A method and system for estimating the center frequency of inertia of a power system

Abstract

The application discloses an inertia center frequency estimation method of a power system, and comprises the following steps: obtaining a power grid model and remote signaling data of a real-time monitoring system to perform topology analysis, and obtaining a node branch model; calculating an extended node admittance matrix and a generator node admittance matrix according to the node branch model, the remote signaling data and a generator internal reactance parameter; obtaining a generator inertia time constant, performing normalization processing to obtain an inertia constant vector, and calculating a pseudo-inverse matrix of the generator node admittance matrix and a weight vector by using a multi-thread parallel technology; filtering elements in the weight vector by setting a threshold value, performing normalization processing on non-zero elements after the filtering, and obtaining a key node bus position; obtaining a bus frequency at a corresponding position, performing estimation filtering on the bus frequency by using an unscented Kalman filter, and calculating a frequency of an inertia center of the power system based on the bus frequency, which has important reference significance for selection of a power grid frequency monitoring point.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system automation, in particular to a method and system for estimating the center of inertia frequency of a power system. BACKGROUND

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

[0003] The existing frequency estimation method involves the microgrid field, which mainly estimates the frequency safety of a microgrid, calculates the change curve of the power storage device, the power generation device, the load state data and the environmental data through a pre-trained frequency estimation model, and obtains the microgrid frequency curve of the microgrid. On the other hand, it involves the power system frequency estimation technology field, which uses a wide linear model to establish an autoregressive expression of a complex voltage signal, updates the standard weight coefficient and the conjugate weight coefficient in the autoregressive expression by correcting the cost function according to the difference between the actual value and the estimated value of the complex voltage signal, and derives the power system frequency estimation value at each moment through the two weight coefficients at each moment. None of them describes the estimation method of the inertia center frequency of power dispatching automation. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the technical problem solved by the present application is that the grid operation control operator measures and monitors the frequency at certain nodes in the power grid, but the frequency at these nodes follows the dynamic behavior of the synchronous generators in their vicinity and cannot capture the inertia center frequency of the entire system.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

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

[0008] Obtain the power grid model and the telesign data of the real-time monitoring system, perform topology analysis according to the power grid model and the telesign data of the real-time monitoring system, and obtain a node branch model;

[0009] According to the node branch model and the internal reactance parameter of the generator, an extended node admittance matrix containing the internal reactance of the generator and a generator node admittance matrix are obtained;

[0010] Obtain the generator inertia time constant, and calculate a normalized inertia constant vector according to the generator inertia time constant;

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

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

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

[0014] As a preferred scheme of the power system inertia center frequency estimation method, wherein: the topology analysis according to the power grid model and the telesign data of the real-time monitoring system comprises:

[0015] When the telesign data and the telesign data of the last time change do not exceed the set range, the topology analysis is performed by using a local topology method;

[0016] When the telesign data and the telesign data of the last time change exceed the set range, the topology analysis is performed by using a global topology method to form the node branch model.

[0017] As a preferred scheme of the power system inertia center frequency estimation method, wherein: the node admittance matrix comprises:

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

[0019] When the telesign data and the telesign data of the last time do not change, 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 according to the present application, wherein: the calculation of the normalized inertia constant vector according to the inertia time constant of the generator includes:

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

[0022] The inertia time constants of all generators under the reference capacity are summed to obtain the total inertia time constant;

[0023] The inertia time constant of each generator under 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 inertia center frequency of the power system according to the present application, wherein: the calculation of the pseudo-inverse matrix of the generator node admittance matrix and the weight vector using multi-thread parallel technology includes:

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

[0026] The weight vector is represented as the product of the normalized inertia constant vector and the pseudo-inverse matrix, and the extended node admittance matrix containing the internal reactance of the generator;

[0027] The weight vector is calculated by defining a structure for storing a set of column numbers and values of non-zero elements in a certain row, and a structure for storing non-zero elements of a sparse matrix, and when calculating the elements in the weight vector, the values of the weight vector are calculated by using the row vectors of the transformation of the normalized inertia constant matrix and the column vectors in the sparse matrix for vector multiplication calculation.

[0028] As a preferred solution of the method for estimating the inertia center frequency of the power system according to the present application, wherein: the screening of 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 greater than or equal to the set threshold value are retained, and the elements in the screened weight vector are normalized.

