Robust wide-area damping controller design method for wind-light-fire bundling delivery system

Abstract

The invention discloses a robust wide-area damping controller design method for a wind-light-fire bundling delivery system. Comprising the following steps: selecting a plurality of typical working conditions of the wind-light-fire bundled delivery system as vertexes to establish a polyhedral model, and performing order reduction on the polyhedral model to obtain an order-reduced polyhedral model; wide-area signal transmission delay and communication faults are introduced into the reduced-order polyhedron model; and constructing a robust reduced-order dynamic output feedback controller, solving the robust reduced-order dynamic output feedback controller by adopting an LMI method through a polyhedral model considering time delay and communication faults and a minimum H infinity norm to obtain a robust wide-area damping controller, and transmitting a control signal to the wind-light-fire bundled delivery system. The controller designed by the invention not only provides better robustness for a given operation condition set, but also can ensure an enough damping ratio under the conditions that the system has an unstable dominant mode, fixed or variable time delay and a communication fault.

Description

Technical Field

[0001] The present invention belongs to the field of energy technology and relates to a wide-area damping controller design method, and in particular to a robust wide-area damping controller design method for a wind-solar-fire bundled transmission system. Background Art

[0002] With the proposal of the "dual carbon" goal, my country's new energy has developed rapidly, among which the installed capacity of wind energy and photovoltaic resources ranks among the top in the world. Large wind farms and photovoltaic power plants in some regions form a wind-solar-fire bundled transmission system with traditional thermal power plants, and transmit electricity through long-distance AC and DC transmission lines. However, new energy is volatile and random, and the continuous increase in its penetration rate may cause grid congestion, thereby worsening the damping of the power system, causing low-frequency oscillations, and threatening the stability of large interconnected systems.

[0003] Traditionally, power system stabilizers based on local signals or wide-area damping controllers based on wide-area signals are used to improve the damping of the power system and suppress low-frequency oscillations by adding control signals. However, considering uncertain factors such as load fluctuations, changes in the dispatching output of generator sets, wide-area signal transmission delays, and wide-area signal communication failures, there is currently no good solution to the problem of suppressing low-frequency oscillations in uncertain power systems under various disturbances. Traditional solutions do not have good robustness and it is difficult to effectively improve the damping of the power system under multiple uncertainties.

[0004] Considering the control characteristics of the back-to-back converter of the wind turbine, the control loop of the wind turbine itself can be used to provide damping performance for the system. The reactive power of the wind turbine can be adjusted through the reactive modulation outer loop of the rotor-side controller of the wind turbine, thereby providing damping and suppressing oscillation when low-frequency oscillation occurs in the system. In order to make full use of wind power to improve system damping and stability, and solve the problem of low-frequency oscillation in the case of unstable dominant mode, fixed or variable time delay and communication failure in the system, the present invention discloses a design method of a robust wide-area damping controller for a wind-solar-fire bundled transmission system. Summary of the invention

[0005] To solve the above problems, the present invention proposes a robust wide-area damping controller design method for a wind-solar-thermal bundled transmission system to solve the low-frequency oscillation problem of the power system under the background of increasing penetration of new energy.

[0006] The technical solution adopted by the present invention is as follows:

[0007] A robust wide-area damping controller design method for a wind-solar-thermal bundled transmission system includes the following steps:

[0008] 1) Select several typical working conditions of the wind-solar-thermal bundled transmission system as vertices to establish a polyhedron model, and reduce the order of the polyhedron model to obtain a reduced-order polyhedron model;

[0009] 2) Introducing wide-area signal transmission delay and communication failure into the reduced-order polyhedron model, and obtaining a polyhedron model that takes delay and communication failure into account;

[0010] 3) Construct a robust reduced-order dynamic output feedback controller by considering the polyhedral model of delay and communication failure and minimizing H ∞ norm, and a two-stage linear matrix inequality (LMI) method is used to solve the robust reduced-order dynamic output feedback controller to obtain a robust wide-area damping controller, and the control signal is transmitted to the wind-solar-thermal bundling transmission system.

