Distributed calculation method and system for characteristic values of power system

Abstract

The invention discloses a distributed calculation method and system for characteristic values of a power system, and the method comprises the steps: carrying out the partitioning of nodes of the power system according to a topological relation, building a system node admittance matrix according to the nodes in different partitions, carrying out the equivalent simplification of the system node admittance matrix, obtaining an equivalent node admittance equation, determining an equivalent system corresponding to the equivalent node admittance equation, and carrying out the calculation of the characteristic values of the power system. A state equation is established for an equivalent system, a state matrix is obtained by using a matrix inversion lemma based on an equivalent node admittance equation and the state equation, and the state matrix is solved by using a QR method to obtain a characteristic value of the power system, so that the scale of processing the matrix is reduced, and inversion operation on a large-scale matrix is avoided; the method has the advantages that the method is simple and easy to implement, the influence of equivalently eliminating an external area is avoided, the communication frequency and the calculation amount of partition transmission are reduced, good convergence is still achieved, the requirement for communication conditions of the power system is lowered, and therefore the efficiency and the precision of characteristic value calculation in the partition environment of the power system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a distributed calculation method and system for power system characteristic values. Background Art

[0002] The rapid development of new energy sources at home and abroad has put forward more stringent requirements on the system regulation and support capabilities of the power system. With the increasing proportion of new energy, the flexible regulation resources of the power system are rapidly consumed. Its intermittent and volatile characteristics make the regulation of the power system more difficult, and the safety and stability issues are more prominent. The stability analysis of the power system is still a problem that needs to be faced. It is a common strategy to use distributed methods to calculate the eigenvalues ​​of the whole system to realize low-frequency oscillation analysis, small disturbance stability analysis, etc.

[0003] The operation and management of my country's power system has the characteristics of hierarchical partitioning. By utilizing the computing environment of power system partitions, the computing and surveying tasks are distributed to different partitions for coordinated solution, which can greatly improve the speed of calculation and the accuracy of partition information, while protecting the integrity and security of partition information. However, the current research results on small disturbance stability analysis in terms of partition calculation eigenvalues ​​are relatively few, especially for the characteristics of the power system environment of the partitions, which cannot adapt well to the independent security of information, and thus cannot guarantee the coordinated operation of the partitions of the calculation.

[0004] In the analysis and calculation of power systems, local changes in network structure, operating parameters, etc. are often involved. For example, in the online analysis application of power systems, calculations are required for a variety of operating conditions, but each condition only involves local changes in the power grid, and most other parts of the network remain unchanged. In this case, it is necessary to calculate the results of the network changes many times and in large quantities, and such calculations will inevitably involve a large number of repetitions. In such applications, if the information before the change can be effectively used to quickly calculate the information after the change, the speed and safety of the power grid calculation can be greatly improved. For this application scenario, the modified solution of the network equation can be used. The basic idea is to use a relatively small number of solutions to the network equations before the change to perform a relatively small amount of modified calculations, thereby obtaining the solution of the network equations after the change. The above-mentioned modified solution can greatly improve the calculation speed, so it has been widely used in the calculation field related to the power grid system.

[0005] The matrix inversion lemma is a proven and applied theorem that can simplify the calculation of the inverse matrix of a new matrix after a local change in the matrix. The basic idea of ​​the matrix inversion lemma is to calculate the inverse of a small-scale matrix related to its local change based on the inverse of the original matrix, and then obtain the inverse of the new matrix after the local change through appropriate transformation. Applying this theorem to the modified solution of the power system network equation can greatly reduce the difficulty of calculation and the amount of calculation in power system analysis.

