Method and system for estimating inertia center frequency of power system

Abstract

The invention discloses a method for estimating inertia center frequency of a power system, which comprises the following steps of: acquiring remote signaling data of a power grid model and a real-time monitoring system to carry out topology analysis to obtain a node branch model; calculating to obtain an expanded node admittance matrix and a generator node susceptance matrix according to the node branch model, the remote signaling data and reactance parameters in the generator; obtaining an inertia time constant of the generator, performing normalization processing to obtain an inertia constant vector, and performing calculation by using a multi-thread parallel technology to obtain a pseudo-inverse matrix and a weight vector of a generator node susceptance matrix; screening the elements in the weight vector by setting a threshold value, and performing normalization processing on the screened non-zero elements to obtain the bus position of the key node; the method obtains the bus frequency of the corresponding position, carries out estimation filtering on the bus frequency through unscented Kalman filtering, calculates the frequency of the inertia center of the power system based on the bus frequency, and has important reference significance for the selection of a power grid frequency monitoring point.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and in particular to a method and system for estimating the inertia centre frequency of a power system. Background Art

[0002] The frequency motion trajectory of the center of inertia (COI) of the power system reflects the overall dynamic trend of the power grid frequency to a certain extent. The difference between the angular velocity of the generator and the angular velocity of the COI in the frequency simulation is often used to determine the degree of deviation of the system from the initial operating point. The dynamic trajectory of the rotors of each synchronous generator set in the system under the COI coordinate system can effectively reflect the relative stability of the synchronous generator set relative to the overall trend of the system. The frequency of the center of inertia of the system cannot be directly measured and collected in the actual power grid. It needs to be calculated using the measured values ​​of the rotor speed of all generators in the power grid. The power grid operation control operator measures and monitors the frequency at certain nodes in the power grid, but the frequency of these nodes follows the dynamic behavior of the synchronous generators near them and does not represent the average frequency of the entire system.

[0003] On the one hand, the existing schemes on frequency estimation methods involve the field of microgrids, mainly a method, device, equipment and storage medium for frequency security assessment of microgrids. The method calculates the change curves of electric energy storage equipment, power generation equipment, load status data and environmental data through a pre-trained frequency estimation model to obtain the microgrid frequency curve of the microgrid. On the other hand, it involves the technical field of power system frequency estimation, and uses a wide linear model to establish an autoregressive expression of a complex voltage signal. According to the difference between the actual value and the estimated value of the complex voltage signal, the standard weight coefficient and the conjugate weight coefficient in the autoregressive expression are updated by a modified cost function, and the power system frequency estimation value at each moment is deduced by the two weight coefficients at each moment. There is no description of the estimation method of the inertia center frequency of power dispatching automation. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the present invention solves the problem that the grid operation control operator measures and monitors the frequencies at certain nodes in the grid, but the frequencies of these nodes follow the dynamic behavior of the synchronous generators nearby and cannot capture the inertial center frequency of the entire system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for estimating a center frequency of inertia of a power system, comprising:

[0008] Acquire the remote signaling data of the power grid model and the real-time monitoring system, perform topological analysis based on the remote signaling data of the power grid model and the real-time monitoring system, and obtain a node branch model;

[0009] According to the node branch model and the internal reactance parameters of the generator, an extended node susceptance matrix including the internal reactance of the generator and a node susceptance matrix of the generator are obtained;

[0010] Obtaining the inertia time constant of the generator, and calculating a normalized inertia constant vector according to the inertia time constant of the generator;

[0011] According to the generator node susceptance matrix and the normalized inertia constant vector, a pseudo-inverse matrix and a weight vector of the generator node susceptance matrix are calculated by using multi-threaded parallel technology;

[0012] The elements in the weight vector are screened by setting a threshold value, and the non-zero elements after screening are normalized to obtain the busbar position of the key node;

[0013] The bus frequency at the corresponding position is obtained according to the bus position of the key node, the bus frequency is estimated and filtered by using an unscented Kalman filter, and the frequency of the inertia center of the power system is calculated based on the bus frequency.