[0011] Furthermore, the polyhedron model is established by selecting several typical working conditions of the wind-solar-fire bundled transmission system as vertices, specifically including:

[0012] The rated operating condition of the wind-solar-thermal bundled transmission system is taken as the benchmark condition. A series of operating points are obtained by changing the operating data such as wind turbine output, synchronous machine output, photovoltaic output and load power. The operating point with convergent power flow is selected as a typical condition. According to the uncertainty of load demand and output power, a state space model is established for each typical condition. The state space model is:

[0013]

[0014] y=C(α)x

[0015] Among them, A(α), B(α) and C(α) are time-varying parameter matrices corresponding to Polyhedron domain A(α) is the system state matrix; B(α) is the control input matrix; C(α) is the system output matrix; The state variables of the wind-solar-thermal bundled transmission system include the state variables of synchronous generators, wind turbines and photovoltaics; It is the output variable of the wind-solar-thermal bundled transmission system and also the input signal of the controller; It is the input variable for the wind-solar-fire bundled transmission system and also the output signal of the controller.

[0016] Furthermore, the method for reducing the order of the polyhedron model is a selective modal analysis method, and the reduced-order polyhedron model is:

[0017]

[0018] in, represents the convex hull; The state space model corresponding to each typical working condition, that is, the polyhedron Vertex, N represents the vertex of the polyhedron The total number of j represents the coordinates of the polyhedron; the convex combination of these vertices Form a polyhedron Each vertex represents a linear time-invariant model; A j ,B j ,C j are the corresponding system state matrix, control input matrix and system output matrix respectively.

[0019] Furthermore, the wide area signal transmission delay is introduced into the reduced-order polyhedron model, including:

[0020] Use the Padé approximation method to build a delay approximation model, specifically: transform the transmission delay Modeled as a second-order transfer function G d (s),

[0021]

[0022] Among them, T d represents the value of transmission delay, s is a complex variable in the frequency domain;

[0023] Then the second-order transfer function G d (s) is converted into a state space expression:

[0024]

[0025] y d =C d x d

[0026] Among them, x d is the vector of delayed state variables, u d is the vector of the input signal, that is, the vector of the original data signal, y d is the vector of the output signal, that is, the vector of the data signal after delay; A d , B d , C d are the corresponding state matrix, input matrix and output matrix respectively.

[0027] The delay approximation model is combined with the reduced-order polyhedron model to obtain a polyhedron model that takes delay into account:

[0028]

[0029] in nd is the order of the delay approximation model, is the state variable; represents the delayed wide-area measurement output signal of the system, are the corresponding system state matrix, control input matrix and system output matrix respectively.

[0030] Furthermore, introducing communication failure into the polyhedron model considering delay includes:

[0031] When the wide area signal communication fails, the output matrix in the polyhedron model Make corrections,

[0032] Specifically: the output matrix The kth row corresponding to the kth (k=1,2,…,p)th communication failure in becomes zero; the output matrix for:

[0033]

[0034] in, Represents the output matrix The row corresponding to the k-th output in ;

[0035] Corrected output matrix for:

[0036]

[0037] The polyhedron model considering delay and communication failure is:

[0038]

[0039] in, is the corresponding system state matrix, which will change with different communication failures; is the control input matrix; It is the system output matrix, which will change with different communication failures.

[0040] Furthermore, multiple feedback signals and various communication faults may be selected simultaneously.

[0041] Furthermore, the robust reduced-order dynamic output feedback controller is:

[0042]

[0043] in, is a vector of controller model state variables, n c is the order of the controller; A c , B c , Cc , D c is the parameter matrix corresponding to the controller.

[0044] Furthermore, the polyhedron model considering delay and communication failure and minimizing H ∞ norm, and a two-stage linear matrix inequality (LMI) method is used to solve the robust reduced-order dynamic output feedback controller, including:

[0045] The polyhedral model considering delay and communication failure is transformed into a continuous-time augmented state space expression:

[0046]

[0047] in, is the external disturbance input vector, including load fluctuation and wind speed change; z represents the ∞ Modulation output vector related to performance indicators; is the disturbance gain matrix; is the control input matrix; and H ∞ The coefficient matrices of state variables, disturbance inputs, and control inputs related to the performance indicators; are the parameter matrices of state variables and disturbance inputs related to the system output, respectively.

[0048] The augmented state space expression including the controller state variables is obtained by using the following similarity transformation η:

[0049]

[0050] Among them, I n represents the n-th order identity matrix, Indicates n c The identity matrix of order;

[0051] The augmented state space expression including the controller state variables is:

[0052]

[0053] in, is the disturbance gain matrix; is the control input matrix; and H ∞ The coefficient matrices of state variables, disturbance inputs, and control inputs related to the performance indicators; are the parameter matrices of state variables and disturbance inputs related to the system output, respectively.

