Ultra-low frequency oscillation suppression method based on oscillation source positioning

Abstract

The invention provides an ultra-low frequency oscillation suppression method based on oscillation source positioning, and relates to the technical field of power system stabilization and control. The method comprises the following steps: performing oscillation mode decomposition on each hydroelectric generating set generator in the wind-water storage system; the calculated oscillation energy is determined as a unit of an oscillation source; the acceleration power of the oscillation source is selected as the output of the wind-water storage system, and the wind storage output is used as the input; identifying a transfer function matrix of the wind-water storage system; an additional controller is arranged on the wind storage side, the acceleration power of the oscillation source serves as input of the additional controller, and a transfer function matrix of the additional controller is obtained through calculation based on the transfer function matrix of the wind-water storage system; and the output obtained through calculation according to the transfer function matrix of the additional controller is added to the wind storage constant power side, and ultra-low frequency oscillation suppression is achieved. According to the method, the flexible and adjustable performance advantage of wind storage can be fully utilized, and the utilization rate of auxiliary service resources and the suppression effect on ultra-low frequency oscillation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system stability and control, and in particular to a method for suppressing ultra-low frequency oscillation based on oscillation source positioning. Background Art

[0002] Large power grid systems with a high proportion of hydropower, such as isolated hydropower DC islands or asynchronously interconnected systems, are at serious risk of ultra-low frequency oscillations. For example, an ultra-low frequency oscillation with an oscillation period of about 20s occurred in an asynchronous interconnection experiment of a local power grid, which lasted for half an hour. Ultra-low frequency oscillations are different from traditional low-frequency oscillations and are mainly mechanical power oscillations. Most of the existing measures to suppress ultra-low frequency oscillations are based on hydropower units, such as adjusting the speed regulator parameters of hydropower units, optimizing the speed regulation parameters using deep learning or particle swarm algorithms, and increasing damping. However, this method reduces the primary frequency regulation performance of the hydropower unit, increasing the incidence of system frequency limit violations under large disturbances.

[0003] During the large-scale grid connection of wind power, the random volatility of wind turbine output further worsens the frequency stability problem of the power grid. The difference between wind power inertia and traditional synchronous machine inertia leads to a further reduction in the inertia of the power grid, increasing the risk of ultra-low frequency oscillation. Energy storage access can solve the problem of unstable wind turbine output. The wind storage system has a fast dynamic adjustment capability. Adding reasonable additional damping control on the wind storage side can suppress ultra-low frequency oscillation. However, existing ultra-low frequency oscillation suppression measures mostly use frequency as a reference signal, without combining the oscillation source signal, resulting in low utilization of auxiliary service resources. Summary of the invention

[0004] In order to solve the above-mentioned technical problems existing in the prior art, for a high-proportion hydropower system with wind-storage access, the present invention aims to provide a method for suppressing ultra-low frequency oscillations by involving a wind-storage system and combining oscillation source positioning.

[0005] Specifically, the present invention provides an ultra-low frequency oscillation suppression method with oscillation source positioning, which is used to suppress ultra-low frequency oscillation of a wind and water storage system, wherein the wind and water storage system includes a wind turbine connected by a busbar, energy storage and at least two hydropower turbines.

[0006] The technical solution specifically includes the following steps:

[0007] Step S1: performing oscillation mode decomposition on each hydropower unit in the wind and water storage system, and decomposing the speed curve data or mechanical power curve data of the corresponding generator;

[0008] Select the ultra-low frequency oscillation mode to calculate the oscillation energy, and determine the unit as the oscillation source according to the oscillation energy;

[0009] Step S2: taking the acceleration power of the oscillation source as the output of the Feng Shui storage system, i.e., the first output; taking the wind turbine output and the energy storage output as the input of the Feng Shui storage system; wherein the acceleration power is specifically the acceleration power of each of the two oscillation sources with the largest oscillation energy;