[0014] As a preferred solution of the method for estimating the center frequency of inertia of the power system described in the present invention, the topological analysis based on the remote signaling data of the power grid model and the real-time monitoring system includes:

[0015] When the telesignal data does not exceed the set range compared with the previous telesignal data, the local topology method is used to perform topology analysis;

[0016] When the telesignal data and the previous telesignal data change beyond the set range, the global topology method is used to perform topological analysis to form a node branch model.

[0017] As a preferred solution of the method for estimating the center frequency of inertia of the power system described in the present invention, the node admittance matrix includes:

[0018] In the power flow calculation, a high-dimensional sparse node susceptance matrix is ​​formed according to the reactance between nodes, an extended high-dimensional sparse susceptance matrix is ​​formed according to the internal reactance of the synchronous generator, and a high-dimensional sparse generator node susceptance matrix is ​​formed according to the internal reactance of the synchronous generator;

[0019] When the telesignaling data is unchanged from the last telesignaling state, the extended node admittance matrix and the generator node admittance matrix formed last time are directly used.

[0020] As a preferred solution of the method for estimating the inertia center frequency of the power system described in the present invention, wherein: calculating the normalized inertia constant vector according to the generator inertia time constant includes:

[0021] The inertia time constant of all generators is converted to the inertia time constant under the reference capacity;

[0022] The total inertia time constant is obtained by summing the inertia time constants of all generators converted to the reference capacity;

[0023] The inertia time constant of each generator converted to the reference capacity is divided by the total inertia time constant to obtain the normalized inertia time constant of the generator.

[0024] As a preferred solution of the method for estimating the center frequency of inertia of the power system described in the present invention, wherein: the pseudo-inverse matrix and weight vector of the generator node susceptance matrix are calculated by multi-threaded parallel technology, including:

[0025] The pseudo-inverse matrix of the generator node susceptance matrix is ​​expressed as the transpose of the high-dimensional sparse generator node susceptance matrix formed according to the internal reactance of the generator multiplied by itself to obtain a matrix product, the matrix product is inverted to obtain an inverse matrix, and the inverse matrix is ​​multiplied by the transpose of the high-dimensional sparse generator node susceptance matrix formed according to the internal reactance of the generator to obtain a pseudo-inverse matrix of the generator node susceptance matrix;

[0026] The weight vector is expressed as the product of the normalized inertia time constant vector and the pseudo-inverse matrix, the extended nodal susceptance matrix containing the internal reactance of the generator;

[0027] The weight vector is calculated by defining a structure for storing the column number and value set of a row of non-zero elements and a structure for storing non-zero elements of a sparse matrix. When calculating the elements in the weight vector, the value of the weight vector is obtained by vector multiplication using the transformed row vector of the normalized inertia constant matrix and the column vector in the sparse matrix.

[0028] As a preferred solution of the method for estimating the center frequency of inertia of a power system according to the present invention, screening the elements in the weight vector by setting a threshold value includes:

[0029] If the element in the weight vector is less than the set threshold value, the element at the corresponding position in the weight vector is set to zero;

[0030] The elements in the weight vector that are greater than or equal to the set threshold value are retained, and the elements of the filtered weight vector are normalized.

[0031] As a preferred solution of the method for estimating the center frequency of inertia of the power system described in the present invention, the frequency of the center of inertia of the power system includes:

[0032] The unit vector is subtracted from the bus frequency vector to obtain a new vector. The dot product of the weight vector and the new vector is calculated to obtain the calculation result. The calculation result is multiplied by the element value in the weight vector and added by 1 to obtain the frequency of the inertia center of the power system.