[0054] The augmented state space expression containing the controller state variables is converted into a closed-loop system state space expression, and the corresponding parameter matrix formula is:

[0055]

[0056] in, They are the state matrix, control input matrix, output matrix and direct transfer matrix of the closed-loop system respectively.

[0057] Then consider H ∞ Norm performance, robust reduced-order dynamic output feedback controller is solved by LMI method.

[0058] Furthermore, the robust reduced-order dynamic output feedback controller is solved by the LMI method, which includes two stages. In the first stage, the parameter-dependent state feedback gain is calculated. In the second stage, the gains are used to synthesize a fixed-order dynamic output feedback controller K for the entire polyhedron c .

[0059] Furthermore, the first stage includes:

[0060] For a known constant μ>0, if there exists a parameter dependence matrix Z j And a matrix G j , so that the following LMI inequality holds:

[0061]

[0062] P j >εI

[0063] Among them, He(A)=A+A T , ε=1, I is the order and P j The same identity matrix, * indicates the corresponding symmetric term in the block matrix;

[0064] Then the parameter-dependent state feedback controller that can stabilize the uncertain system for:

[0065]

[0066] The parameter μ provides an additional degree of freedom that can be used to construct different

[0067] The second phase includes:

[0068] Known For a constant γ>0, if there exists a parameter matrix R, L, H j , Vj and F j So that the following LMI inequality holds:

[0069]

[0070] Q j >0

[0071] in:

[0072]

[0073]

[0074] Then, the final H ∞ Dynamic output feedback controller K with performance level γ c for:

[0075] K c =R -1 L.

[0076] Furthermore, the control signal is transmitted to the wind-solar-fire bundled transmission system, specifically: the control signal is injected into the reactive modulation outer loop of the rotor side controller of the doubly-fed asynchronous wind generator, and the low-frequency oscillation of the wind-solar-fire bundled transmission system is suppressed by adjusting the reactive power of the wind turbine.

[0077] The beneficial effects of the present invention are:

[0078] This invention provides a method for designing a robust wide-area damping controller for a wind-solar-thermal bundled transmission system. The method aims to consider the occurrence of low-frequency oscillations in the power system and inject a control signal into the reactive modulation outer loop of the rotor-side controller of the doubly-fed asynchronous wind generator. By adjusting the reactive power of the wind turbine, the low-frequency oscillations of the wind-solar-thermal bundled transmission system can be effectively suppressed. The controller designed by the present invention not only provides good robustness for a given set of operating conditions, but also ensures sufficient damping ratios in the presence of unstable dominant modes, fixed or variable time delays, and communication failures in the system. The present invention can serve as an effective reference for the design of wide-area damping controllers for new power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 This is a configuration diagram of the wind-solar-fire bundling and delivery system in an embodiment of the present invention.

[0080] Figure 2 This is a rotor side control block diagram in an embodiment of the present invention.

[0081] Figure 3 This is a structural diagram of an improved two-zone system in an embodiment of the present invention.

[0082] Figure 4 Schematic diagram of the simulation result of scenario A in the embodiment of the present invention.

[0083] Figure 5 Schematic diagram of the simulation result of scenario B in the embodiment of the present invention.

[0084] Figure 6 This is a simulation result diagram of the worst scenario in an embodiment of the present invention. DETAILED DESCRIPTION

[0085] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0086] The present invention provides a method for designing a robust wide-area damping controller for a wind-solar-firepower bundled delivery system, comprising the following steps:

[0087] 1) Select several typical working conditions of the wind-solar-thermal bundled transmission system as vertices to establish a polyhedron model, and reduce the order of the polyhedron model to obtain a reduced-order polyhedron model;

[0088] 2) Introducing wide-area signal transmission delay and communication failure into the reduced-order polyhedron model, and obtaining a polyhedron model that takes delay and communication failure into account;

[0089] 3) Construct a robust reduced-order dynamic output feedback controller by considering the polyhedral model of delay and communication failure and minimizing H ∞ norm, and a two-stage linear matrix inequality (LMI) method is used to solve the robust reduced-order dynamic output feedback controller to obtain a robust wide-area damping controller, and the control signal is transmitted to the wind-solar-thermal bundling transmission system.