[0010] The transfer function matrix of the Feng Shui storage system is identified, that is, the first transfer function matrix;

[0011] Step S3: an additional controller is set on the wind storage side, and the acceleration power is used as input; based on the hybrid robust control theory and the first transfer function matrix, a transfer function matrix of the additional controller is calculated, that is, a second transfer function matrix;

[0012] The output of the additional controller, i.e., the second output, is obtained by calculation according to the second transfer function matrix;

[0013] The second output is added to the fixed power side of the wind turbine and the fixed power side of the energy storage respectively, the output of the wind turbine is adjusted to the additional power command value of the wind turbine, and the output of the energy storage is adjusted to the additional power command value of the energy storage, so as to realize ultra-low frequency oscillation suppression.

[0014] Preferably, step S1 specifically includes:

[0015] Step S11: Establishing a sampling signal Y based on the speed deviation curve or mechanical power curve of the generator,

[0016] Y=[x(0),x(1),...x(i),...,x(N-1)] T ;

[0017] Where i is the sampling point number, x(i) is the data value of the i-th sampling point, N is the number of sampling points, i=0,1,...,N-1, T represents transposition;

[0018] Step S12: constructing an augmented Hankel matrix according to the sampled signal Y; performing singular value decomposition on the augmented Hankel matrix to obtain a signal subspace;

[0019] Step S13: Find the K eigenvalues ​​of the optimal matrix of the signal subspace by the least square method to generate the optimal matrix λ.

[0020]

[0021] In the formula, is the i-th power of the k-th eigenvalue of the optimal matrix, k = 1, 2, ..., K;

[0022] For the oscillation mode, we have

[0023]

[0024] c=[c1 c2 … c k ] T =(λ T λ) -1 λ T Y;

[0025] In the formula, ω k is the angular frequency of the oscillation mode, T s is the period of the sampling signal Y, σ k is the exponential decay factor of the oscillation mode, c is c k The transposed matrix of the set, c k is the product of the amplitude of the oscillation mode signal and the phase rotation factor;

[0026] Step S14: Select an oscillation mode with an oscillation frequency less than a preset frequency, that is, an ultra-low frequency oscillation mode, and calculate the oscillation energy.

[0027]

[0028] ΔE m (k) = ∫ΔP mk Δω k dt;

[0029] In the formula, ΔP mk is the mechanical power signal under the ultra-low frequency oscillation mode, Δω k is the speed deviation signal of the generator in the ultra-low frequency oscillation mode, n is the sampling point number, n=1,2,...,N, ΔE m (k) is the oscillation energy in the ultra-low frequency oscillation mode;

[0030] If ΔE m (k)>0, the corresponding unit is an oscillation source.

[0031] Preferably, the preset frequency is 0.1 Hz.

[0032] Preferably, step S2 specifically includes:

[0033] Step S21: applying power step disturbances to the two oscillation sources with the largest oscillation energy respectively, and performing oscillation mode decomposition; performing Laplace transform on the decomposition results, and dividing them by the Laplace transform results of the power step disturbance, to obtain the corresponding transfer function;

[0034] Step S22: Combining all transfer functions into a first transfer function matrix,

[0035]

[0036] Where s is the Laplace operator, y1(s) and y2(s) are the outputs of the wind-water storage system, i.e., the acceleration power of the two oscillating sources; u1(s) and u2(s) are the inputs of the wind-water storage system, i.e., the wind turbine additional power command value and the energy storage additional power command value; G fg (s) is u g (s) to y f The transfer function of (s), f∈[1,2], g∈[1,2].

[0037] Preferably, the rotation speed curve data and the mechanical power curve data of the generator are decomposed based on a least squares-rotational invariant technique algorithm.

[0038] Preferably, the transfer function matrix of the Feng Shui storage system is identified based on the least squares-rotational invariant technique algorithm.