[0006] The matrix inversion lemma has an application condition, which requires that the size of the locally changed matrix is ​​smaller than or equal to the size of the original matrix, which is difficult to guarantee in the small disturbance stability calculation application environment of the power system. At present, the management and control of the power grid has the characteristics of hierarchical partitioning. Each partition governs the dynamic data and parameters of the power grid in the area relatively independently, and the main data center can obtain the dynamic data and parameters of each partition through the interconnection line network between partitions. At the same time, the type and quantity of data that can be communicated between partitions are limited. The above reasons restrict the application of the matrix inversion lemma in the power system partition calculation environment, and the calculation efficiency and accuracy cannot be guaranteed.

[0007] In view of the above problems, the applicability of the traditional matrix inversion lemma in the partitioned environment of the power network needs to be studied. It is urgent to propose a distributed computing technology that applies the matrix inversion lemma and is suitable for the operation and management of the actual power system, and to improve the traditional matrix inversion lemma to adapt to the characteristics of the actual operation and management of the power system. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a distributed calculation method and system for eigenvalues ​​of an electric power system, which can improve the efficiency and accuracy of eigenvalue calculation in a partitioned environment of the electric power system.

[0009] In order to solve the above technical problems, a technical solution adopted by the present invention is: A distributed calculation method for power system characteristic values, comprising the steps of: Partitioning the nodes of the power system according to the topological relationship to obtain an internal area, a boundary area and an external area, and establishing a system node admittance matrix according to the nodes in the internal area, the boundary area and the external area; Performing equivalent simplification processing on the system node admittance matrix to obtain an equivalent node admittance equation, and determining an equivalent system corresponding to the equivalent node admittance equation, wherein the equivalent system is a power system from which the external area has been eliminated; Establishing a state equation for the equivalent system, and obtaining a state matrix using a matrix inversion lemma based on the equivalent node admittance equation and the state equation; The state matrix is ​​solved using an orthogonal triangular decomposition method to obtain eigenvalues ​​of the power system.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is: A distributed computing system for power system characteristic values, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Partitioning the nodes of the power system according to the topological relationship to obtain an internal area, a boundary area and an external area, and establishing a system node admittance matrix according to the nodes in the internal area, the boundary area and the external area; Performing equivalent simplification processing on the system node admittance matrix to obtain an equivalent node admittance equation, and determining an equivalent system corresponding to the equivalent node admittance equation, wherein the equivalent system is a power system from which the external area has been eliminated; Establishing a state equation for the equivalent system, and obtaining a state matrix using a matrix inversion lemma based on the equivalent node admittance equation and the state equation; The state matrix is ​​solved using an orthogonal triangular decomposition method to obtain eigenvalues ​​of the power system.

[0011] The beneficial effects of the present invention are as follows: the nodes of the power system are partitioned according to the topological relationship to obtain the internal area, the boundary area and the external area, and the system node admittance matrix is ​​established according to the nodes in different partitions, the system node admittance matrix is ​​equivalently simplified to obtain the equivalent node admittance equation, and the equivalent system corresponding to it is determined, the equivalent system has eliminated the external area, the state equation is established for the equivalent system, and the state matrix is ​​obtained by using the matrix inversion lemma based on the equivalent node admittance equation and the state equation, and the state matrix is ​​solved by using the orthogonal triangular decomposition method to obtain the characteristics of the power system The value is obtained by simplifying the equivalent value processing to reduce the scale of the processing matrix. By establishing the state equation for the equivalent system and introducing the matrix inversion lemma, the inversion operation of large-scale matrices is avoided. The orthogonal triangular decomposition method is used to solve the eigenvalues ​​to avoid the influence of the external area of ​​equivalent elimination. Each partition does not need to invert the large-scale matrix, which reduces the number of communications and the amount of calculation for partition transmission. At the same time, it still has good convergence. In the calculation process, it can also reduce the requirements for the communication conditions of the power system, thereby improving the efficiency and accuracy of the eigenvalue calculation in the partition environment of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flowchart of the steps of a distributed calculation method of a power system characteristic value according to an embodiment of the present invention; Figure 2A schematic diagram of the structure of a distributed computing system for power system characteristic values ​​according to an embodiment of the present invention; Figure 3 A calculation flow chart of a distributed calculation method for power system characteristic values ​​in an embodiment of the present invention; Figure 4 A system topology diagram of three machines and nine nodes in a distributed calculation method for power system characteristic values ​​according to an embodiment of the present invention; Figure 5 A simplified equivalent diagram of system partitions in a distributed calculation method for power system characteristic values ​​according to an embodiment of the present invention; Figure 6 Schematic diagram of distribution of characteristic values ​​calculated in a distributed calculation method for characteristic values ​​of a power system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0013] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0014] Please refer to Figure 1 , a distributed calculation method for power system characteristic values, comprising the steps of: Partitioning the nodes of the power system according to the topological relationship to obtain an internal area, a boundary area and an external area, and establishing a system node admittance matrix according to the nodes in the internal area, the boundary area and the external area; Performing equivalent simplification processing on the system node admittance matrix to obtain an equivalent node admittance equation, and determining an equivalent system corresponding to the equivalent node admittance equation, wherein the equivalent system is a power system from which the external area has been eliminated; Establishing a state equation for the equivalent system, and obtaining a state matrix using a matrix inversion lemma based on the equivalent node admittance equation and the state equation; The state matrix is ​​solved using an orthogonal triangular decomposition method to obtain eigenvalues ​​of the power system.