[0090] The polyhedron model is established by selecting several typical working conditions of the wind-solar-fire bundled transmission system as vertices, specifically including:

[0091] like Figure 1 As shown in the figure, the rated operating condition of the wind-solar-thermal bundled transmission system is taken as the benchmark condition. A series of operating points are obtained by changing the operating data such as wind turbine output, synchronous machine output, photovoltaic output and load power. The operating points where the power flow converges are selected to obtain several typical conditions, and a state space model is established for each typical condition. The state space model is:

[0092]

[0093] y=C(α)x

[0094] Among them, A(α), B(α) and C(α) are time-varying parameter matrices corresponding to Polyhedron domain A(α) is the system state matrix; B(α) is the control input matrix; C(α) is the system output matrix; The state variables of the wind-solar-thermal bundled transmission system include the state variables of synchronous generators, wind turbines and photovoltaics; It is the output variable of the wind-solar-thermal bundled transmission system and also the input signal of the controller; It is the input variable for the wind-solar-fire bundled transmission system and also the output signal of the controller.

[0095] The method for reducing the order of the polyhedron model is a selective modal analysis method, and the reduced-order polyhedron model is:

[0096]

[0097] in, represents the convex hull; The state space model corresponding to each typical working condition, that is, the polyhedron Vertex, N represents the vertex of the polyhedron The total number of j represents the coordinates of the polyhedron; the convex combination of these vertices Form a polyhedron Each vertex represents a linear time-invariant model, A j ,B j ,C j are the corresponding system state matrix, control input matrix, and system output matrix. Due to the convex property of the polyhedron, once the control law is established by satisfying the LMI condition of each vertex, the designed controller can ensure that all other vertices in the same polyhedron are robust.

[0098] Introducing the wide area signal transmission delay into the reduced-order polyhedron model includes:

[0099] Use the Padé approximation method to build a delay approximation model, specifically: transform the transmission delay Modeled as a second-order transfer function G d (s),

[0100]

[0101] Among them, T d represents the value of transmission delay, s is a complex variable in the frequency domain;

[0102] Then the second-order transfer function G d (s) is converted into a state space expression:

[0103]

[0104] y d=C d x d

[0105]

[0106] Among them, x d is the vector of delayed state variables, u d is the vector of the input signal, that is, the vector of the original data signal, y d is the vector of the output signal, that is, the vector of the data signal after delay; A d , B d , C d are the corresponding state matrix, input matrix and output matrix matrices.

[0107] The delay approximation model is combined with the reduced-order polyhedron model to obtain a polyhedron model that takes delay into account:

[0108]

[0109] in n d is the order of the delay approximation model, is the state variable; represents the delayed wide-area measurement output signal of the system, are the corresponding system state matrix, control input matrix and system output matrix.

[0110] Introducing communication failure into the polyhedron model considering delay includes:

[0111] When the wide area signal communication fails, the output matrix in the polyhedron model Make corrections, specifically: output matrix The kth row corresponding to the kth (k=1,2,…,p)th communication failure in becomes zero; the output matrix for:

[0112]

[0113] in, Represents the output matrix The row corresponding to the k-th output in ;

[0114] Corrected output matrix for:

[0115]

[0116] The polyhedron model considering delay and communication failure is:

[0117]

[0118] in, is the corresponding system state matrix, which will change with different communication failures; is the control input matrix; It is the system output matrix, which will change with different communication failures.

[0119] The present invention can select multiple feedback signals and various communication faults at the same time.

[0120] like Figure 2 As shown, a robust reduced-order dynamic output feedback controller is designed, and its state space expression or matrix expression is:

[0121]

[0122] in, is a vector of controller model state variables, n c is the order of the controller; A c , B c , C c , D c is the parameter matrix corresponding to the controller.

[0123] The polyhedral model considering delay and communication failure and minimizing H ∞ norm, and a two-stage linear matrix inequality (LMI) method is used to solve the robust reduced-order dynamic output feedback controller, including:

[0124] The polyhedral model considering delay and communication failure is transformed into a continuous-time augmented state space expression:

[0125]

[0126]

[0127] in, is the external disturbance input vector, including load fluctuation and wind speed change; z represents the ∞ Modulation output vector related to performance indicators; is the disturbance gain matrix; is the control input matrix; and H ∞ The coefficient matrices of state variables, disturbance inputs, and control inputs related to the performance indicators; are the parameter matrices of state variables and disturbance inputs related to the system output, respectively.

