Power grid low-frequency oscillation suppression method based on wide-area damping controller and related equipment

Abstract

The application discloses a power grid low-frequency oscillation suppression method based on a wide-area damping controller and related equipment, relates to the technical field of power systems, and comprises the following steps: linearizing a power system at steady-state operating points of a plurality of steady-state flow convergence conditions to obtain a linear time-invariant model and a corresponding state space equation; calculating a participation factor according to the state space equation; determining a control signal and a feedback signal according to the participation factor; reducing the order of the linear time-invariant model according to the control signal and the feedback signal, modifying and extending a model matrix obtained after the order reduction, and obtaining a closed-loop system; constructing a controller parameter optimization problem according to the closed-loop system; solving the controller parameter optimization problem to obtain a feedback controller; and controlling the power system according to the feedback controller. The application can effectively cope with new energy uncertainty, enhance system damping, suppress low-frequency oscillation, and improve power system stability.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to a method and related equipment for suppressing low-frequency oscillations in power grids based on a wide-area damping controller. Background Technology

[0002] The intermittent and uncertain nature of renewable energy generation increases the risk of deterioration in system damping characteristics, potentially inducing low-frequency oscillations and affecting the safe and stable operation of the power grid. Existing methods for suppressing low-frequency oscillations mainly include power system stabilizers based on local measurement signals and wide-area damping control technology based on wide-area measurement information. However, due to various uncertainties such as load fluctuations, generator output variations, wide-area communication delays, and signal loss, the operating conditions of the power system are complex and variable. Existing renewable energy damping controller design methods cannot meet the requirements for safe and stable power system control. Summary of the Invention

[0003] The main objective of this application is to propose a method and related equipment for suppressing low-frequency oscillations in power grids based on a wide-area damping controller, so as to improve the stability of the power system.

[0004] To achieve the above objectives, one aspect of this application proposes a method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller, the method comprising the following steps: The power system is linearized at the steady-state operating point under multiple steady-state power flow convergence conditions to obtain a linear time-invariant model and the corresponding state-space equations. The participation factor is calculated based on the state-space equation. The control signal and feedback signal are determined based on the participating factors; The linear time-invariant model is reduced in order based on the control signal and the feedback signal. The model matrix obtained after the order reduction is then corrected and expanded to obtain a closed-loop system. The controller parameter optimization problem is constructed based on the closed-loop system. Solve the controller parameter optimization problem to obtain the feedback controller; The power system is controlled according to the feedback controller.

[0005] In some embodiments, calculating the participation factor based on the state-space equation includes the following steps: Determine the eigenvalues ​​of the state matrix based on the state-space equation; Determine the right and left eigenvectors of the eigenvalues; The participation factor is calculated based on the right eigenvector, the left eigenvector, and the total number of state variables in the state-space equation.

[0006] In some embodiments, determining the control signal and feedback signal based on the participation factor includes the following steps: The controllability index is calculated based on the column vector of the input matrix in the state-space equation and the left eigenvector. The signal with the largest controllability index is selected as the control signal; The observability index is calculated based on the row vector of the output matrix in the state-space equation and the right eigenvector. The signal with the largest observability index is selected as the feedback signal.

[0007] In some embodiments, the step of correcting and expanding the model matrix obtained after order reduction to obtain a closed-loop system includes the following steps: The reduced-order model matrix is ​​modified and expanded to obtain the time-delay model; The delay models under all operating conditions are combined to form an uncertainty model; The closed-loop system, including the controller, is determined based on the uncertainty model.

[0008] In some embodiments, constructing the controller parameter optimization problem based on the closed-loop system includes the following steps: With the H∞ and H2 performance of the closed-loop system as optimization objectives, a controller parameter optimization problem based on linear matrix inequalities is constructed.

[0009] In some embodiments, solving the controller parameter optimization problem to obtain a feedback controller includes the following steps: The controller parameter optimization problem is solved using a two-stage linear matrix inequality algorithm. In the first stage, the state feedback controller is solved, and then the state feedback controller is substituted into the second stage to solve for the controller parameters, thus obtaining the output feedback controller.