[0039] The technical solution provided by the present invention can select the acceleration power corresponding to different oscillation sources as the feedback signal of additional control on the basis of ensuring the primary frequency regulation performance of the hydropower unit, and introduce the fan output and energy storage output as the input of the hydropower unit. It can make full use of the mechanical power oscillation characteristics of ultra-low frequency oscillation and the flexible and adjustable performance advantages of fans and energy storage, and improve the suppression effect of ultra-low frequency oscillation on the basis of improving the utilization rate of auxiliary service resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the structure of an additional controller on the wind storage side in one embodiment of the present invention.

[0041] Figure 2 It is a schematic diagram of the process of ultra-low frequency oscillation suppression based on oscillation source positioning in the present invention.

[0042] Figure 3 It is a structural schematic diagram of a Feng Shui storage system in one embodiment of the present invention.

[0043] Figure 4 This is an oscillation energy curve diagram of each unit of a hydropower system in one embodiment of the present invention.

[0044] Figure 5 This is a comparison diagram of frequency curves of a wind-hydropower system under different control methods in one embodiment of the present invention. DETAILED DESCRIPTION

[0045] The present invention designs an additional damping controller based on hybrid robust control. The input signal of the additional controller is the acceleration power signal of the oscillation source unit, and the output signal is added to the fixed power side of the wind storage system to achieve dynamic adjustment of the wind storage output with the acceleration power of the oscillation source unit, increase the ultra-low frequency damping of the system, and realize the suppression of ultra-low frequency oscillation.

[0046] Hereinafter, the technical solution provided by the present invention will be further elaborated in combination with specific embodiments and drawings.

[0047] Example 1

[0048] This embodiment provides a method for suppressing ultra-low frequency oscillation based on oscillation source positioning. The method involves a wind storage system, such as Figure 1 As shown, the specific steps include:

[0049] Step 1: Perform oscillation mode decomposition based on the Total Least Squares-Estimation on Signal Parameters via Rotational Technique (TLS-ESPRIT) algorithm to decompose the generator speed curve and mechanical power curve data. Select the ultra-low frequency oscillation mode to calculate the oscillation energy, and determine whether the unit is the oscillation source based on the oscillation energy.

[0050] The sampling signal Y is established based on the generator speed deviation curve or mechanical power curve.

[0051] Y=[x(0),x(1),...x(i),...,x(N-1)] T ;

[0052] In the formula, i is the sampling point number, x(i) is the data value of the i-th sampling point, N is the number of sampling points, i=0,1,...,N-1, and T represents transposition. Construct an augmented Hankel matrix based on the sampled signal Y; perform singular value decomposition on the augmented Hankel matrix to obtain the signal subspace and noise subspace. The K eigenvalues ​​of the optimal matrix of the signal subspace sought by the TLS (Total Least Squares) method generate the matrix λ,

[0053]

[0054] In the formula, is the i-th power of the k-th eigenvalue of the optimal matrix, k = 1, 2, ..., K.

[0055] For the oscillation mode, we have

[0056]

[0057] a k =2|c k |;

[0058]

[0059] In the formula, ω k is the angular frequency of the oscillation mode, Ts is the period of the sampling signal Y, σ k is the exponential decay factor of the oscillation mode, a k is the amplitude of the oscillation mode, c k is the product of the amplitude of the oscillation mode signal and the phase rotation factor, is the phase angle of the oscillation mode.

[0060] in,

[0061] c=[c1 c2 … c k ] T =(λ T λ) -1 λ T Y.

[0062] Select ultra-low frequency oscillation, that is, the mode with an oscillation frequency less than 0.1 Hz, and the mechanical power signal ΔP under the ultra-low frequency oscillation mode mk Or generator speed deviation signal Δω k for:

[0063]

[0064] Where n is the sampling point number, n = 1, 2, ..., N;

[0065] The oscillation energy is:

[0066] ΔE m (k) = ∫ΔP mk Δω k dt;

[0067] In the formula, ΔP mk is the mechanical power variation under the ultra-low frequency oscillation mode;

[0068] If the oscillation energy is positive, the corresponding unit is the oscillation source.