[0015] From the above description, it can be seen that the beneficial effects of the present invention are: the nodes of the power system are partitioned according to the topological relationship to obtain the internal area, the boundary area and the external area, and the system node admittance matrix is ​​established according to the nodes in different partitions, the system node admittance matrix is ​​equivalently simplified to obtain the equivalent node admittance equation, and the equivalent system corresponding to it is determined, the equivalent system has eliminated the external area, the state equation is established for the equivalent system, and the state matrix is ​​obtained by using the matrix inversion lemma based on the equivalent node admittance equation and the state equation, and the state matrix is ​​solved by using the orthogonal triangular decomposition method to obtain the power system The eigenvalues ​​of the system are obtained, thereby reducing the scale of the processing matrix through equivalent simplification. By establishing the state equation for the equivalent system and introducing the matrix inversion lemma, the inversion operation of large-scale matrices is avoided. The orthogonal triangular decomposition method is used to solve the eigenvalues ​​to avoid the influence of the external area of ​​equivalent elimination. Each partition does not need to invert the large-scale matrix, which reduces the number of communications and the amount of calculation for partition transmission. At the same time, it still has good convergence. In the calculation process, it can also reduce the requirements for the communication conditions of the power system, thereby improving the efficiency and accuracy of eigenvalue calculation in the partition environment of the power system.

[0016] Furthermore, partitioning the nodes of the power system according to the topological relationship to obtain the internal area, the boundary area and the external area includes: Determine dynamic element nodes from the power system, and use the dynamic element nodes as internal nodes to form an internal area; Nodes directly associated with the internal nodes in the internal area form a boundary area; The nodes that are not directly related to the boundary nodes in the boundary area form an external area.

[0017] From the above description, it can be seen that by partitioning the power system, the set of power generation nodes and the set of boundary nodes in the power system can be determined, which facilitates the subsequent equivalent simplification processing of the power system to improve the efficiency of eigenvalue calculation.

[0018] Further, the internal area includes internal nodes; The boundary area includes boundary nodes; The external area includes external nodes; The establishing of a system node admittance matrix according to the nodes in the inner area, the boundary area, and the outer area comprises: ; In the formula, represents the self-admittance of the internal node, represents the mutual admittance between internal nodes and boundary nodes, represents the mutual admittance between the boundary nodes and the internal nodes, represents the self-admittance of the boundary node, represents the mutual admittance between the boundary node and the external node, represents the mutual admittance between the external nodes and the boundary nodes, represents the self-admittance of the external node, represents the change in internal node voltage, represents the change in boundary node current, Represents the change in external node current, represents the change in the internal node current, represents the change in boundary node current, Indicates the change in external node current.