[0010] In some embodiments, controlling the power system according to the feedback controller includes the following steps: The output feedback signal of the power system is dynamically acquired and sent to the feedback controller; The feedback controller calculates the corresponding damping control command online based on the feedback signal; The damping control command is sent to the controlled energy device so that the energy device can adjust the corresponding adjustable capacity or operating state, thereby suppressing low-frequency oscillations.

[0011] To achieve the above objectives, another aspect of this application proposes a power grid low-frequency oscillation suppression device based on a wide-area damping controller, the device comprising: The system modeling unit is used to linearize the power system at the steady-state operating point under multiple steady-state power flow convergence conditions, so as to obtain a linear time-invariant model and the corresponding state-space equations. A participation factor calculation unit is used to calculate the participation factor based on the state-space equation. A signal determination unit is used to determine control signals and feedback signals based on the participation factors; The system closed-loop unit is used to reduce the order of the linear time-invariant model according to the control signal and the feedback signal, and to modify and expand the model matrix obtained after the order reduction to obtain a closed-loop system. The problem construction unit is used to construct a controller parameter optimization problem based on the closed-loop system. The problem-solving unit is used to solve the controller parameter optimization problem to obtain a feedback controller; A system control unit for controlling the power system according to the feedback controller.

[0012] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0013] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0014] To achieve the above objectives, another aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0015] The embodiments of this application include at least the following beneficial effects: This application provides a method and related equipment for suppressing low-frequency oscillations in power grids based on a wide-area damping controller. The scheme linearizes the power system at steady-state operating points under multiple steady-state power flow convergence conditions to obtain a linear time-invariant model and its corresponding state-space equations. Participation factors are calculated based on the state-space equations. Control and feedback signals are determined based on the participation factors. The linear time-invariant model is reduced in order based on the control and feedback signals, and the resulting model matrix is ​​corrected and extended to obtain a closed-loop system. A controller parameter optimization problem is constructed based on the closed-loop system. The controller parameter optimization problem is solved to obtain a feedback controller. The power system is then controlled using the feedback controller. This application, through multi-steady-state operating point linearization, utilizing participation factors to determine control and feedback signals, reducing the order and considering wide-area time delay for correction and extension to form a closed-loop system, and solving for the feedback controller, effectively addresses the uncertainties of new energy sources, enhances system damping, suppresses low-frequency oscillations, and improves power system stability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the low-frequency oscillation suppression method for power grids based on a wide-area damping controller provided in this application embodiment; Figure 2 Example flowchart of a method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller provided in this application embodiment; Figure 3 A schematic diagram of the structure of the power grid low-frequency oscillation suppression device based on a wide-area damping controller provided in the embodiments of this application; Figure 4 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] This application provides a method and related equipment for suppressing low-frequency oscillations in power grids based on a wide-area damping controller, relating to the field of power system technology. The method and related equipment provided in this application can be applied to terminals, servers, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller, but is not limited to the above forms.

[0021] This application can be applied to numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0022] Reference Figure 1 This application provides a method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller. This method may include, but is not limited to, steps S100 to S160, as follows: S100: The power system is linearized at the steady-state operating point under multiple steady-state power flow convergence conditions to obtain a linear time-invariant model and the corresponding state-space equations. S110: The participation factor is calculated based on the state-space equation; S120: Determine the control signal and feedback signal based on the participating factors; S130: Reduce the order of the linear time-invariant model according to the control signal and the feedback signal, and modify and expand the model matrix obtained after the order reduction to obtain the closed-loop system; S140: Construct a controller parameter optimization problem based on the closed-loop system; S150: Solve the controller parameter optimization problem to obtain the feedback controller; S160: Control the power system according to the feedback controller.