[0069] Step 2: Select the acceleration power of the two oscillation source signals with the largest oscillation energy as the output of the water-wind storage system, and the wind storage output as the input of the wind-water storage system. Based on the TLS-ESPRIT algorithm, the partial transfer function of the system is identified and a complete transfer function matrix of the multi-input and output system is formed.

[0070] Specifically, the actual power grid has a multi-input and multi-output model:

[0071]

[0072] In the formula, s is the Laplace operator, y1(s) and y2(s) are the outputs of the wind-water storage system, that is, the acceleration power of the two oscillating sources; u1(s) and u2(s) are the inputs of the wind-water storage system, that is, the wind turbine additional power command value and the energy storage additional power command value.11 (s) is the transfer function of u1(s)-y1(s); G 12 (s) is the transfer function of u2(s)-y1(s); G 21 (s) is the transfer function of u1(s)-y2(s); G 22 (s) is the transfer function of u2(s)-y2(s). G 11 (s), G 12 (s), G 21 (s) and G 22 (s) can be obtained through identification. The identification process is to apply a small power step disturbance only at the fan, and through the first step of oscillation mode decomposition, the oscillation mode decomposition result of the acceleration power of the oscillation source unit G1 is obtained. After the Lapse transformation, the Lapse transformation divided by the step disturbance can be obtained. 11 (s), similarly, according to the acceleration power decomposition result of the oscillation source unit G2, we can get G 21 (s). Only a small power step disturbance is applied at the energy storage, and the oscillation mode decomposition result of the acceleration power of the oscillation source unit G1 is obtained through the oscillation mode decomposition in step 1. The oscillation mode decomposition result of the acceleration power of the oscillation source unit G1 can be obtained by dividing the oscillation mode of the step disturbance by the oscillation mode transformation. 12 (s), similarly, according to the acceleration power decomposition result of the oscillation source unit G2, we can get G 22 (S).

[0073] The above-mentioned selection of two oscillation source signals with the largest oscillation energy as the output of the Feng Shui storage system and the feedback signal of the additional controller is an optimal method, which can reduce the difficulty of calculation while ensuring the accuracy of the model and improve the rate of ultra-low frequency oscillation suppression.

[0074] Step 3: Based on the hybrid robust control theory and the transfer function matrix identified in step 2, the transfer function matrix K(s) of the additional controller on the wind storage side is calculated, the acceleration power of the oscillation source of the feedback signal of the additional controller, and the output of the additional controller is attached to the constant power side of the wind storage.

[0075] Specifically: According to the transfer function G obtained by identification 11 (s), G 12 (s), G 21 (s) and G 22 (s), based on the robust control algorithm, the corresponding calculation controller transfer function K 11 (s), K 12 (s), K 21 (s) and K 22 (s), the specific structure of the additional controller on the wind storage side is as follows Figure 1 As shown. Among them, P1 is the actual output of energy storage, P ref1 is the energy storage output command value, P2 is the actual output of the fan, and P ref2is the wind turbine output command value, and the oscillation source acceleration power is used as the input of the additional controller on the wind storage side and is added to the wind storage output command value after passing through the controller and the limiting link. The wind turbine and energy storage output are dynamically adjusted with the unbalanced power of the oscillation source, thereby achieving the purpose of enhancing the system damping and suppressing ultra-low frequency oscillation.

[0076] Among them, the TLS-ESPRIT algorithm is a preferred algorithm, which has strong anti-noise and anti-interference capabilities. Optionally, other algorithms can be used in practice to implement its functions, such as the prony algorithm. PI stands for Proportional-Integral, proportional integral control.

