025] Calculate the distance traveled by a random walk based on the dispersion factor:

[0026]

[0027] Among them, R iT is the distance advanced by the ith observer at the Tth iteration, X iT is the position of the ith observer at the Tth iteration, and rand is a random number between 0 and 1;

[0028] Then update the observer's position according to the forward distance, that is, let X iT =X iT +R iT .

[0029] As a further preferred embodiment, when the sparrow search algorithm is used to solve the optimization model, the golden sine strategy is used to update the position of the worst particle in each iteration, that is, the particles with the largest fitness function value in the current iteration are updated.

[0030] As a further preferred method, the golden sine strategy is used to update the worst particle position, including:

[0031] Introducing the golden ratio x 1 、x 2 , expressed as:

[0032]

[0033] Among them, a and b are the initial search values ​​of the golden section, and τ is the golden section ratio;

[0034] Update the worst particle position based on the golden ratio:

[0035]

[0036] Among them, V mj T is the jth parameter of the mth worst particle at the Tth iteration position, r 1 is a random number between 0 and 2π, r 2 is a random number between 0 and π, D j T is the jth parameter at the optimal position in the Tth iteration.

[0037] According to another aspect of the present invention, a damping control system is provided, which includes a processor, wherein the processor is used to execute the damping control method of the above-mentioned grid-connected pumped storage-wind power generation interconnection system.

[0038] In general, the above technical solution conceived by the present invention has the following technical advantages compared with the prior art:

[0039] 1. The dual damping controller designed in the present invention takes the speed as input and the voltage as output. The speed control signal of the generator set is easy to obtain, and the voltage feedback signal is directly transmitted to the generator set. The damping control has high timeliness and speed, which significantly improves the regulation quality and response speed of the units in the grid-connected pumped storage-wind power generation interconnection system. The dual damping controller can enhance the damping performance and stability of the grid-connected pumped storage-wind power generation interconnection system, effectively suppress low-frequency oscillations, ensure the safe and stable operation of the power system, and has good mobility.

[0040] 2. The shaft system and excitation dual damping controller designed in the present invention can improve the speed regulation quality of pumped storage units and wind turbines, and ensure the safe operation of the power grid.

[0041] 3. The present invention optimizes the design of the shaft system and excitation dual damping controller by improving the sparrow search algorithm. The global search performance of the sparrow search optimization algorithm improved by integrating random walk and golden sine strategies is significantly improved, and it has a faster convergence speed and better optimization results.

[0042] 4. The present invention utilizes the shaft system and excitation dual damping controller optimized by the fitness function using the integral of the speed deviation of wind power generation and pumped storage units, which can effectively improve the damping performance of the grid-connected pumped storage-wind power interconnection subsystem and has a certain robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of a damping control method for a grid-connected pumped storage-wind power generation interconnection system provided by an embodiment of the present invention;

[0044] Figure 2 A topological diagram of a grid-connected pumped storage-wind power generation interconnection system with a dual damping controller provided in an embodiment of the present invention;

[0045] Figure 3 A flow chart of determining parameters of a dual damping controller based on an improved sparrow search algorithm provided by an embodiment of the present invention;

[0046] Figure 4 (a) and (b) are comparison diagrams of the dynamic response process of the speed of the pumped storage and wind turbine generator set before and after the dual damping controller provided by the embodiment of the present invention acts;

[0047] Figure 5 (a) and (b) are comparison diagrams of the dynamic response process of the speed of the pumped storage and wind turbine generator set before and after the action of the dual damping controller with the improved sparrow search algorithm optimized design provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0049] The embodiment of the present invention provides a damping control method for a grid-connected pumped storage-wind power generation interconnection system, such as Figure 1 As shown, the following steps are included:

[0050] (1) Design a dual damping controller for the grid-connected pumped storage-wind power generation interconnection system.

[0051] The dual damping controller captures the speed signal of the grid-connected pumped storage-wind power generation interconnection system unit as the control signal, and feeds back the output voltage signal to perform damping control on the pumped storage unit and the wind turbine generator set, thereby suppressing system oscillation.

[0052] Specifically, the grid-connected pumped storage-wind power generation interconnection system includes a pumped storage unit and a wind turbine generator set; the dual damping controller includes a shaft damping controller for controlling the wind turbine generator set and an excitation damping controller for controlling the pumped storage unit. The topology is as follows: Figure 2 shown.