[0023] Specifically, embodiments of this application can obtain multiple steady-state operating points of a power system under a set of steady-state power flow convergence conditions. At each steady-state operating point, the power system is linearized to generate a linear time-invariant model and its state-space equations corresponding to that operating condition. For each state-space equation, the corresponding participation factor is calculated. Based on the analysis results of the participation factor, the control signal and feedback signal are determined from the available wide-area measurement signals. Based on the determined control signal and feedback signal, the linear time-invariant model is reduced in order to obtain the reduced-order model matrix. The reduced-order model matrix is ​​modified and extended to form a closed-loop system containing a controller structure. Based on this closed-loop system, an optimization problem is constructed with the controller parameters as decision variables. The constructed optimization problem is solved to obtain a feedback controller. The obtained feedback controller is connected to the power system to apply damping control to suppress low-frequency oscillations in the power grid.

[0024] Optionally, calculating the participation factor based on the state-space equation includes the following steps: Determine the eigenvalues ​​of the state matrix based on the state-space equation; Determine the right and left eigenvectors of the eigenvalues; The participation factor is calculated based on the right eigenvector, the left eigenvector, and the total number of state variables in the state-space equation.

[0025] Specifically, embodiments of this application can extract a state matrix from the state-space equation and solve for the eigenvalues ​​of the state matrix. For each eigenvalue, its corresponding right eigenvector and left eigenvector are calculated. Using the calculated right and left eigenvectors, combined with the total number of state variables in the state-space equation, the participation factor between each eigenvalue and each state variable is calculated one by one.

[0026] Optionally, determining the control signal and feedback signal based on the participation factor includes the following steps: The controllability index is calculated based on the column vector of the input matrix in the state-space equation and the left eigenvector. The signal with the largest controllability index is selected as the control signal; The observability index is calculated based on the row vector of the output matrix in the state-space equation and the right eigenvector. The signal with the largest observability index is selected as the feedback signal.

[0027] Specifically, in this embodiment, based on the input matrix in the state-space equation, each column vector of the input matrix is ​​extracted one by one, and each column vector is operated on with the left eigenvector to obtain the controllability index of each candidate control signal. The controllability indices of all candidate control signals are compared, and the signal with the largest controllability index value is selected as the control signal.

[0028] Based on the output matrix in the state-space equation, each row vector of the output matrix is ​​extracted one by one. Each row vector is then operated on with the right eigenvector to obtain the observability index of each candidate feedback signal. The observability indices of all candidate feedback signals are compared, and the signal with the largest observability index value is selected as the feedback signal.

[0029] Optionally, the step of modifying and expanding the model matrix obtained after order reduction to obtain the closed-loop system includes the following steps: The reduced-order model matrix is ​​modified and expanded to obtain the time-delay model; The delay models under all operating conditions are combined to form an uncertainty model; The closed-loop system, including the controller, is determined based on the uncertainty model.

[0030] Specifically, embodiments of this application can modify and extend the model matrix obtained after order reduction, introducing the delay effects generated by wide-area communication links to obtain a delay model describing the delay characteristics. Multiple delay models generated under different steady-state power flow convergence conditions are combined to form an uncertainty model capable of covering various operating modes. Based on this uncertainty model, the controller structure to be designed is incorporated to determine the closed-loop system including the controller.

[0031] Optionally, constructing the controller parameter optimization problem based on the closed-loop system includes the following steps: With the H∞ and H2 performance of the closed-loop system as optimization objectives, a controller parameter optimization problem based on linear matrix inequalities is constructed.

[0032] Specifically, in this embodiment, the H∞ and H2 performance requirements of the closed-loop system can be set as optimization objectives. Based on these optimization objectives, the constraints and objective function of the controller parameters are constructed in the form of linear matrix inequalities, generating a controller parameter optimization problem.

[0033] Optionally, solving the controller parameter optimization problem to obtain the feedback controller includes the following steps: The controller parameter optimization problem is solved using a two-stage linear matrix inequality algorithm. In the first stage, the state feedback controller is solved, and then the state feedback controller is substituted into the second stage to solve for the controller parameters, thus obtaining the output feedback controller.