[0031] As a preferred solution of the method for estimating the inertia center frequency of the power system according to the present application, wherein: the frequency of the inertia center of the power system includes:

[0032] The bus frequency vector is subtracted by a unit vector to obtain a new vector, a dot product of the weight vector and the new vector is calculated 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 power system inertia center.

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

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

[0035] An admittance matrix forming module is configured to obtain an extended node admittance matrix containing internal reactance of a generator and a generator node admittance matrix according to the node-branch model and the internal reactance parameter of the generator.

[0036] A calculation module is configured to obtain a generator inertia time constant, and calculate a normalized inertia constant vector according to the generator inertia time constant.

[0037] A multi-thread matrix-vector multiplication parallel calculation module is configured to calculate a pseudo-inverse matrix of the generator node admittance matrix and a weight vector according to the generator node admittance matrix and the normalized inertia constant vector by using a multi-thread parallel technology.

[0038] A screening module is configured to screen elements in the weight vector by setting a threshold value, and normalize non-zero elements after the screening to obtain a key node bus position.

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

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

[0041] A memory and a processor.

[0042] The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions, so as to realize the steps of the method for estimating the frequency of the power system inertia center.

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

[0044] The beneficial effects of the present application: the power system inertia center frequency estimation method proposed in the present application only relies on the frequency of part of the nodes in the power grid, and is based on the admittance matrix of the power grid and the inertia constant and internal reactance parameters of the synchronous generator. It is not only suitable for frequency calculation when the power grid is disturbed, but also uses steady-state frequency calculation. For new energy power generation with increasing proportion of power electronic interface grid connection, the node frequency signal obtained by the widely used phase-locked loop technology in grid connection has more extensive use. The bus frequency is estimated and filtered by using the unscented Kalman filter (UKF), which can effectively avoid the influence of bus frequency measurement caused by noise, even pulse noise, network attack, communication loss, etc. The filtering and correction of the collected frequency measurement are realized. For the frequency of the power grid position with a larger weight in the inertia center frequency calculation, the frequency of its adjacent nodes can be used to replace it. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor. Among them:

[0046] Figure 1 The overall flowchart of the power system inertia center frequency estimation method provided by the present application;

[0047] Figure 2 The network topology structure diagram after topology analysis of the power system inertia center frequency estimation method provided by the present application. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

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

[0050] Secondly, the "one embodiment" or "an embodiment" referred to herein means a specific feature, structure, characteristic, or combination of features and / or characteristics described herein that can be included in at least one implementation of the present application. The various appearances of "in one embodiment" or "an embodiment" in the specification do not all refer to the same embodiment, although they can.

[0051] The application is described in detail in conjunction with the schematic drawings. In the detailed description of the embodiments of the application, the sectional view of the device structure is partially enlarged without the general proportion for the convenience of illustration, and the schematic drawings are only examples which should not limit the scope of protection of the application. In addition, the three-dimensional spatial dimensions of length, width and depth should be included in the actual manufacture.

[0052] Meanwhile, in the description of the application, it should be noted that the terms "upper, lower, inner and outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the application. In addition, the terms "first, second or third" are only for the purpose of description and cannot be understood as indicating or implying relative importance.

[0053] Unless otherwise specifically defined and limited in the present application, the terms "mounting, connecting, connection" should be broadly understood, for example: it can be fixed connection, detachable connection or integral connection; it can also be mechanical connection, electrical connection or direct connection, it can also be indirectly connected through intermediate medium, or it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0054] Embodiment 1

[0055] Reference Figure 1 For an embodiment of the present application, an estimation method of the inertia center frequency of a power system is provided, comprising:

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

[0057] In the embodiment of the present application, when the change of the remote signaling data and the remote signaling data of the last time does not exceed the set range, the local topology method is used for topology analysis;

[0058] When the change of the remote signaling data and the remote signaling data of the last time exceeds the set range, the global topology method is used for topology analysis to form a node branch model.

[0059] Specifically, the power grid model and the telesign data of the real-time monitoring system include power grid line reactance parameters, transformer reactance parameters, generator inertia time constant and its internal reactance parameters, topological connection relationship between devices, and telesign state of the switch;

[0060] The setting range can be one ten-thousandth of the total telesign number threshold value of the varying telesign number.