[0019] From the above description, it can be seen that a system node admittance matrix is ​​established according to the nodes in the internal area, the boundary area and the external area. Through the system node admittance matrix, the voltage and power flow of each node in the power system can be calculated, which is helpful to evaluate the stability and load distribution of the power system, and can be used for short-circuit analysis and voltage stability analysis.

[0020] Furthermore, the equivalent simplification processing is performed on the system node admittance matrix to obtain the equivalent node admittance equation, which includes: ; ; In the formula, represents the equivalent admittance of the boundary nodes.

[0021] From the above description, it can be seen that by equivalently simplifying the node admittance matrix of the power system, the relationship between the node admittance, current and voltage in the external area can be eliminated, and the order and scale of the node admittance matrix can be reduced, so as to facilitate the subsequent establishment of the state equation of the power system.

[0022] Furthermore, establishing the state equation for the equivalent system includes: ; In the formula, Indicates generator j The change in the state variable, A j Indicates generator j The first coefficient matrix of B j Indicates generator j The second coefficient matrix of Indicates the generator node voltage The change in the column vector consisting of the real and imaginary parts of Represents the generator node current The change in the column vector consisting of the real and imaginary parts of Cj Indicates generator j The third coefficient matrix of D j Indicates generator j The fourth coefficient matrix of .

[0023] From the above description, it can be seen that the scale of the state equation is greatly reduced at this time, which is conducive to the subsequent rapid calculation of the eigenvalue.

[0024] Further, the obtaining of the state matrix using the matrix inversion lemma based on the equivalent node admittance equation and the state equation comprises: The state equation is combined with the equivalent node admittance equation to obtain a linearized equation of the system at a steady-state operating point; Eliminating the system node voltage variation in the linearized equation; Calculate auxiliary inversion factors; The matrix inversion lemma is used to obtain a state matrix based on the linearized equation after eliminating the system node voltage variation and the auxiliary inversion factor.

[0025] From the above description, it can be seen that the application of equivalent systems and matrix inversion lemmas reduces the difficulty of calculating all the eigenvalues ​​of the system. There is no need to exchange internal information between partitions, but only one-way intersection with the boundary area for calculation and evaluation, which further reduces the number of communications between partitions to exchange information, and reduces the requirements for communication conditions of the power system during the calculation process. At the same time, the algorithm can still have good accuracy.

[0026] Furthermore, the state equation is combined with the equivalent node admittance equation to obtain a linearized equation of the system at a steady-state operating point, which includes: ; ; ; ; ; ; In the formula, represents the change of all state variables of the system, represents the fifth coefficient matrix, represents the sixth coefficient matrix, represents the seventh coefficient matrix, represents the eighth coefficient matrix, Represents the change in system node voltage, represents the simultaneous first coefficient matrix of the system generators, represents the simultaneous second coefficient matrix of the system generators, represents the third coefficient matrix of the simultaneous generators of the system, represents the fourth coefficient matrix of the simultaneous generators of the system, represents the self-admittance of the internal node, represents the mutual admittance between internal nodes and boundary nodes, represents the mutual admittance between the boundary nodes and the internal nodes, represents the equivalent admittance of the boundary nodes, Indicates n The first coefficient matrix of the generator, Indicates n The second coefficient matrix of the generator, Indicates n The third coefficient matrix of the generator, Indicates n The fourth coefficient matrix of the generator.

[0027] From the above description, it can be seen that by combining the state equation with the equivalent node admittance equation, the linearized equation of the system at the steady-state operating point is obtained, which is beneficial to the subsequent calculation of the state matrix and improves the overall calculation efficiency.

[0028] Further, eliminating the system node voltage variation in the linearized equation includes: ; In the formula, A represents the state matrix; The calculation of auxiliary inversion factors includes: ; In the formula, a represents the auxiliary inversion factor, From , .