[0034] Specifically, for the controller parameter optimization problem, this application embodiment can employ a two-stage linear matrix inequality algorithm for solution. In the first stage of the solution, a state feedback controller is calculated. Then, this state feedback controller is substituted into the linear matrix inequality required for the second stage to continue solving for the controller parameters, ultimately obtaining the output feedback controller.

[0035] Optionally, controlling the power system according to the feedback controller includes the following steps: The output feedback signal of the power system is dynamically acquired and sent to the feedback controller; The feedback controller calculates the corresponding damping control command online based on the feedback signal; The damping control command is sent to the controlled energy device so that the energy device can adjust the corresponding adjustable capacity or operating state, thereby suppressing low-frequency oscillations.

[0036] Specifically, during power system operation, this embodiment can dynamically acquire pre-selected output feedback signals and send these signals to the feedback controller in real time. The feedback controller performs online calculations based on the continuously received feedback signals and generates corresponding damping control commands in real time. These generated damping control commands are then sent to the controlled energy devices. In response to these commands, the controlled energy devices adjust their adjustable capacity or change their operating state, injecting additional damping into the system through power or state adjustments, thereby suppressing low-frequency oscillations.

[0037] The following sections will provide a detailed description and explanation of some optional embodiments of this application, using specific application examples.

[0038] For example, Figure 2 An example flowchart of a method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller, provided in an embodiment of this application.

[0039] Specifically, embodiments of this application may include the following technical solutions: 1. Based on the actual operating characteristics and dispatching arrangements of the power system, several typical operating conditions with steady-state power flow convergence are selected. The system is linearized at the steady-state operating point of each condition, yielding a linear time-invariant model and its state-space description as follows: ; in These are the system's state variables, output variables, and input variables, respectively. These are the state matrix, input matrix, and output matrix, respectively.

[0040] 2. Based on a linear time-invariant model, modal parameters such as participation factor, eigenvalues, and damping ratio are calculated. Mode analysis is then used to identify key inter-regional oscillation modes requiring enhanced damping. Among these, the participation factor... Represents state variables In eigenvalues The degree of participation in the oscillation mode, The larger the value, the more likely it is to indicate Pattern and The higher the correlation between states, the more accurate the calculation formula is: ; in, The total number of state variables. and State matrices Regarding eigenvalues The right and left eigenvectors.

[0041] 3. Among the candidate renewable energy power stations, a series of alternative control signals and output feedback signals are selected, and then the geometric controllability index of the alternative control signals is calculated. A larger controllability index indicates a greater influence of the control signal on the oscillation mode; therefore, the signal with the largest controllability index is selected as the control signal. The geometric observability index of the feedback signal is then calculated. The larger the observability index, the greater the degree to which the feedback signal reflects the oscillation mode. The signal with the largest observability index is selected as the feedback signal.

[0042] in: ; For matrix The Column vector, and the first Each input variable corresponds to one; For matrix The Row vector, and the first row vector Each output variable corresponds to one; These are the modulus and the Euclidean norm, respectively.

[0043] 4. For large-scale power systems, the linearized model has a high order. To improve the design efficiency of the new energy damping controller, the order of each linear time-invariant model is reduced based on the control signal and feedback signal to avoid interference from irrelevant oscillation modes in the controller design, while retaining the eigenvalue information of the main modes.

[0044] 5. Considering uncertainties such as communication delay and signal loss, the reduced-order system model matrix is ​​modified and expanded, where the delay... Corresponding approximate delay model The expression is as follows: ; in, For Laplace variables.

[0045] By combining the models under all operating conditions, a unified system uncertainty model is formed, and the expression for the closed-loop system including the controller is further obtained as follows: ; in, , For all working conditions, For the state variables of the closed-loop system. and For additional output, To add perturbation variables, This is the coefficient matrix corresponding to the state equation. The coefficient matrix of the H∞ performance output equation. This is the coefficient matrix of the H2 performance output equation.