[0033] In a second aspect, the present invention provides a system for estimating the inertia center frequency of a power system, comprising:

[0034] A topology analysis module is used to obtain the remote signaling data of the power grid model and the real-time monitoring system, and perform topology analysis based on the remote signaling data of the power grid model and the real-time monitoring system to obtain a node branch model;

[0035] A susceptance matrix forming module is used to obtain an extended node susceptance matrix including the internal reactance of the generator and a generator node susceptance matrix according to the node branch model and the internal reactance parameters of the generator;

[0036] A calculation module, used for obtaining the inertia time constant of the generator, and calculating a normalized inertia constant vector according to the inertia time constant of the generator;

[0037] A multi-threaded matrix-vector multiplication parallel calculation module calculates the pseudo-inverse matrix and weight vector of the generator node susceptance matrix according to the generator node susceptance matrix and the normalized inertia constant vector using multi-threaded parallel technology;

[0038] A screening module is used to screen the elements in the weight vector by setting a threshold value, and normalize the screened non-zero elements to obtain the busbar position of the key node;

[0039] The filtering module is used to obtain the bus frequency of the corresponding position according to the bus position of the key node, estimate and filter the bus frequency using an unscented Kalman filter, and calculate the frequency of the inertia center of the power system based on the bus frequency.

[0040] In a third aspect, the present invention provides a computing device, comprising:

[0041] Memory and processor;

[0042] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for estimating the inertia center frequency of the power system are implemented.

[0043] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for estimating the center frequency of inertia of a power system.

[0044] Beneficial effects of the present invention: The method for estimating the center frequency of inertia of the power system proposed in the present invention only relies on the frequencies of some nodes in the power grid, and is only based on the admittance matrix of the power grid and the inertia constant of the synchronous generator and its internal reactance parameters. It is not only applicable to the frequency calculation of the power grid during disturbance, but also uses steady-state frequency calculation. As the proportion of new energy power generation connected to the grid using power electronic interfaces is increasing, the node frequency signal obtained by the phase-locked loop technology widely used in its grid connection has gained a wider range of uses. The bus frequency is estimated and filtered by the unscented Kalman filter UKF, which can effectively avoid the bus frequency measurement from being affected by noise or even pulse noise, network attacks, communication loss, etc., and realize filtering and correction of the collected frequency measurement. The frequency of the power grid position with a larger weight in the calculation of the center frequency of inertia determined by the weight vector can be replaced by the frequency of its adjacent node. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0046] Figure 1 An overall flow chart of a method for estimating the inertia center frequency of a power system provided by the present invention;

[0047] Figure 2 A network topology diagram after topological analysis of a method for estimating the inertia centre frequency of a power system provided by the present invention. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0049] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0050] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0051] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0052] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0053] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] Example 1

[0055] Reference Figure 1 , as an embodiment of the present invention, provides a method for estimating the inertia center frequency of a power system, comprising:

[0056] S100: Acquire the remote signaling data of the power grid model and the real-time monitoring system, perform topology analysis based on the remote signaling data of the power grid model and the real-time monitoring system, and obtain a node branch model;

[0057] In the embodiment of the present application, when the telesignaling data does not change beyond the set range compared with the previous telesignaling data, a local topology method is used to perform topology analysis;

[0058] When the telesignal data and the previous telesignal data change beyond the set range, the global topology method is used to perform topological analysis to form a node branch model.

[0059] Specifically, the remote signaling data of the power grid model and real-time monitoring system include the power grid line reactance parameters, transformer reactance parameters, generator inertia time constant and its internal reactance parameters, topological connection relationship between devices and remote signaling status of switch blades required for frequency calculation;

[0060] The setting range can be one ten-thousandth of the total number of telesignals as the threshold value of the number of telesignals changed.

[0061] It should be noted that real-time monitoring of telesignaling data can monitor various indicators and parameters of the power grid in real time, discover problems and abnormal situations in a timely manner, and avoid accidents. The setting range of telesignaling data can be one ten-thousandth of the total number of telesignals as the threshold value of the change in the number of telesignals, which can help the system to efficiently identify and respond to important changes when the amount of data is huge.

[0062] S200: obtaining an extended node susceptance matrix including the internal reactance of the generator and a node susceptance matrix of the generator according to the node branch model and the internal reactance parameters of the generator;

[0063] In the embodiment of the present application, in the power flow calculation, a high-dimensional sparse node susceptance matrix is ​​formed according to the reactance between nodes, an extended high-dimensional sparse susceptance matrix is ​​formed according to the internal reactance of the synchronous generator, and a high-dimensional sparse generator node susceptance matrix is ​​formed according to the internal reactance of the synchronous generator;

[0064] When the telesignaling data is unchanged from the last telesignaling state, the extended node admittance matrix and the generator node admittance matrix formed last time are directly used.