[0029] From the above description, it can be seen that by using the matrix inversion lemma, the amount of calculation of the auxiliary inversion factor is significantly lower than that of the original inversion matrix, which improves the calculation speed.

[0030] Further, the use of the matrix inversion lemma to obtain the state matrix based on the linearized equation after eliminating the system node voltage variation and the auxiliary inversion factor includes: .

[0031] From the above description, it can be seen that in the equivalent system, the matrix order of the operation is greatly reduced, and all the accurate eigenvalues ​​of the system can be calculated based on the state matrix, which reduces the difficulty of operation.

[0032] Please refer to Figure 2Another embodiment of the present invention provides a distributed computing system for power system characteristic values, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements each step of the above-mentioned distributed computing method for power system characteristic values ​​when executing the computer program.

[0033] The above-mentioned distributed calculation method and system of power system characteristic values ​​of the present invention can be applied to power systems, and are described below through specific implementation methods: Please refer to Figure 1 , Figure 3-Figure 6 , Embodiment 1 of the present invention is: A distributed calculation method for power system characteristic values, comprising the steps of: S1. Partition the nodes of the power system according to the topological relationship to obtain the internal area, the boundary area and the external area, and establish the system node admittance matrix according to the nodes in the internal area, the boundary area and the external area, such as Figure 3 As shown, specifically including S11-S14: S11. Determine dynamic element nodes (such as generator nodes) from the power system, and use the dynamic element nodes as internal nodes to form an internal area, where the internal area includes internal nodes.

[0034] S12. Nodes directly associated with the internal nodes in the internal area form a boundary area, wherein the boundary area includes boundary nodes.

[0035] S13. Nodes that are not directly associated with the boundary nodes in the boundary area form an external area, where the external area includes external nodes.

[0036] Among them, the internal node set can be expressed as , each generator node stores the parameters and dynamic data of the power grid where the generator is located. The boundary node set can be expressed as , the boundary node set has the parameters and dynamic data of the inter-regional contact line network, and the external node set can be expressed as , the external node set includes loads and user terminals. And satisfy m=n , x Represents node-related variables, including node voltage changes , node current change And the corresponding admittance block Y . It is reflected in the system node admittance matrix formula, x G and x W , x W and xB The correlation matrix between the expressions of is not zero, x G and x W The incidence matrix of all nodes is zero matrix.

[0037] S14, establishing a system node admittance matrix according to the nodes in the inner area, the boundary area, and the outer area includes: After being divided into regions, the node admittance equation of the whole system can be expressed in blocks as follows: ; In the formula, Represents an internal node i The current change, Represents a boundary node i The current change, Represents an external node i The current change, Represents an internal node i The voltage change, Represents a boundary node i The voltage change, Represents an external node i The voltage change, Represents an internal node i The self-admittance, Represents a boundary node i The self-admittance, Represents an external node i The self-admittance, Represents an internal node i With boundary nodes i The mutual admittance of Represents a boundary node i With internal nodes i The self-admittance, Represents an external node i , j The mutual admittance of Represents an external node i With boundary nodes i The mutual admittance of Represents a boundary node i With external nodes i The self-admittance, Represents an external node i The self-admittance of .

[0038] Integrating the above formula, we can get the system node admittance matrix, which is: ; In the formula, represents the self-admittance of the internal node, represents the mutual admittance between internal nodes and boundary nodes, represents the mutual admittance between the boundary nodes and the internal nodes, represents the self-admittance of the boundary node, represents the mutual admittance between the boundary node and the external node, represents the mutual admittance between the external nodes and the boundary nodes, represents the self-admittance of the external node, represents the change in internal node voltage, represents the change in boundary node current, Represents the change in external node current, represents the change in the internal node current, represents the change in boundary node current, Indicates the change in external node current.

[0039] Among them, it can be seen from the above formula that , , , , is a diagonal block matrix, and .