[0061] It should be noted that the real-time monitoring telesign data can monitor various indicators and parameters of the power grid in real time, timely find problems and abnormal conditions, and avoid accidents. The setting range of the telesign data can be one ten-thousandth of the total telesign number threshold value of the varying telesign number, which can help the system to efficiently identify and respond to important changes when the data volume is large.

[0062] S200: obtaining an extended node admittance matrix containing generator internal reactance and a generator node admittance matrix according to the node branch model and the generator internal reactance parameter;

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

[0064] When the telesign data does not change from the last telesign 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 online running generator internal reactance parameter and the telesign data form admittance matrices B BB , B Bs , and B BG , respectively. BB , B Bs is an admittance matrix containing only the internal reactance of the generator, and B BG is a high-dimensional sparse generator node admittance matrix (n x m dimension) containing only the internal reactance of the generator.

[0066] When the telesign state obtained this time does not change from the telesign state obtained last time, the admittance matrices B BB , B Bs , and B BG formed last time are directly used.

[0067] The extended node admittance matrix B BB is calculated according to B Bs and B BBS , wherein BBBS = B BB + B Bs The forming method of the node admittance matrix in the power system flow calculation program is adopted, and the node admittance matrix B is formed by using the branch superposition method according to the reactance of the line and transformer branch between nodes BB The node admittance matrix B is corrected according to the internal reactance of the generator at the node connected with the generator BB Thus, B is directly formed BBS In implementation, no matrix addition operation is needed.

[0068] According to B Bs , the following equation is formed Wherein is an m x m matrix, and the element value in is directly obtained according to the internal reactance value of the generator and the topology node where the generator is located in implementation, without matrix multiplication and matrix inverse operation.

[0069] When the current obtained remote signaling state is not changed from the last obtained remote signaling state, the extended node admittance matrix B BBS is directly used.

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

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

[0072] In the embodiment of the application, the inertia time constant of all generators is calculated to the inertia time constant under the reference capacity;

[0073] The inertia time constants of all generators calculated to the reference capacity are summed to obtain the total inertia time constant;

[0074] The inertia time constant of each generator calculated 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 inertia time constant H of the generator is obtained, which can be obtained from the dispatching automation system online through the data service mode or from the offline file. For a specific generator, H is a fixed constant and does not change with the change of the power grid operating mode. Only when a new unit is put into operation, the execution is needed, and no execution is needed in the usual operation calculation.

[0076] According to the online running inertia time constant H of the generator i , the normalized inertia constant vector h is formed, wherein​

[0077] According to the real-time state of the generator terminal outlet switch breaker in the power grid and the topology node vector h connected by the generator.

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

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

[0080] In the embodiments of the present application, the pseudo-inverse matrix of the generator node admittance matrix is represented as the transpose of the high-dimensional sparse generator node admittance matrix formed according to the internal reactance of the generator multiplied by itself, the inverse matrix of the matrix product is obtained, and the pseudo-inverse matrix of the generator node admittance matrix is obtained by multiplying the inverse matrix with the transpose of the high-dimensional sparse generator node admittance matrix formed according to the internal reactance of the generator;

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

[0082] The weight vector is calculated by defining a structure for storing a certain row of non-zero element column number and value set, and a structure for storing non-zero elements of a sparse matrix, and when calculating the elements in the weight vector, the transformed row vector of the normalized inertia constant matrix and the column vector in the sparse matrix are used to calculate the value of the weight vector by vector multiplication.

[0083] Specifically, the pseudo-inverse matrix matrix weight vector ξ T , wherein

[0084] Since the calculation of each element in the matrix and the vector ξ T is independent, the OpenMP technology is used to realize the calculation of the matrix matrix and the vector ξ T by parallel calculation.