[0065] Specifically, according to the node branch model, the internal reactance parameters and telesignaling data of the online generator form the susceptance matrix B BB , B Bs , B BG , where B BB is the high-dimensional sparse node susceptance matrix (n×n dimension) formed according to the reactance (ignoring resistance) between nodes in the power flow calculation, B Bs is the susceptance matrix formed only according to the internal reactance of the generator, B BG is a high-dimensional sparse generator node susceptance matrix (n×m dimensions) formed only according to the internal reactance of the generator;

[0066] When the telesignal status obtained this time does not change from the telesignal status obtained last time, the susceptance matrix B formed last time is directly used. BB , B Bs , B BG ;

[0067] According to B BB and B Bs Calculate the extended node susceptance matrix B BBS , where BBBS =B BB +B Bs The node admittance matrix B is formed by using the node admittance matrix formation method in the power system flow calculation program and the branch superposition method is used according to the reactance of the line and transformer branches between nodes. BB At the node connected to the generator, the node susceptance matrix B is corrected according to the internal reactance of the generator BB Thus directly forming B BBS , there is no need to perform matrix addition operations during implementation.

[0068] According to B Bs form in It is an m×m dimensional matrix. In implementation, it is directly obtained according to the reactance value in the generator and the topological node where it is located. The element values ​​in , without the need for matrix multiplication and matrix inversion operations.

[0069] When the telesignaling state obtained this time does not change from the telesignaling state obtained last time, the expanded node susceptance matrix B formed last time is directly used. BBS .

[0070] It should be noted that this method can reduce the consumption of computing resources and improve computing efficiency, which is crucial for real-time monitoring and control of power grids because it can ensure the speed and reliability of the power grid under various operating conditions.

[0071] S300: Acquire the generator inertia time constant, and calculate a normalized inertia constant vector according to the generator inertia time constant;

[0072] In the embodiment of the present application, the inertia time constants of all generators are converted to the inertia time constants under the reference capacity;

[0073] The total inertia time constant is obtained by summing the inertia time constants of all generators converted to the reference capacity;

[0074] The inertia time constant of each generator converted to the reference capacity is divided by the total inertia time constant to obtain the normalized inertia time constant of the generator.

[0075] Specifically, the generator inertia time constant H is obtained. H can be obtained from the dispatching automation system online through data services or from offline files. For a specific generator, H is a fixed constant and does not change with the change of the power grid operation mode. It only needs to be executed when a new unit is put into operation and does not need to be executed in normal operation calculations.

[0076] According to the inertia time constant H of the generator running online i Form the normalized inertial time constant vector h, where

[0077] The vector h is formed according to the real-time status of the generator-end outlet switch in the power grid and the topological nodes to which the generator is connected.

[0078] It should be noted that by considering the inertia time constant of the generator, the dynamic behavior of the power grid when it is disturbed can be taken into account for prediction and control. The normalized inertia time constant vector h can help the power grid dispatching agency understand the contribution of different generators to the grid frequency regulation, thereby optimizing the operation and control strategy of the power grid.

[0079] S400: According to the generator node susceptance matrix and the normalized inertia constant vector, a pseudo-inverse matrix and a weight vector of the generator node susceptance matrix are calculated by using multi-thread parallel technology;

[0080] In the embodiment of the present application, the pseudo-inverse matrix of the generator node susceptance matrix is ​​represented by multiplying the transpose of the high-dimensional sparse generator node susceptance matrix formed according to the internal reactance of the generator with itself to obtain a matrix product, inverting the matrix product to obtain an inverse matrix, and multiplying the inverse matrix with the transpose of the high-dimensional sparse generator node susceptance matrix formed according to the internal reactance of the generator to obtain a pseudo-inverse matrix of the generator node susceptance matrix;

[0081] The weight vector is expressed as the product of the normalized inertia time constant vector and the pseudo-inverse matrix, the extended nodal susceptance matrix containing the internal reactance of the generator;

[0082] The weight vector is calculated by defining a structure for storing the column number and value set of a row of non-zero elements and a structure for storing non-zero elements of a sparse matrix. When calculating the elements in the weight vector, the value of the weight vector is obtained by vector multiplication using the transformed row vector of the normalized inertia constant matrix and the column vector in the sparse matrix.