[0128] The augmented state space expression including the controller state variables is obtained by using the following similarity transformation η:

[0129]

[0130] Among them, I n represents the n-th order identity matrix, Indicates n c The identity matrix of order;

[0131] The augmented state space expression including the controller state variables is:

[0132]

[0133] in:

[0134]

[0135] in, is the disturbance gain matrix; is the control input matrix; and H ∞ The coefficient matrices of state variables, disturbance inputs, and control inputs related to the performance indicators; are the parameter matrices of state variables and disturbance inputs related to the system output, respectively.

[0136] The augmented state space expression containing the controller state variables is converted into a closed-loop system state space expression, and the corresponding parameter matrix formula is:

[0137]

[0138]

[0139] in, They are the state matrix, control input matrix, output matrix and direct transfer matrix of the closed-loop system respectively.

[0140] Then consider H ∞ Norm performance, robust reduced-order dynamic output feedback controller is solved by LMI method.

[0141] Furthermore, the robust reduced-order dynamic output feedback controller is solved by the LMI method, which includes two stages. In the first stage, the parameter-dependent state feedback gain is calculated. In the second stage, the gains are used to synthesize a fixed-order dynamic output feedback controller K for the entire polyhedron c .

[0142] Furthermore, the first stage includes:

[0143] For a known constant μ>0, if there exists a parameter dependence matrix Zj And a matrix G j , so that the following LMI inequality holds:

[0144]

[0145] P j >εI

[0146] Among them, He(A)=A+A T , ε=1, I is the order and P j The same identity matrix, * indicates the corresponding symmetric term in the block matrix;

[0147] Then the parameter-dependent state feedback controller that can stabilize the uncertain system for:

[0148]

[0149] The parameter μ provides an additional degree of freedom that can be used to construct different

[0150] The second phase includes:

[0151] Known For a constant γ>0, if there exists a parameter matrix R, L, H j , V j and f j So that the following LMI inequality holds:

[0152]

[0153] Q j >0

[0154] in:

[0155]

[0156] Then, the final H ∞ Dynamic output feedback controller K with performance level γ c for:

[0157] K c =R -1 L.

[0158] In the above LMI conditions, the matrix variable H j , V j , and F j is a homogeneous polynomial of fixed order 1. However, for the first and second phase Lyapunov matrices P j and Q jand the first stage Z j , we can choose different polynomial orders and use the set g = {g P g Q g Z}express.

[0159] The transmitting of the control signal to the wind-solar-thermal bundled transmission system is specifically: injecting the control signal into the reactive modulation outer loop of the rotor side controller of the doubly-fed asynchronous wind generator, and suppressing the low-frequency oscillation of the wind-solar-thermal bundled transmission system by adjusting the reactive power of the wind turbine.

[0160] The robust wide-area damping controller designed by the method of the present invention not only provides good robustness for a given set of operating conditions, but also can ensure sufficient damping ratio when the system has an unstable dominant mode, fixed or variable time delay, and communication failure. It can effectively suppress the low-frequency oscillation of the wind-solar-thermal bundled transmission system and can serve as an effective reference for the design of wide-area damping controllers for new power systems.

[0161] A specific embodiment of the present invention is as follows:

[0162] The method of the present invention is used to Figure 3 The improved two-area system with wind-solar-thermal bundled transmission is verified. The four operating conditions (p1-p4) are defined as follows (the controller is designed for p1-p3, that is, p4 is not included in the polyhedron model):

[0163] p1: Rated operating conditions, where area 1 transmits 500 MW of power to area 2.

[0164] p2: Low penetration condition, the power output of wind energy, photovoltaic energy and G2 are reduced by 75%, 50% and 10% respectively compared with the rated value, the load demand of nodes 7 and 9 is reduced by 150MW respectively, and 400MW of power is transmitted from area 1 to area 2.

[0165] p3: High penetration condition. The power output of G1-G3 is increased by 20%, 20%, and 10% respectively compared with the rated value. The load demand of nodes 7 and 9 increases by 100MW and 200MW, and 600MW of power is transmitted from area 1 to area 2.

[0166] p4: Unstable operating condition, one circuit of line 8-9 is permanently tripped, the power output of G3 increases by 20% compared to the rated value, and the load value of node 9 increases by 300MW relative to the baseline value.

[0167] The power angles δ1 and δ2 of the synchronous machines G1 and G2 are selected as the wide-area input signals of the controller, the transmission delay is 150ms, and at most a single communication failure is considered each time. A robust wide-area damping controller is designed according to the above method. The method proposed in the present invention can be verified by comparing the oscillation waveforms of the system before and after adding the proposed controller in different operating scenarios (as shown in Table 1).