[0085] Based on is a diagonal matrix, h T is a vector, the calculation of and When the number of nodes in the power grid is large, the calculation is not realized by matrix multiplication, but the numerical calculation of the relevant single elements is directly performed according to the characteristics of the diagonal matrix and the vector to quickly obtain the weight vector and

[0086] The weight vector ξ is calculated T When the number of nodes in the power grid is large, the calculation is not realized by matrix multiplication, but the numerical calculation of the relevant single elements is directly performed according to the characteristics of the diagonal matrix and the vector to quickly obtain the weight vector and the sparse matrix B BBS The associated container map provided by C++ STL is used to store the definition structure, a structure is defined for storing the column number and value set of a non-zero element in a row, and a structure is defined for storing the sparse matrix B BBS Non-zero elements, in view of is a row vector, when calculating a certain element in the weight vector by column, the calculation is not realized by matrix multiplication, but the vector multiplication calculation is directly performed according to the element value in the row vector and the column vector in the matrix B BBS to obtain the value of the weight vector.

[0087] It should be noted that the OpenMP technology is used because OpenMP has good portability, high scalability, supports incremental parallelization development, and is easy to embed into the actual production operation of the control system architecture.

[0088] The value of the weight vector is the weight of the bus frequency on the system inertia center frequency, and the value of the weight vector can determine the most important node or region in the frequency dynamic aspect of the power grid, which has important reference significance for the selection of the frequency monitoring point of the power grid by the dispatch center.

[0089] S500: 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 position of the key node bus;

[0090] In the embodiment of the application, 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;

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

[0092] Specifically, according to the set threshold value |ξ i |<ε1, the elements ξ i in the weight vector ξ are screened, the value of |ξ i |<ε1 is set to zero, and the non-zero ξ i values in the screened ξ are normalized, the node with a larger weight in the inertia center frequency calculation is determined according to the threshold value ε2, and the position of the node in the actual power grid is determined.

[0093] It should be noted that by screening and normalization, resources and attention can be focused on the most important part of the power grid, improving the efficiency of analysis and decision-making, and by identifying key nodes, the power grid can be more effectively managed and controlled, especially in the face of disturbances and failures, enabling rapid response and taking necessary measures.

[0094] S600: Obtain the bus frequency of the corresponding position according to the key node bus position, estimate and filter the bus frequency by using the unscented Kalman filter, and calculate the frequency of the power system inertia center based on the bus frequency;

[0095] In the embodiments of the present application, the bus frequency vector is subtracted from the unit vector to obtain a new vector, the weight vector is calculated by point multiplication with the new vector to obtain a calculation result, and the calculation result is multiplied by the element value in the weight vector and added by 1 to obtain the frequency of the power system inertia center.

[0096] Specifically, according to the determined key node bus position, the bus frequency collected by the corresponding position of the phasor measurement unit device or obtained by using the phase-locked loop technology is obtained, when the remote signaling state obtained this time does not change from the remote signaling state obtained last time, the weight vector formed last time is directly used and the power grid position with larger weight in the inertia center frequency calculation is determined.

[0097] It should be noted that the unscented Kalman filter is used to estimate and filter the bus frequency, which can effectively avoid the influence of noise, even pulse noise, network attack, communication loss and the like on the bus frequency measurement, and realize filtering and correction of the collected frequency measurement.

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

[0099] ω COI =ξ T (ω B -1 n，1 )+1

[0100] Wherein, ξ T is a weight vector, ω B is a bus frequency, and 1 n，1 is a full one vector.

[0101] Sparse vector multiplication can be used to quickly realize operation, and the inertia center frequency value can be quickly obtained by directly using the element value in the weight vector and the collected bus frequency as sparse vector multiplication calculation according to the threshold value |ξ i |<ε1 filtered out nodes do not participate in the calculation.

[0102] When the remote signaling state obtained this time does not change from the remote signaling state obtained last time, the weight vector formed last time is directly used and the inertia center frequency is calculated according to the latest obtained bus frequency.

[0103] It should be noted that the method allows some nodes to collect errors or missing, first, the UKF is used to estimate the bus frequency filtering, which can effectively avoid the influence of bus frequency measurement by noise, even impulse noise, network attack, communication loss, etc., realize the filtering and correction of the collected frequency measurement. Two is according to the electromagnetic wave propagation characteristics, the frequency of the power grid position with larger weight in the inertial center frequency calculation of weight vector can be replaced by the frequency of its adjacent node, the method has strong fault tolerance.

[0104] The above is a schematic scheme of the power system inertia center frequency estimation method of the embodiment. It should be noted that the technical scheme of the power system inertia center frequency estimation device belongs to the same concept as the technical scheme of the power system inertia center frequency estimation method described above. The technical scheme of the power system inertia center frequency estimation device in this embodiment is not described in detail. Please refer to the description of the technical scheme of the power system inertia center frequency estimation method described above.