[0083] Specifically, the pseudo-inverse matrix is ​​calculated sequentially using multi-threaded parallel technology matrix Weight vector ξ T ,in

[0084] Since the matrix and the vector ξ T The calculation of each element in is independent of each other, and the OpenMP technology is used to implement the matrix in turn through parallel computing. matrix and vector ξ T Calculation.

[0085] based on is a diagonal matrix, h T For vectors, in calculation and When the number of grid nodes is large, no matter how large the number is, there is no need to perform matrix multiplication to realize the operation. The numerical calculation of the relevant single elements can be performed directly according to the characteristics of the diagonal matrix and the vector to quickly obtain and

[0086] Calculate the weight vector ξ T When , the sparse vector and the sparse matrix B BBS Use the associative container map provided by C++STL to define the structure for storage. Define a structure to store a row of non-zero column numbers and value sets; define a structure to store the sparse matrix B BBS Non-zero, given is a row vector. When calculating an element in the weight vector by column, there is no need to implement the operation through matrix multiplication. The element values ​​in B BBS The column vectors in the matrix are multiplied by vectors to obtain the value of the weight vector.

[0087] It should be noted that the use of OpenMP technology is due to the advantages of OpenMP such as good portability, high scalability, support for incremental parallel development, etc., and it is easy to embed into the control system architecture of actual production operation.

[0088] The value of the weight vector is the weight of the bus frequency to the system inertia center frequency. According to the value of the weight vector, the most important node or area in the power grid in terms of frequency dynamics can be determined, which has important reference significance for the dispatching center to select the power grid frequency monitoring point.

[0089] S500: Screening the elements in the weight vector by setting a threshold value, normalizing the screened non-zero elements, and obtaining the busbar position of the key node;

[0090] In the embodiment of the present application, if an element in the weight vector is less than a set threshold value, the element at the corresponding position in the weight vector is set to zero;

[0091] The elements in the weight vector that are greater than or equal to the set threshold value are retained, and the elements of the filtered weight vector are normalized.

[0092] Specifically, according to the set threshold value |ξ i |<ε1 for the element ξ in the weight vector ξ i Filter and set |ξ i |<ε1 is set to zero, and the non-zero ξ in the filtered ξ is i The values ​​are normalized, and the nodes with larger weights in the calculation of the inertia center frequency are determined according to the threshold value ε2, and their positions in the actual power grid are determined.

[0093] It should be noted that through screening and normalization processing, resources and attention can be focused on the most important parts of the power grid, improving the efficiency of analysis and decision-making. By identifying key nodes, the power grid can be managed and controlled more effectively, especially in the face of disturbances and faults, and can respond quickly and take necessary measures.

[0094] S600: obtaining the bus frequency at the corresponding position according to the bus position of the key node, estimating and filtering the bus frequency by using an unscented Kalman filter, and calculating the frequency of the inertia center of the power system based on the bus frequency;

[0095] In an embodiment of the present application, the unit vector is subtracted from the bus frequency vector to obtain a new vector, a dot product is performed between the weight vector and the new vector to obtain a calculation result, the calculation result is multiplied by the element value in the weight vector and added by 1 to obtain the frequency of the center of inertia of the power system.

[0096] Specifically, according to the determined bus position of the key node, the bus frequency collected by the phasor measurement unit device at the corresponding position or obtained by the phase-locked loop technology is obtained. When the telesignaling state obtained by this calculation is unchanged from the telesignaling state obtained last time, the weight vector formed last time is directly used to determine the grid position with a larger weight in the inertia center frequency calculation.