[0046] 6. Construct a dynamic output feedback controller, and design a controller parameter optimization problem based on the linear matrix inequality, with the H∞ and H2 performance of the closed-loop system as optimization objectives. The expression is: ; in, and To coordinate Performance weighting coefficients; These are parameters related to H∞ performance; These are parameters related to H2 performance; It is the identity matrix; Represents the trace of a matrix; Configure the relevant parameters for the regional poles. For a circle centered at the origin, the interior angles are... The conical sector region, with an included angle Damping ratio with eigenvalue Closely related, it is often used in power systems to limit the damping ratio of oscillations, and correspondingly... for: ; 7. The above controller parameter optimization problem is solved using a two-stage linear matrix inequality algorithm. In the first stage, a state feedback controller is first solved. Then, substituting these parameters into the second stage solution for the remaining controller parameters, we finally obtain the complete output feedback controller, expressed as: ; in, These are the controller's state variables, output variables, and input variables, respectively. These are the controller's state matrix, input matrix, and output matrix, respectively.

[0047] 8. In actual operation, the system's output feedback signals are collected in real time. The signal is then sent to the feedback controller, which calculates the corresponding damping control command online based on the signal. The instructions are then sent to the controlled new energy equipment, and by adjusting its adjustable capacity or operating status, the low-frequency oscillation of the system can be effectively suppressed.

[0048] In summary, the embodiments of this application include the following key technical solutions: 1. The design of the new energy damping controller takes into account the uncertainty of the system's operating conditions, effectively improving the system's damping characteristics in different scenarios; 2. When establishing the system model, further consider the transmission delay of feedback signals and the scenario of signal loss to improve the reliability of the controller in wide-area measurement scenarios; 3. Based on the control requirements, the controller can be flexibly deployed in different new energy power plants to maximize the utilization rate of new energy.

[0049] The embodiments of this application include at least the following beneficial effects: 1. The embodiments of this application are applicable to new power systems with a high proportion of new energy access; 2. The embodiments of this application can effectively improve the damping ratio of the system under a wide range of operating conditions, making up for the shortcomings of controllers that only consider a single operating condition and cannot adapt to changes in operating conditions; 3. The embodiments of this application can provide sufficient damping for the system in scenarios where there is a transmission delay or even partial signal loss in the system's measurement output feedback signal, effectively suppressing inter-regional oscillations; 4. The embodiments of this application can improve the utilization rate of new energy and enhance the stability of the system by adjusting the adjustable capacity of the new energy equipment.

[0050] Reference Figure 3This application also provides a power grid low-frequency oscillation suppression device based on a wide-area damping controller, which can implement the above-mentioned power grid low-frequency oscillation suppression method based on a wide-area damping controller. The device includes: The system modeling unit is used to linearize the power system at the steady-state operating point under multiple steady-state power flow convergence conditions, so as to obtain a linear time-invariant model and the corresponding state-space equations. A participation factor calculation unit is used to calculate the participation factor based on the state-space equation. A signal determination unit is used to determine control signals and feedback signals based on the participation factors; The system closed-loop unit is used to reduce the order of the linear time-invariant model according to the control signal and the feedback signal, and to modify and expand the model matrix obtained after the order reduction to obtain a closed-loop system. The problem construction unit is used to construct a controller parameter optimization problem based on the closed-loop system. The problem-solving unit is used to solve the controller parameter optimization problem to obtain a feedback controller; A system control unit for controlling the power system according to the feedback controller.

[0051] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0052] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method of this application. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0053] It is understood that the content of the above method embodiments is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the methods of this application, and the beneficial effects achieved are the same as those achieved by the methods of this application.

[0054] Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 101 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 102 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 102 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 102 and is called and executed by the processor 101. Input / output interface 103 is used to implement information input and output; The communication interface 104 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 105 transmits information between various components of the device (e.g., processor 101, memory 102, input / output interface 103, and communication interface 104); The processor 101, memory 102, input / output interface 103 and communication interface 104 are connected to each other within the device via bus 105.