[0168] Table 1

[0169]

[0170] The method of the present invention is used to perform simulation calculations on the embodiment, and the results are as follows:

[0171] Figure 4 The oscillation of physical quantities such as synchronous machine speed, tie line power, wind turbine outlet voltage, and wind turbine reactive power regulation after a three-phase short circuit fault occurs in the line under scenario A is given. The results show that oscillations continue to occur after disturbances in the power system without a damping controller. After adding a damping controller, the low-frequency oscillation of the system is effectively suppressed within 6 seconds by adjusting the reactive power output of the wind turbine. Figure 5 The oscillation of the synchronous machine power angle and the tie line power when the excitation voltage suddenly changes in scenario B with transmission delay is given. From the results, it can be seen that compared with the controller that does not consider the wide-area signal transmission delay, the controller designed by the present invention can suppress the low-frequency oscillation of the system more quickly and effectively. Figure 6 The oscillation of physical quantities such as synchronous machine power angle, speed and interconnection line power after the line trips under the worst case conditions including transmission delay, communication failure and fluctuation of new energy output conditions is given. It can be seen from the results that even in this case, the controller can still quickly suppress the low-frequency oscillation of the system. Therefore, the controller designed by the present invention can effectively suppress the low-frequency oscillation of the wind-solar-fire bundled transmission system when the system has an unstable dominant mode, a fixed or variable time delay and a communication failure.

[0172] The above specific implementation modes are used to explain the present invention rather than to limit the present invention. Any modification and change made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A robust wide-area damping controller design method for wind-solar-fired bundled delivery system, characterized in that: The following steps are involved: 1) Select several typical working conditions of the wind-solar-thermal bundled transmission system as vertices to establish a polyhedron model, and reduce the order of the polyhedron model to obtain a reduced-order polyhedron model; 2) Introducing wide-area signal transmission delay and communication failure into the reduced-order polyhedron model, and obtaining a polyhedron model that takes delay and communication failure into account; 3) Construct a robust reduced-order dynamic output feedback controller by considering the polyhedral model of delay and communication failure and minimizing H ∞ norm, and a two-stage linear matrix inequality (LMI) method is used to solve the robust reduced-order dynamic output feedback controller to obtain a robust wide-area damping controller, and the control signal is transmitted to the wind-solar-thermal bundling transmission system.

2. The robust wide-area damping controller design method for wind-solar-fired bundled delivery system according to claim 1 is characterized in that: The polyhedron model is established by selecting several typical working conditions of the wind-solar-fire bundled transmission system as vertices, specifically including: Several typical operating conditions of the wind-solar-thermal bundled transmission system are selected, and a state space model is established for each typical operating condition according to the uncertainty of load demand and output power; the state space model is: y=C(α)x Among them, A(α), B(α) and C(α) are time-varying parameter matrices corresponding to Polyhedron domain A(α) is the system state matrix; B(α) is the control input matrix; C(α) is the system output matrix; The state variables of the wind-solar-thermal bundled transmission system include the state variables of synchronous generators, wind turbines and photovoltaics; Output variables for wind-solar-thermal bundled transmission system; Input variables for the wind-solar-thermal bundled delivery system.

3. The robust wide-area damping controller design method for wind-solar-fired bundled delivery system according to claim 1 is characterized in that: The method for reducing the order of the polyhedron model is a selective modal analysis method, and the reduced-order polyhedron model is: in, represents the convex hull; The state space model corresponding to each typical working condition, that is, the polyhedron Vertex, N represents the vertex of the polyhedron The total number of j represents the polyhedron coordinates; A j ,B j ,C j are the corresponding system state matrix, control input matrix and system output matrix respectively.

4. The robust wide-area damping controller design method for wind-solar-fired bundled delivery system according to claim 1 is characterized in that: Introducing the wide area signal transmission delay into the reduced-order polyhedron model includes: Use the Padé approximation method to build a delay approximation model, specifically: transform the transmission delay Modeled as a second-order transfer function G d (s), Among them, T d represents the value of transmission delay, s is a complex variable in the frequency domain; Then the second-order transfer function G d (s) is converted into a state space expression: y d =C d x d Among them, x d is the vector of delayed state variables, u d is the vector of the input signal, that is, the vector of the original data signal, y d is the vector of the output signal, that is, the vector of the data signal after delay; A d , B d , C d are the corresponding state matrix, input matrix and output matrix matrices respectively; The delay approximation model is combined with the reduced-order polyhedron model to obtain a polyhedron model that takes delay into account: in n d is the order of the delay approximation model, is the state variable; represents the delayed wide-area measurement output signal of the system, are the corresponding system state matrix, control input matrix and system output matrix respectively.