[0097] It should be noted that the use of unscented Kalman filtering to estimate and filter the bus frequency can effectively prevent the bus frequency measurement from being affected by noise or even pulse noise, network attacks, communication loss, etc., and realize the filtering and correction of the collected frequency measurement.

[0098] Specifically, the frequency of the center of inertia is expressed as:

[0099] ω COI =ξ T (ω B -1 n，1 )+1

[0100] Among them, ξ T is the weight vector, ω B Bus frequency, 1 n，1 is an all-one vector.

[0101] The sparse vector multiplication can be used to quickly implement the operation. The element value in the weight vector and the collected bus frequency are directly used as the sparse vector multiplication calculation to quickly obtain the value of the inertia center frequency. i |<ε1 filtered out nodes do not need to participate in the calculation;

[0102] When the telesignaling state obtained by this calculation is the same as the telesignaling state obtained last time, the weight vector formed by the last calculation is directly used and the inertia center frequency is calculated according to the latest bus frequency obtained.

[0103] It should be noted that this method allows errors or loss in frequency acquisition of some nodes. First, the bus frequency is estimated and filtered by using the unscented Kalman filter UKF, which can effectively avoid the bus frequency measurement from being affected by noise or even pulse noise, network attacks, communication loss, etc., and realize the filtering and correction of the acquisition frequency measurement. Second, according to the characteristics of electromagnetic wave propagation, the frequency of the grid position with a larger weight in the calculation of the inertial center frequency determined by the weight vector can be replaced by the frequency of its adjacent nodes. This method has strong fault tolerance.

[0104] The above is a schematic scheme of a method for estimating the center frequency of inertia of a power system in this embodiment. It should be noted that the technical scheme of the device for estimating the center frequency of inertia of a power system and the technical scheme of the method for estimating the center frequency of inertia of a power system described above belong to the same concept, and the details of the technical scheme of the device for estimating the center frequency of inertia of a power system in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the method for estimating the center frequency of inertia of a power system described above.

[0105] The device for estimating the inertia center frequency of the power system in this embodiment includes:

[0106] A topology analysis module is used to obtain the remote signaling data of the power grid model and the real-time monitoring system, and perform topology analysis based on the remote signaling data of the power grid model and the real-time monitoring system to obtain a node branch model;

[0107] A susceptance matrix forming module is used to obtain an extended node susceptance matrix including the internal reactance of the generator and a generator node susceptance matrix according to the node branch model and the internal reactance parameters of the generator;

[0108] A calculation module, used for obtaining the inertia time constant of the generator, and calculating a normalized inertia constant vector according to the inertia time constant of the generator;

[0109] A multi-threaded matrix-vector multiplication parallel calculation module calculates the pseudo-inverse matrix and weight vector of the generator node susceptance matrix according to the generator node susceptance matrix and the normalized inertia constant vector using multi-threaded parallel technology;

[0110] A screening module is used to screen the elements in the weight vector by setting a threshold value, and normalize the screened non-zero elements to obtain the busbar position of the key node;

[0111] The filtering module is used to obtain the bus frequency of the corresponding position according to the bus position of the key node, estimate and filter the bus frequency using an unscented Kalman filter, and calculate the frequency of the inertia center of the power system based on the bus frequency.

[0112] This embodiment further provides a computing device, which is applicable to estimating the inertia center frequency of a power system, and includes:

[0113] A memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method for estimating the inertia center frequency of the power system as proposed in the above embodiment.

[0114] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for estimating the inertia center frequency of a power system as proposed in the above embodiment is implemented.

[0115] The storage medium proposed in this embodiment and the method for estimating the center frequency of inertia of the power system proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0116] Through the above description of the implementation mode, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation mode. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (FLASH), a hard disk or an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of various embodiments of the present invention.

[0117] Example 2

[0118] Reference Figure 2 , which is different from the first embodiment, provides a verification test of a method for estimating the center frequency of inertia of an electric power system, in order to verify and illustrate the technical effects adopted in this method.