[0055] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method of this application.

[0056] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0057] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0058] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0059] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0060] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0061] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0062] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0063] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0064] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0065] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0066] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0067] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0068] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0069] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller, characterized in that, The method includes the following steps: The power system is linearized at the steady-state operating point under multiple steady-state power flow convergence conditions to obtain a linear time-invariant model and the corresponding state-space equations. The participation factor is calculated based on the state-space equation. The control signal and feedback signal are determined based on the participating factors; The linear time-invariant model is reduced in order based on the control signal and the feedback signal. The model matrix obtained after the order reduction is then corrected and expanded to obtain a closed-loop system. The controller parameter optimization problem is constructed based on the closed-loop system. Solve the controller parameter optimization problem to obtain the feedback controller; The power system is controlled according to the feedback controller.

2. The method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller according to claim 1, characterized in that, The calculation of the participation factor based on the state-space equation includes the following steps: Determine the eigenvalues ​​of the state matrix based on the state-space equation; Determine the right and left eigenvectors of the eigenvalues; The participation factor is calculated based on the right eigenvector, the left eigenvector, and the total number of state variables in the state-space equation.

3. The method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller according to claim 2, characterized in that, The process of determining the control signal and feedback signal based on the participation factor includes the following steps: The controllability index is calculated based on the column vector of the input matrix in the state-space equation and the left eigenvector. The signal with the largest controllability index is selected as the control signal; The observability index is calculated based on the row vector of the output matrix in the state-space equation and the right eigenvector. The signal with the largest observability index is selected as the feedback signal.

4. The method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller according to claim 1, characterized in that, The process of correcting and expanding the model matrix obtained after order reduction to obtain the closed-loop system includes the following steps: The reduced-order model matrix is ​​modified and expanded to obtain the time-delay model; The delay models under all operating conditions are combined to form an uncertainty model; The closed-loop system, including the controller, is determined based on the uncertainty model.

5. The method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller according to claim 1, characterized in that, The process of constructing the controller parameter optimization problem based on the closed-loop system includes the following steps: With the H∞ and H2 performance of the closed-loop system as optimization objectives, a controller parameter optimization problem based on linear matrix inequalities is constructed.

6. The method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller according to claim 1, characterized in that, Solving the controller parameter optimization problem to obtain the feedback controller includes the following steps: The controller parameter optimization problem is solved using a two-stage linear matrix inequality algorithm. In the first stage, the state feedback controller is solved, and then the state feedback controller is substituted into the second stage to solve for the controller parameters, thus obtaining the output feedback controller.

7. The method for suppressing low-frequency oscillations in power grids based on a wide-area damping controller according to any one of claims 1 to 6, characterized in that, The step of controlling the power system according to the feedback controller includes the following steps: The output feedback signal of the power system is dynamically acquired and sent to the feedback controller; The feedback controller calculates the corresponding damping control command online based on the feedback signal; The damping control command is sent to the controlled energy device so that the energy device can adjust the corresponding adjustable capacity or operating state, thereby suppressing low-frequency oscillations.

8. A power grid low-frequency oscillation suppression device based on a wide-area damping controller, characterized in that, The device includes: The system modeling unit is used to linearize the power system at the steady-state operating point under multiple steady-state power flow convergence conditions, so as to obtain a linear time-invariant model and the corresponding state-space equations. A participation factor calculation unit is used to calculate the participation factor based on the state-space equation. A signal determination unit is used to determine control signals and feedback signals based on the participation factors; The system closed-loop unit is used to reduce the order of the linear time-invariant model according to the control signal and the feedback signal, and to modify and expand the model matrix obtained after the order reduction to obtain a closed-loop system. The problem construction unit is used to construct a controller parameter optimization problem based on the closed-loop system. The problem-solving unit is used to solve the controller parameter optimization problem to obtain a feedback controller; A system control unit for controlling the power system according to the feedback controller.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 7.

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