[0053] Furthermore, the shaft damping controller model is:

[0054]

[0055] Among them, ω r is the wind turbine speed signal, K s1 is the gain of the shaft damping controller amplification link, T 10 is the filter time constant of the shaft damping controller, T 11 and T 12 is the time constant of the lead-lag compensation link of the shaft damping controller, V 11 is the intermediate variable of the shaft damping controller, V PSS1 is the output voltage of the shaft damping controller, ω t is the wind turbine speed, T t is the mechanical torque of the wind turbine, T e is the electromagnetic torque of the wind turbine, H t and H g is the inertia constant of the wind turbine and generator, θ sh is the wind turbine shaft torsion angle, K sh and D sh is the wind turbine shaft stiffness coefficient and damping coefficient, ω bis the base angular velocity.

[0056] The excitation damping controller model is:

[0057]

[0058] Among them, x t is the speed signal of the pumped storage unit, K s2 is the gain of the excitation damping controller amplifier, T 20 is the time constant of the filter link of the excitation damping controller, T 21 and T 22 is the time constant of the lead-lag compensation link of the excitation damping controller, V 21 is the intermediate variable of the excitation damping controller, V PSS2 is the output voltage of the excitation damping controller, E fd is the excitation system voltage, K A is the gain of the excitation system amplification link, T A is the time constant of the excitation system, V g and V gref is the voltage and reference value of the pumped storage unit.

[0059] The shaft damping controller captures the wind turbine generator speed signal ω r , feedback output voltage signal V PSS1 The excitation damping controller captures the speed signal x of the pumped storage unit. t , feedback output voltage signal V PSS2 Transmitted to the pumped storage unit excitation system for damping control.

[0060] (2) Determine the parameters of the dual damping controller.

[0061] The integral of the unit speed deviation is used as the fitness function, and the optimization model is constructed with the minimum fitness function value as the optimization target. The optimization model is solved to obtain the dual damping controller parameters; the dual damping controller parameters that need to be determined include K s1 ,T 10 ,T 11 ,T 12 ,K s2 ,T 20 ,T 21 and T 22 .

[0062] Furthermore, the random walk strategy and the golden sine strategy are introduced to improve the sparrow search algorithm, and the parameters of the dual damping controller are obtained by solving the optimization model through the improved sparrow search algorithm. Figure 3 As shown, the specific steps include:

[0063] Step 1: Initialize the population, number of iterations, sparrow search algorithm and other related parameters, and initialize the grid-connected pumped storage-wind power generation interconnection system parameters. Specifically, one particle in the population corresponds to a set of controller parameters (K s1 ,T 10 ,T 11 ,T 12 ,K s2 ,T 20 ,T 21 ,T 22 ); Initialize multiple particles and divide them into explorers, followers, and observers in advance.

[0064] Step 2: According to the update method of explorers and followers in the traditional sparrow search algorithm, update the positions of explorers and followers, and calculate the fitness accordingly; according to the update method of observers in the traditional sparrow search algorithm, update the observer position, and then update the observer position based on the random walk strategy, and calculate the fitness accordingly.

[0065] Step 3: Sort the fitness of all particles from small to large, update the worst positions of several sparrows in the population (i.e., the worst particles with the largest fitness, 5 in this embodiment) based on the golden sine strategy, and recalculate the fitness; update and save the global optimal fitness value and the corresponding optimal position.

[0066] Step 4: Determine whether the iteration conditions are met. If so, output the optimal fitness and the optimal dual damping controller parameters; if not, return to step 2.

[0067] Furthermore, in the above process, for any particle, the fitness is calculated as follows:

[0068] Substitute the dual damping controller parameters corresponding to the particle into the grid-connected pumped storage-wind power generation interconnection system, and preset the unit speed reference value (the preset reference value of the wind turbine speed ω rref and the preset reference value x of the pumped storage unit speed tref );

[0069] Apply disturbance to the system and obtain dynamic response data of the unit speed. In this embodiment, a three-phase short-circuit grounding fault is applied, the fault is removed after 0.1s, and the simulation is calculated to 10s. The state variable equation is solved by the ode15s function of MATLAB, and the speed x of the pumped storage unit is saved. t and wind turbine speed ω r Dynamic response data;

[0070] Solve the speed deviation integral of the pumped storage unit and the wind turbine generator set to obtain the fitness Fit.