[0119] like Figure 2 As shown in the figure, BS1~BS5 are the network topology diagrams after topology analysis, including two traditional synchronous generators G1 and G2 and a virtual synchronous generator VSG. The resistance parameters of the equipment are ignored. The reactance parameters of each device are shown in the figure x 1 、x 2 、x 3 、x 4 and x′ d，1 , x′ d，2 , x′d，3 shown.

[0120] The node admittance matrix B of the system BBS for:

[0121]

[0122] B BG for:

[0123]

[0124] The rated capacities of generators G1, G2 and VSG are S 1 , S 2 , S 3 , the normalized inertia time constants calculated to the reference capacity are h 1 、h 2 、h 3 , nodes 4 and 5 are not connected to generators, and the inertia time constant is zero, then h = [h 1 h 2 h 3 0 0].

[0125] Based on the matrix B BBS , B BG 、hAccording to Calculate the weight vector ξ T =[ξ 1 ξ 2 ξ 3 0 0]In fact T A large number of elements are zero and less than 1, and the threshold value ε1 is set, |ξ i |<ε1 for the element ξ in the weight vector ξ i Filter and set |ξ i |<ε1 is set to zero, and the non-zero ξ in the filtered ξ is i The value is normalized, and the node with a larger weight in the calculation of the inertia center frequency is determined according to the threshold value ε2, such as the weight vector ξ T The vector processed according to the threshold value is ξ T =[ξ 1 0 ξ 3 0 0] / (ξ 1 +ξ 3 ), and 1 >ξ 3 , then the node frequency of node 1 has a greater influence on the inertia center frequency than node 3, and node 2 has a greater influence on the inertia center frequency due to ξ 2 If the frequency is less than the threshold, the effect of the frequency on the inertial center frequency is ignored.

[0126] Assume that the node frequencies of nodes 1, 2, 3, 4, and 5 are ω respectively.1 ,ω 2 ,ω 3 ,ω 4 ,ω 5 ,but where ω 4 =ω 5 =0, then according to ω COI =ξ T (ω B -1 n，1 )+1 to calculate the frequency of the center of inertia.

[0127] This method improves the accuracy and efficiency of power system analysis. Through real-time monitoring and fast calculation, it enhances the real-time and dynamic response capabilities of the system. By using multi-threaded parallel technology, it significantly improves the calculation speed of large-scale power systems. The application of unscented Kalman filtering improves the accuracy and stability of bus frequency estimation.

[0128] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for estimating the center frequency of inertia of a power system, characterized in that: include: Acquire the remote signaling data of the power grid model and the real-time monitoring system, perform topological analysis based on the remote signaling data of the power grid model and the real-time monitoring system, and obtain a node branch model; According to the node branch model and the internal reactance parameters of the generator, an extended node susceptance matrix including the internal reactance of the generator and a node susceptance matrix of the generator are obtained; Obtaining the inertia time constant of the generator, and calculating a normalized inertia constant vector according to the inertia time constant of the generator; According to the generator node susceptance matrix and the normalized inertia constant vector, a pseudo-inverse matrix and a weight vector of the generator node susceptance matrix are calculated by using multi-threaded parallel technology; The elements in the weight vector are screened by setting a threshold value, and the non-zero elements after screening are normalized to obtain the busbar position of the key node; The bus frequency at the corresponding position is obtained according to the bus position of the key node, the bus frequency is estimated and filtered by using an unscented Kalman filter, and the frequency of the inertia center of the power system is calculated based on the bus frequency.

2. The method for estimating the center frequency of inertia of a power system according to claim 1, characterized in that: The topological analysis based on the power grid model and the remote signaling data of the real-time monitoring system includes: When the telesignal data does not exceed the set range compared with the previous telesignal data, the local topology method is used to perform topology analysis; When the telesignal data and the previous telesignal data change beyond the set range, the global topology method is used to perform topological analysis to form a node branch model.