[0077] Example 2

[0078] The process of the ultra-low frequency oscillation suppression method based on oscillation source positioning provided in this embodiment is as follows: Figure 2 Combining this method with Figure 3 As shown, a wind turbine system including a busbar-connected wind turbine, energy storage and at least two hydropower units is simulated and verified on PSCAD (Power Systems Computer Aided Design, electromagnetic transient simulation software). Wind turbine system 1) applies a small power disturbance on the wind turbine side, and uses the TLS-ESPRIT algorithm to perform oscillation mode decomposition to decompose the generator speed curve and mechanical power curve data. The ultra-low frequency oscillation mode is selected to calculate the oscillation energy. The oscillation energy of each unit is as follows Figure 4 As shown, the oscillation energy of generators G1 and G3 is large, and they are oscillation source units. The oscillation energy of generator G2 is close to zero, and it provides almost no oscillation energy. The oscillation energy of generator G4 is negative, and it is a positive damping unit. The ultra-low frequency oscillation process is often accompanied by electromagnetic power oscillation, so the acceleration power of generators G1 and G3 can be selected as feedback signals.

[0079] 2) The acceleration power of the oscillation source generators G1 and G3 is selected as the system output, and the output of the wind storage system is selected as the system input. The transfer function obtained based on the TLS-ESPRIT algorithm is:

[0080]

[0081] 3) The transfer function of the additional controller on the wind-storage side is calculated as:

[0082]

[0083] The feedback signal of the additional controller is the acceleration power of the oscillation source generators G1 and G3, and the additional controller output is on the wind storage constant power side. When the load is reduced by 2500MW, the effects of different controllers are compared as follows: Figure 5As shown in the figure, the robust controller based on the oscillating source signal has a better suppression effect than the non-oscillating source signal, which proves the effectiveness of this method. Under the additional robust control based on the oscillating source signal, the highest point of the system frequency is 50.1Hz, and the frequency peak based on the non-oscillating source signal is 50.2Hz, which is the same as the peak of the traditional PI control. 50.2Hz is the upper limit of the normal operation frequency, and the system frequency under the control of the non-oscillating source signal is easy to exceed the limit.

[0084] In summary, the technical solution provided by the present invention can select the acceleration power corresponding to different oscillation sources as the feedback signal of the additional control on the basis of ensuring the primary frequency regulation performance of the hydropower unit, design the additional robust damping controller on the wind-storage side, introduce the wind turbine output and the energy storage output as the input of the hydropower unit, the controller input signal is the acceleration power signal of the oscillation source, and the output signal is attached to the fixed power side of the wind turbine and the energy storage unit, which can make full use of the mechanical power oscillation characteristics of the ultra-low frequency oscillation and the flexible and adjustable performance advantages of the wind turbine and the energy storage, and improve the suppression effect of the ultra-low frequency oscillation on the basis of improving the utilization rate of the auxiliary service resources;

[0085] Furthermore, each preferred scheme has achieved the following beneficial effects on the basis of achieving the above-mentioned beneficial effects: processing data through the least squares-rotational invariant technology can more effectively reduce noise interference, making the decomposition result or the established sampling signal more accurate.

Claims

1. A method for suppressing ultra-low frequency oscillation based on oscillation source positioning, which is used to suppress ultra-low frequency oscillation of a wind and water storage system, wherein the wind and water storage system includes a wind turbine generator set connected by a busbar, energy storage and at least two hydropower generator sets; It is characterized in that The following steps are involved: Step S1: performing oscillation mode decomposition on each hydropower unit in the wind and water storage system, and decomposing the speed curve data or mechanical power curve data of the corresponding generator; Select the ultra-low frequency oscillation mode to calculate the oscillation energy, and determine the unit that is the oscillation source based on the oscillation energy; Step S2: taking the acceleration power of the oscillation source as the output of the Feng Shui storage system, i.e., the first output; taking the wind turbine output and the energy storage output as the input of the Feng Shui storage system; wherein the acceleration power is specifically the acceleration power of each of the two oscillation sources with the largest oscillation energy; The transfer function matrix of the Feng Shui storage system is identified, that is, the first transfer function matrix; Step S3: an additional controller is set on the wind storage side, and the acceleration power is used as input; based on the hybrid robust control theory and the first transfer function matrix, a transfer function matrix of the additional controller is calculated, that is, a second transfer function matrix; The output of the additional controller, i.e., the second output, is obtained by calculation according to the second transfer function matrix; The second output is added to the fixed power side of the wind turbine and the fixed power side of the energy storage respectively, the output of the wind turbine is adjusted to the additional power command value of the wind turbine, and the output of the energy storage is adjusted to the additional power command value of the energy storage, so as to realize ultra-low frequency oscillation suppression.