[0040] By partitioning the power system according to topological relationships and dividing the nodes into three categories, the set of power generation nodes and the set of boundary nodes in the power system can be determined, so as to facilitate the subsequent simplification of the node admittance equation of the power system.

[0041] S2. Performing equivalent simplification processing on the system node admittance matrix to obtain an equivalent node admittance equation, and determining an equivalent system corresponding to the equivalent node admittance equation, wherein the equivalent system is a power system from which the external area has been eliminated.

[0042] The equivalent simplification process of the system node admittance matrix to obtain the equivalent node admittance equation includes: From the third row in the system node admittance matrix, we can get: ; Substituting the above equation into the second row of the system node admittance matrix, we eliminate ,get: ; Since the external nodes consist of load nodes, In dynamic modeling, take 0 to integrate the information of the boundary area and the external area , , , , so the equivalent node admittance equation is specifically: ; ; In the formula, represents the equivalent admittance of the boundary nodes.

[0043] Observing the symmetric relationship in the above matrix topology, we can get , can be merged and stored. Since the subsequent generator modeling will not involve the nodes in the external area, an equivalent system with the external area eliminated has been obtained.

[0044] By simplifying the node admittance equation of the power system, the relationship between the node admittance, current and voltage in the external area can be eliminated, and the order and scale of the node admittance equation can be reduced to facilitate the subsequent establishment of the state equation of the power system.

[0045] S3, establish a state equation for the equivalent system, and obtain a state matrix based on the equivalent node admittance equation and the state equation using the matrix inversion lemma, such as Figure 3 As shown, specifically including S31-S35: S31, establishing a state equation for the equivalent system, specifically: ; In the formula, Indicates generator j The change in the state variables (including angular velocity, rotor angle, etc.), A j Indicates generator j The first coefficient matrix of B j Indicates generator j The second coefficient matrix of Indicates the generator node voltage The change in the column vector consisting of the real and imaginary parts of Represents the generator node current The change in the column vector consisting of the real and imaginary parts of C j Indicates generator j The third coefficient matrix of D j Indicates generator j The fourth coefficient matrix, the first coefficient matrix, the second coefficient matrix, the third coefficient matrix and the fourth coefficient matrix are related to the structure, parameters and operating conditions of the system.

[0046] The state equation is the generator j ( j =1,…,n).

[0047] S32, the state equation is combined with the equivalent node admittance equation to obtain the linearized equation of the system at the steady-state operation point, which is specifically: ; ; ; ; ; ; In the formula, represents the change of all state variables of the system, represents the fifth coefficient matrix, represents the sixth coefficient matrix, represents the seventh coefficient matrix, represents the eighth coefficient matrix, Represents the change in system node voltage, represents the simultaneous first coefficient matrix of the system generators, represents the simultaneous second coefficient matrix of the system generators, represents the third coefficient matrix of the simultaneous generators of the system, represents the fourth coefficient matrix of the simultaneous generators of the system, Indicates n The first coefficient matrix of the generator, Indicates n The second coefficient matrix of the generator, Indicates n The third coefficient matrix of the generator, Indicates n The fourth coefficient matrix of the generator.

[0048] S33, eliminating the system node voltage variation in the linearized equation, specifically: ; In the formula, A Represents the state matrix.

[0049] Among them, the state matrix A The calculation formula is: .

[0050] S34, calculating the auxiliary inversion factor, including: From the matrix inversion lemma, we know that: , known A for n × n A non-singular matrix of order,M , N for n × m The matrix of order, a for m × m is a non-singular matrix with m ≤ n . If the matrix auxiliary inversion factor is a reversible matrix, then The inverse matrix can be transformed into: ; In the original power system, m for Y BB The order of n for Y GG The order of m ≤ n ; But in the above equivalent system, m = n , so we can apply the matrix inversion lemma.

[0051] From , , then the auxiliary inversion factor is: ; In the formula, a Represents the auxiliary inversion factor.