[0105] The power system inertia center frequency estimation device in this embodiment comprises:

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

[0107] A susceptance matrix forming module is configured to obtain an extended node susceptance matrix and a generator node susceptance matrix containing generator internal reactance according to the node branch model and a generator internal reactance parameter.

[0108] A calculation module is configured to obtain a generator inertia time constant, and calculate a normalized inertia constant vector according to the generator inertia time constant.

[0109] A multi-thread matrix vector multiplication parallel computing module is configured to calculate a pseudo-inverse matrix of the generator node susceptance matrix and a weight vector according to the generator node susceptance matrix and the normalized inertia constant vector, and utilize a multi-thread parallel technology.

[0110] A screening module is configured to screen elements in the weight vector by setting a threshold value, normalize non-zero elements after screening, and obtain a key node bus position.

[0111] A filtering module is configured to obtain a bus frequency at a corresponding position according to the key node bus position, estimate the bus frequency by using UKF, and calculate a frequency of a power system inertia center based on the bus frequency.

[0112] The embodiment also provides a computing device suitable for estimation of the inertia center frequency of a power system, comprising:

[0113] The memory is used for storing computer executable instructions, and the processor is used for executing the computer executable instructions to realize the estimation method of the inertia center frequency of the power system proposed in the above embodiment.

[0114] The embodiment also provides a storage medium having a computer program stored thereon, and the program is executed by a processor to realize the estimation method of the inertia center frequency of the power system proposed in the above embodiment.

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

[0116] Through the above description of the embodiments, those skilled in the art can clearly understand that the present application can be realized by means of software and necessary general hardware, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a FLASH memory, a hard disk or an optical disk, etc., including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of various embodiments of the present application.

[0117] Embodiment 2

[0118] Reference Figure 2 Unlike the first embodiment, a verification test of the estimation method of the inertia center frequency of the power system is provided to verify the technical effects adopted in the method.

[0119] As Figure 2 shown, BS1-BS5 are network topology structure diagrams after topology analysis, containing two traditional synchronous generators G1 and G2 and one virtual synchronous generator VSG, ignoring the resistance parameters of the devices, and the reactance parameters of the devices are shown as x1, x2, x3, x4 and x' d，1 , x' d，2 , x' d，3 .

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

[0121]

[0122] B BG is:

[0123]

[0124] The rated capacity of the generators G1, G2 and VSG is S1, S2, S3 respectively, the normalized inertia time constant reduced to the reference capacity is h1, h2, h3 respectively, the nodes 4 and 5 are not connected to the generator, and the inertia time constant is zero, so h = [h1 h2 h3 0 0].

[0125] Based on the matrix B BBS , B BG , h is calculated according to The weight vector ξ T = [ξ1 ξ2 ξ3 0 0] is actually ξ T A large number of elements in the matrix are zero and less than 1, a threshold value ε1 is set, |ξ i | < ε1, the elements ξ i in the weight vector ξ are screened, the values of |ξ i | < ε1 are set to zero, and the non-zero ξ i values in the screened ξ are normalized, according to the threshold value ε2 to determine the nodes with larger weights in the calculation of the inertia center frequency, for example, the weight vector ξ T According to the threshold value processed vector is ξ T = [ξ1 0 ξ3 0 0] / (ξ1+ξ3), and ξ1 > ξ3, the influence of the node frequency of node 1 on the inertia center frequency is greater than that of node 3, and the frequency of node 2 is ignored due to the threshold value of ξ2.

[0126] Let the node frequencies of nodes 1, 2, 3, 4, 5 be ω1, ω2, ω3, ω4, ω5 respectively, then where ω4 = ω5 = 0, the frequency of the inertia center is calculated according to ω COI = ξ T (ω B -1 n，1 ) + 1.

[0127] This method improves the accuracy and efficiency of power system analysis, enhances the real-time performance and dynamic response capability of the system through real-time monitoring and fast calculation, significantly improves the calculation speed of large-scale power systems by using multi-thread parallel technology, and improves the accuracy and stability of bus frequency estimation by using the unscented Kalman filter.