2. The method for suppressing ultra-low frequency oscillation based on oscillation source positioning according to claim 1, characterized in that: Step S1 specifically includes: Step S11: Establishing a sampling signal Y based on the speed deviation curve or mechanical power curve of the generator, Y=[x(0),x(1),...x(i),...,x(N-1)] T ; Where i is the sampling point number, x(i) is the data value of the i-th sampling point, N is the number of sampling points, i=0,1,...,N-1, T represents transposition; Step S12: constructing an augmented Hankel matrix according to the sampled signal Y; performing singular value decomposition on the augmented Hankel matrix to obtain a signal subspace; Step S13: Find the K eigenvalues ​​of the optimal matrix of the signal subspace by the least square method to generate the optimal matrix λ. In the formula, is the i-th power of the k-th eigenvalue of the optimal matrix, k = 1, 2, ..., K; For the oscillation mode, we have c=[c1 c2 … c k ] T =(λ T l) -1 l T Y; In the formula, ω k is the angular frequency of the oscillation mode, T s is the period of the sampling signal Y, σ k is the exponential decay factor of the oscillation mode, c is c k The transposed matrix of the set, c k is the product of the amplitude of the oscillation mode signal and the phase rotation factor; Step S14: Select an oscillation mode with an oscillation frequency less than a preset frequency, that is, an ultra-low frequency oscillation mode, and calculate the oscillation energy. DE m (k)=∫ΔP mk Give k dt; Where ΔP mk is the mechanical power signal under the ultra-low frequency oscillation mode, Δω k is the speed deviation signal of the generator in the ultra-low frequency oscillation mode, n is the sampling point number, n=1,2,...,N, ΔE m (k) is the oscillation energy in the ultra-low frequency oscillation mode; If ΔE m (k)>0, the corresponding unit is an oscillation source.

3. The method for suppressing ultra-low frequency oscillation based on oscillation source positioning according to claim 2, characterized in that: The preset frequency is 0.1 Hz.

4. The method for suppressing ultra-low frequency oscillation based on oscillation source positioning according to claim 1, characterized in that: Step S2 specifically includes: Step S21: applying power step disturbances to the two oscillation sources with the largest oscillation energy respectively, and performing oscillation mode decomposition; performing Laplace transform on the decomposition results, and dividing them by the Laplace transform results of the power step disturbance, to obtain the corresponding transfer function; Step S22: Combining all transfer functions into a first transfer function matrix, Where s is the Laplace operator, y1(s) and y2(s) are the outputs of the wind-water storage system, i.e., the acceleration power of the two oscillating sources; u1(s) and u2(s) are the inputs of the wind-water storage system, i.e., the additional power command value of the wind turbine and the additional power command value of the energy storage; G fg (s) is u g (s) to y f The transfer function of (s), f∈[1,2], g∈[1,2].

5. A method for suppressing ultra-low frequency oscillation based on oscillation source positioning according to any one of claims 1 to 4, characterized in that: The speed curve data and mechanical power curve data of the generator are decomposed based on the least squares-rotational invariant technology algorithm.

6. A method for suppressing ultra-low frequency oscillation based on oscillation source positioning according to any one of claims 1 to 4, characterized in that: The transfer function matrix of the Feng Shui storage system is identified based on the least squares-rotational invariant technique algorithm.

Images