[0071] Specifically, the fitness function is the sum of the integral of the wind turbine speed, the pumped storage unit speed and the preset reference value deviation, expressed as: Fit = ∫|ω r -ω rref |+|x t -x tref |dt.

[0072] Furthermore, the random walk strategy is used to update the observer's alert search range, and a dispersion factor is defined to control the observer's dispersion during the search process to improve the exploitation capability of the original sparrow search algorithm.

[0073] The dispersion factor is defined as:

[0074]

[0075] Among them, DF T is the dispersion factor at the Tth iteration, T max is the maximum number of iterations; the forward distance of the random walk is calculated according to the dispersion factor, and the expression is:

[0076]

[0077] Among them, R iT is the distance advanced by the ith observer at the Tth iteration, X iT is the parameter of the ith observer particle at the Tth iteration, and rand is a random number between 0 and 1;

[0078] The updated observer particle is:

[0079] X iT =X iT +R iT

[0080] Furthermore, the golden sine strategy is used to strengthen the global search and enrich the diversity of solutions.

[0081] The golden sine strategy introduces the golden ratio coefficient x 1 ,x 2 , so that search and development achieve the best balance, can be expressed as:

[0082]

[0083] Among them, a and b are the initial search values ​​of the golden section, and τ is the golden section ratio;

[0084] The golden sine algorithm is used to update the worst position, which can be expressed as:

[0085]

[0086] Among them, V mjT is the jth parameter of the mth worst particle at the Tth iteration position, r 1 is a random number between 0 and 2π, r 2 is a random number between 0 and π, D j T is the jth parameter of the optimal position in the Tth iteration (i.e., the particle position with the smallest fitness value in the current iteration).

[0087] A damping control system provided in an embodiment of the present invention includes a processor, wherein the processor is used to execute the damping control method of the above-mentioned grid-connected pumped storage-wind power generation interconnection system.

[0088] In order to clarify the regulation quality of the grid-connected pumped storage-wind power generation interconnection system under the action of the shaft system and excitation dual damping controller, the state variable equation is simulated in the time domain by the ode15s function of MATLAB software, and the dynamic characteristics of the grid-connected pumped storage-wind power generation interconnection system before and after the action of the controller are compared and analyzed. Figure 4 As shown, before the controller takes effect, there is no additional damping control on the shaft system and the excitation system in the grid-connected pumped storage-wind power generation interconnection system.

[0089] See also Figure 4 It can be seen that before the dual damping controller of shaft system and excitation is applied, the grid-connected pumped storage-wind power generation interconnection system shows obvious low-frequency oscillation phenomenon, and the speed oscillation amplitude of wind turbines and pumped storage units is large, and it takes a long time to adjust to restore to a stable state. After the dual damping controller of shaft system and excitation is introduced (the parameters of the controller are set according to experience), the low-frequency oscillation of the grid-connected pumped storage-wind power generation interconnection system is significantly suppressed, the dynamic response process converges quickly, and the oscillation amplitude is significantly reduced. This result shows that the dual damping controller of shaft system and excitation can effectively eliminate the low-frequency oscillation phenomenon of the grid-connected pumped storage-wind power generation interconnection system, making it converge quickly into a steady state, and the system stability and damping characteristics are significantly improved.

[0090] In order to further prove the optimization effect of the shaft system and excitation dual damping controller designed by the improved sparrow search algorithm on the speed regulation quality of the grid-connected pumped storage-wind power generation interconnection system, the state variable equation is simulated in the time domain by the ode15s function of MATLAB software, and compared with the conventional sparrow search algorithm. The three-phase short-circuit grounding fault is applied and removed after 0.1s. The dynamic response of the speed of the pumped storage unit and the wind turbine generator set is as follows Figure 5 shown.

[0091] See also Figure 5It can be seen that the shaft system and excitation dual damping controller optimized by the improved sparrow search algorithm can make the speed oscillation amplitude of wind turbines and pumped storage units smaller than that of the shaft system and excitation dual damping controller optimized by the traditional sparrow search algorithm, and restore to a stable state in a shorter time, significantly suppressing the low-frequency oscillation of the grid-connected pumped storage-wind power generation interconnection system, and improving the dynamic regulation quality of the unit speed.