[0128] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not to limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced, without departing from the spirit and scope of the technical solutions of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A method for estimating the center frequency of inertia in a power system, characterized in that, include: Obtain remote signaling data from the power grid model and the real-time monitoring system, and perform topology analysis based on the power grid model and the real-time monitoring system to obtain the node branch model; Based on the nodal branch model and generator internal reactance parameters, the extended nodal susceptance matrix and the generator nodal susceptance matrix, which include the generator internal reactance, are obtained. Obtain the generator inertial time constant, and calculate the normalized inertial constant vector based on the generator inertial time constant; The pseudo-inverse matrix and weight vector of the generator node susceptance matrix are calculated using the generator node susceptance matrix and the normalized inertia constant vector, and multi-threaded parallel technology is used. By setting a threshold value to filter the elements in the weight vector, and normalizing the filtered non-zero elements, the position of the key node busbar is obtained. Based on the bus positions of the key nodes, the bus frequencies at the corresponding positions are obtained. The bus frequencies are estimated and filtered using unscented Kalman filtering. The frequency of the power system inertial center is then calculated based on the bus frequencies.

2. The method for estimating the center frequency of power system inertia as described in claim 1, characterized in that, Topology analysis based on the power grid model and remote signaling data from the real-time monitoring system includes: When the change between the remote signaling data and the previous remote signaling data does not exceed the set range, topology analysis is performed using the local topology method. When the changes between the remote signaling data and the previous remote signaling data exceed the set range, a topology analysis is performed using a global topology approach to form a node branch model.

3. The method for estimating the center frequency of power system inertia as described in claim 1 or 2, characterized in that, Based on the nodal branch model and generator internal reactance parameters, the extended nodal susceptance matrix and generator nodal susceptance matrix, which include the generator internal reactance, are obtained as follows: In power flow calculation, a high-dimensional sparse node susceptance matrix is ​​formed based on the reactance between nodes, an extended high-dimensional sparse susceptance matrix is ​​formed based on the internal reactance of the synchronous generator, and a high-dimensional sparse generator node susceptance matrix is ​​formed based on the internal reactance of the synchronous generator. When the remote signaling data is unchanged from the previous remote signaling state, the extended node admittance matrix and generator node susceptance matrix formed in the previous step are used directly.

4. The method for estimating the center frequency of power system inertia as described in claim 3, characterized in that, The normalized inertial constant vector calculated based on the generator's inertial time constant includes: The inertial time constant of all generators is reduced to the inertial time constant under the reference capacity. The total inertial time constant is obtained by summing the inertial time constants of all generators reduced to the reference capacity. The normalized inertial time constant of each generator is obtained by dividing the inertial time constant of each generator at the reference capacity by the total inertial time constant.

5. The method for estimating the center frequency of power system inertia as described in claim 4, characterized in that, The pseudo-inverse matrix and weight vector of the generator node susceptance matrix, calculated using multi-threaded parallel techniques, include: The pseudo-inverse of the generator node susceptance matrix is ​​represented by multiplying the transpose of the high-dimensional sparse generator node susceptance matrix formed by the generator internal reactance with itself to obtain a matrix product. The inverse of the matrix product is then obtained, and the inverse matrix is ​​multiplied by the transpose of the high-dimensional sparse generator node susceptance matrix formed by the generator internal reactance to obtain the pseudo-inverse of the generator node susceptance matrix. The weight vector is represented as the product of the normalized inertial time constant vector, the pseudo-inverse matrix, and the extended nodal susceptance matrix containing the generator internal reactance. The weight vector is defined by a structure for storing the non-zero element column indices and numerical sets of a row, and a structure for storing the non-zero elements of a sparse matrix. When calculating the elements in the weight vector, the value of the weight vector is obtained by multiplying the row vector of the normalized inertia constant matrix transformation with the column vector in the sparse matrix.

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

7. The method for estimating the center frequency of power system inertia as described in claim 6, characterized in that, The frequencies of the power system's center of inertia include: Subtracting the unit vector from the bus frequency vector yields a new vector. The weight vector is then multiplied by the new vector to obtain the result. This result is multiplied by the element values ​​in the weight vector and incremented by 1 to obtain the frequency of the power system's inertial center.

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

9. An electronic device, characterized in that, The device includes: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method described in 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 the processor, they implement the method described in any one of claims 1 to 7.

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