[0052] S35, using the matrix inversion lemma to obtain a state matrix based on the linearized equation after eliminating the system node voltage variation and the auxiliary inversion factor, specifically: .

[0053] S4. Solve the state matrix using an orthogonal triangular decomposition (QR) method to obtain eigenvalues ​​of the power system.

[0054] The following provides a specific application scenario, namely an IEEE 3-machine 9-node system, using the above method of the present invention.

[0055] Reference Figure 4 and Figure 5 , the IEEE 3-machine 9-node system is divided into three areas, including the inner area, the boundary area, and the outer area. Among them, the inner area has nodes 1, 2, and 3, the boundary area has nodes 4, 7, and 9, and the inner area has nodes 5, 6, and 8; node 1 is connected to generator 1; area 3 has nodes 3, 6, and 9, and node 3 is connected to generator 3.

[0056] System parameters are shown in Tables 1 to 3. T J represents the inertia time constant, R a represents the excitation resistance, X d is the direct-axis reactance, represents the direct-axis transient reactance, X q represents the quadrature-axis reactance, represents the quadrature-axis transient reactance, represents the stator open-circuit time constant of the direct-axis field winding, represents the stator open-circuit time constant of the quadrature-axis damping winding, D represents the damping coefficient, T R , K A , T A , T B are the parameters of the generator self-shunt static excitation system, T R represents the time measurement constant, K A It represents the gain of the comprehensive amplification link. T A It represents the time constant of the comprehensive amplification link. T B Represents the inherent equivalent time constant of the excitation regulator.

[0057] Table 1 Generator data

[0058] Table 2 Flow data of normal operation

[0059] Table 3 Branch data

[0060] Divide the nodes into partitions to establish the system node admittance matrix: ; ; ; ; ; ; ; The boundary area integrates the information of the boundary area and the external area , , , , calculate the equivalent admittance of the boundary nodes: ; From this, we can obtain the equivalent nodal admittance equation of the equivalent system.

[0061] The state equation is established for the equivalent system, specifically: ; ; ; ; ; ; ; ; ; ; ; ; The above data of each generator node is collected from the boundary area to obtain the coefficient matrix: ; ; ; Compute the auxiliary inversion factor: ; Recalculate the state matrix A .

[0062] All characteristic values ​​of the original power system are calculated according to the QR method, as shown in Table 4 and Figure 6 shown.

[0063] Table 4 Calculated eigenvalue results

[0064] By comparing with the original power system characteristic values, it is found that the error of all calculated characteristic values ​​is less than one ten-thousandth, so the accuracy of the above method of the present invention is verified.

[0065] The distributed calculation method of the eigenvalue of the power system of the present invention performs equivalent simplification on the power system, so when calculating the state matrix, the equivalent admittance of the boundary nodes is inverted, which is the boundary nodes excluding the generator nodes and the external nodes, and the scale is small and it is a diagonal block matrix. Compared with the original system directly calculating the state matrix, it is necessary to invert the admittance matrix blocks of all nodes excluding the generator nodes, and its order is the sum of the number of boundary nodes and the number of external nodes, and the scale is large and the calculation scale is large. In addition, the admittance matrices used in the calculation of the state matrix of the system after equivalent processing are all of the same size as the generator node admittance block, and there is a set of repeated data, which reduces the data storage amount and improves the calculation efficiency at the same time.

[0066] Moreover, the above method of the present invention only requires each partition to transmit a small amount of processed data from each generator node in the internal area to the boundary area in a one-way manner, and does not require each generator node in the internal area to exchange information of each partition's internal nodes, especially the generator and load information of important nodes. Since the present invention does not require each internal important node to exchange detailed power data during the calculation process, the security independence of each partition can be maintained under the hierarchical and partitioned management system of my country's power system, which has practical significance.

[0067] In addition, the eigenvalues ​​calculated using the above method of the present invention are compared with the original power system eigenvalues, and their accuracy is verified. The above method of the present invention improves the calculation accuracy of the eigenvalues.