3. The method for estimating the center frequency of inertia of a power system according to claim 1 or 2, characterized in that: The node admittance matrix includes: In the power flow calculation, a high-dimensional sparse node susceptance matrix is ​​formed according to the reactance between nodes, an extended high-dimensional sparse susceptance matrix is ​​formed according to the internal reactance of the synchronous generator, and a high-dimensional sparse generator node susceptance matrix is ​​formed according to the internal reactance of the synchronous generator; When the telesignaling data is unchanged from the last telesignaling state, the extended node admittance matrix and the generator node admittance matrix formed last time are directly used.

4. The method for estimating the center frequency of inertia of a power system according to claim 3, characterized in that: The normalized inertia constant vector calculated according to the generator inertia time constant includes: The inertia time constant of all generators is converted to the inertia time constant under the reference capacity; The total inertia time constant is obtained by summing the inertia time constants of all generators converted to the reference capacity; The inertia time constant of each generator converted to the reference capacity is divided by the total inertia time constant to obtain the normalized inertia time constant of the generator.

5. The method for estimating the center frequency of inertia of a power system as claimed in claim 4, characterized in that: The pseudo-inverse matrix and weight vector of the generator node susceptance matrix calculated by multi-threaded parallel technology include: The pseudo-inverse matrix of the generator node susceptance matrix is ​​expressed as the transpose of the high-dimensional sparse generator node susceptance matrix formed according to the internal reactance of the generator multiplied by itself to obtain a matrix product, the matrix product is inverted to obtain an inverse matrix, and the inverse matrix is ​​multiplied by the transpose of the high-dimensional sparse generator node susceptance matrix formed according to the internal reactance of the generator to obtain a pseudo-inverse matrix of the generator node susceptance matrix; The weight vector is expressed as the product of the normalized inertia time constant vector and the pseudo-inverse matrix, the extended nodal susceptance matrix containing the internal reactance of the generator; The weight vector is calculated by defining a structure for storing the column number and value set of a row of non-zero elements and a structure for storing non-zero elements of a sparse matrix. When calculating the elements in the weight vector, the value of the weight vector is obtained by vector multiplication using the transformed row vector of the normalized inertia constant matrix and the column vector in the sparse matrix.

6. The method for estimating the center frequency of inertia of a power system as claimed in claim 5, characterized in that: Screening the elements in the weight vector by setting the threshold value includes: If the element in the weight vector is less than the set threshold value, the element at the corresponding position in the weight vector is set to zero; The elements in the weight vector that are greater than or equal to the set threshold value are retained, and the elements of the filtered weight vector are normalized.

7. The method for estimating the center frequency of inertia of a power system as claimed in claim 6, characterized in that: The frequencies of the power system's center of inertia include: The unit vector is subtracted from the bus frequency vector to obtain a new vector. The dot product of the weight vector and the new vector is calculated to obtain the calculation result. The calculation result is multiplied by the element value in the weight vector and added by 1 to obtain the frequency of the inertia center of the power system.

8. A system for estimating the center frequency of inertia of a power system, characterized in that: include: A topology analysis module is used to obtain the remote signaling data of the power grid model and the real-time monitoring system, and perform topology analysis based on the remote signaling data of the power grid model and the real-time monitoring system to obtain a node branch model; A susceptance matrix forming module is used to obtain an extended node susceptance matrix including the internal reactance of the generator and a generator node susceptance matrix according to the node branch model and the internal reactance parameters of the generator; A calculation module, used for obtaining the inertia time constant of the generator, and calculating a normalized inertia constant vector according to the inertia time constant of the generator; A multi-threaded matrix-vector multiplication parallel calculation module calculates the pseudo-inverse matrix and weight vector of the generator node susceptance matrix according to the generator node susceptance matrix and the normalized inertia constant vector using multi-threaded parallel technology; A screening module is used to screen the elements in the weight vector by setting a threshold value, and normalize the screened non-zero elements to obtain the busbar position of the key node; The filtering module is used to obtain the bus frequency of the corresponding position according to the bus position of the key node, estimate and filter the bus frequency using an unscented Kalman filter, and calculate the frequency of the inertia center of the power system based on the bus frequency.

9. An electronic device, characterized in that: The device comprises: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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