5. The method for designing a robust wide-area damping controller for a wind-solar-fired bundled delivery system according to claim 4, characterized in that: Introducing communication failure into the polyhedron model considering delay includes: When the wide area signal communication fails, the output matrix in the polyhedron model Make corrections, specifically: output matrix The kth row corresponding to the kth communication failure in becomes zero; the output matrix for: Where k = 1, 2, ..., p, Represents the output matrix The row corresponding to the k-th output in ; Corrected output matrix for: The polyhedron model considering delay and communication failure is: in, is the corresponding system state matrix; is the control input matrix; is the system output matrix.

6. The robust wide-area damping controller design method for wind-solar-fired bundled delivery system according to claim 1 is characterized in that: The robust reduced-order dynamic output feedback controller is: in, is a vector of controller model state variables, n c is the order of the controller; A c , B c , C c , D c is the parameter matrix corresponding to the controller.

7. The method for designing a robust wide-area damping controller for a wind-solar-fired bundled delivery system according to claim 1, characterized in that: The polyhedral model considering delay and communication failure and minimizing H ∞ norm, and a two-stage linear matrix inequality (LMI) method is used to solve the robust reduced-order dynamic output feedback controller, including: The polyhedral model considering delay and communication failure is transformed into a continuous-time augmented state space expression: in, is the external disturbance input vector, including load fluctuation and wind speed change; z represents the ∞ Modulation output vector related to performance indicators; is the disturbance gain matrix; is the control input matrix; and H ∞ The coefficient matrices of state variables, disturbance inputs, and control inputs related to the performance indicators; are the parameter matrices of state variables and disturbance inputs related to the system output, respectively; The augmented state space expression including the controller state variables is obtained by using the following similarity transformation η: Among them, I n represents the n-th order identity matrix, Indicates n c The identity matrix of order; The augmented state space expression including the controller state variables is: in, is the disturbance gain matrix; is the control input matrix; and H ∞ The coefficient matrices of state variables, disturbance inputs, and control inputs related to the performance indicators; are the parameter matrices of state variables and disturbance inputs related to the system output, respectively; The augmented state space expression containing the controller state variables is converted into a closed-loop system state space expression, and the corresponding parameter matrix formula is: in, They are the state matrix, control input matrix, output matrix and direct transfer matrix of the closed-loop system respectively; Then consider H ∞ Norm performance, robust reduced-order dynamic output feedback controller is solved by LMI method.

8. The method for designing a robust wide-area damping controller for a wind-solar-fired bundled delivery system according to claim 7, characterized in that: The robust reduced-order dynamic output feedback controller is solved by the LMI method, which includes two stages. In the first stage, the parameter-dependent state feedback gain is calculated. In the second stage, the gains are used to synthesize a fixed-order dynamic output feedback controller K for the entire polyhedron c .

9. The method for designing a robust wide-area damping controller for a wind-solar-fired bundled delivery system according to claim 8, characterized in that: The first phase includes: For a known constant μ>0, if there exists a parameter dependence matrix and Z j , and a matrix G j , so that the following LMI inequality holds: Among them, He(A)=A+A T , ε=1, I is the order and P j The same identity matrix, * indicates the corresponding symmetric term in the block matrix; Then the parameter-dependent state feedback controller that can stabilize the uncertain system for: The second phase includes: Known For a constant γ>0, if there exists a parameter matrix R, L, H j , V j and f j So that the following LMI inequality holds: Q j >0 in: Then, the final H ∞ Dynamic output feedback controller K with performance level γ c for: K c =R -1 L。 10. The method for designing a robust wide-area damping controller for a wind-solar-fired bundled delivery system according to claim 1, characterized in that: The transmitting of the control signal to the wind-solar-thermal bundled transmission system is specifically: injecting the control signal into the reactive modulation outer loop of the rotor side controller of the doubly-fed asynchronous wind generator, and suppressing the low-frequency oscillation of the wind-solar-thermal bundled transmission system by adjusting the reactive power of the wind turbine.

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