[0092] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A damping control method for a grid-connected pumped storage-wind power generation interconnection system, characterized in that: The steps include: The dual damping controller captures the unit speed signal of the grid-connected pumped storage-wind power generation interconnection system, and then feeds back the output voltage signal to perform damping control on the grid-connected pumped storage-wind power generation interconnection system; The dual damping controller includes a shaft damping controller for controlling the wind turbine generator set, and an excitation damping controller for controlling the pumped storage unit; The expression of the shaft damping controller is: Among them, ω r is the speed signal of the wind turbine generator set, K s1 is the gain of the shaft damping controller amplification link, T 10 is the filter time constant of the shaft damping controller, T 11 and T 12 is the time constant of the lead-lag compensation link of the shaft damping controller, V 11 is the intermediate variable of the shaft damping controller, V PSS1 is the output voltage of the shaft damping controller, ω t is the wind turbine speed, T t is the mechanical torque of the wind turbine, T e is the electromagnetic torque of the wind turbine, H t and H g is the inertia constant of the wind turbine and generator, θ sh is the wind turbine shaft torsion angle, K sh and D sh is the wind turbine shaft stiffness coefficient and damping coefficient, ω b is the reference angular velocity, t is the time; The expression of the excitation damping controller is: Among them, x t is the speed signal of the pumped storage unit, K s2 is the gain of the excitation damping controller amplification link, T 20 is the time constant of the filter link of the excitation damping controller, T 21 and T 22 is the time constant of the lead-lag compensation link of the excitation damping controller, V 21 is the intermediate variable of the excitation damping controller, V PSS2 is the output voltage of the excitation damping controller, E fd is the excitation system voltage, K A is the gain of the excitation system amplification link, T A is the time constant of the excitation system, V g and V gref is the voltage and reference value of the pumped storage unit; The parameter determination method of the dual damping controller is as follows: constructing a fitness function based on the deviation between the unit speed and a preset reference value after the disturbance is applied, constructing an optimization model with the minimum fitness function value as the optimization target, and solving the optimization model using a sparrow search algorithm to obtain the dual damping controller parameters; When the sparrow search algorithm is used to solve the optimization model, the observer position is updated through a random walk strategy in each iteration, including: Define the dispersion factor, expressed as: Among them, DF T is the dispersion factor at the Tth iteration, T max is the maximum number of iterations; Calculate the distance traveled by a random walk based on the dispersion factor: Among them, R iT is the distance advanced by the ith observer at the Tth iteration, X iT is the position of the ith observer at the Tth iteration, and rand is a random number between 0 and 1; Then update the observer's position according to the forward distance, that is, let X iT =X iT +R iT ; When the sparrow search algorithm is used to solve the optimization model, the golden sine strategy is used to update the position of the worst particle in each iteration, that is, to update the particles with the largest fitness function value in the current iteration, including: Introducing the golden section coefficients x1 and x2, expressed as: Among them, a and b are the initial search values ​​of the golden section, and τ is the golden section ratio; Update the worst particle position based on the golden ratio: Among them, V mj T is the jth parameter of the mth worst particle at the Tth iteration position, r1 is a random number between 0 and 2π, r2 is a random number between 0 and π, D j T is the jth parameter at the optimal position in the Tth iteration.

2. The damping control method of the grid-connected pumped storage-wind power generation interconnection system according to claim 1, characterized in that: The shaft damping controller captures the wind turbine speed signal ω r , feedback output voltage signal V PSS1 The excitation damping controller captures the speed signal x of the pumped storage unit and transmits it to the shaft system of the wind turbine generator set for damping control; t , feedback output voltage signal V PSS2 Transmitted to the pumped storage unit excitation system for damping control; the dual damping controller parameters to be determined include K s1 ,T 10 ,T 11 ,T 12 ,K s2 ,T 20 ,T 21 and T 22 .

3. The damping control method of the grid-connected pumped storage-wind power generation interconnection system according to claim 1, characterized in that: The fitness function Fit is: Fit=∫|ω r -ω rref |+|x t -x tref |dt Among them, ω r ,ω rref are the wind turbine speed signal and the preset reference value, respectively, t 、x tref are the speed signal of the pumped storage unit and the preset reference value respectively, and t is the time.

4. A damping control system, characterized in that: It includes a processor, which is used to execute the damping control method of the grid-connected pumped storage-wind power generation interconnection system as described in any one of claims 1-3.

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