[0068] Please refer to Figure 2 , Embodiment 2 of the present invention is: A distributed computing system for power system characteristic values ​​comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step in the distributed computing method for power system characteristic values ​​in Embodiment 1 is implemented.

[0069] In summary, the present invention provides a distributed calculation method and system for eigenvalues ​​of an electric power system, which partitions the nodes of the electric power system according to the topological relationship to obtain internal areas, boundary areas and external areas, and establishes a system node admittance matrix according to the nodes in different partitions, performs equivalent simplification processing on the system node admittance matrix to obtain an equivalent node admittance equation, and determines an equivalent system corresponding to it, in which the external area has been eliminated, establishes a state equation for the equivalent system, and uses the matrix inversion lemma based on the equivalent node admittance equation and the state equation to obtain a state matrix, uses the orthogonal triangular decomposition method to solve the state matrix to obtain the eigenvalue of the electric power system, thereby reducing the scale of the processing matrix through equivalent simplification processing, and avoiding the problem of eigenvalues ​​by establishing a state equation for the equivalent system and introducing the matrix inversion lemma. The inversion operation of large-scale matrices is performed, and then the orthogonal triangular decomposition method is used to solve the eigenvalues, avoiding the influence of the external area of ​​equivalence elimination. Each partition does not need to perform inversion calculation on the large-scale matrix, reducing the number of communications and the amount of calculation for partition transmission, while still having good convergence. In the calculation process, the requirements for the communication conditions of the power system can also be reduced, thereby improving the efficiency and accuracy of eigenvalue calculation in the partition environment of the power system; and the application of the equivalent system and matrix inversion lemma reduces the difficulty of calculating all the eigenvalues ​​of the system. There is no need to exchange internal information between partitions, but a one-way intersection with the boundary area is used for calculation and evaluation, which further reduces the number of communications for exchanging information between partitions, reduces the requirements for the communication conditions of the power system during the calculation process, and the algorithm still has good accuracy.

[0070] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A distributed calculation method for power system characteristic values, characterized in that: Includes steps: Partitioning the nodes of the power system according to the topological relationship to obtain an internal area, a boundary area and an external area, and establishing a system node admittance matrix according to the nodes in the internal area, the boundary area and the external area; Performing equivalent simplification processing on the system node admittance matrix to obtain an equivalent node admittance equation, and determining an equivalent system corresponding to the equivalent node admittance equation, wherein the equivalent system is a power system from which the external area has been eliminated; Establishing a state equation for the equivalent system, and obtaining a state matrix using a matrix inversion lemma based on the equivalent node admittance equation and the state equation; The state matrix is ​​solved using an orthogonal triangular decomposition method to obtain eigenvalues ​​of the power system.

2. A distributed calculation method for power system characteristic values ​​according to claim 1, characterized in that: Partitioning the nodes of the power system according to the topological relationship to obtain the internal area, the boundary area and the external area includes: Determine dynamic element nodes from the power system, and use the dynamic element nodes as internal nodes to form an internal area; Nodes directly associated with the internal nodes in the internal area form a boundary area; The nodes that are not directly related to the boundary nodes in the boundary area form an external area.

3. A distributed calculation method for power system characteristic values ​​according to claim 1, characterized in that: The internal area includes internal nodes; The boundary area includes boundary nodes; The external area includes external nodes; The establishing of a system node admittance matrix according to the nodes in the inner area, the boundary area, and the outer area comprises: ； In the formula, represents the self-admittance of the internal node, represents the mutual admittance between internal nodes and boundary nodes, represents the mutual admittance between the boundary nodes and the internal nodes, represents the self-admittance of the boundary node, represents the mutual admittance between the boundary node and the external node, represents the mutual admittance between the external nodes and the boundary nodes, represents the self-admittance of the external node, represents the change in internal node voltage, represents the change in the boundary node current, Represents the change in external node current, represents the change in the internal node current, represents the change in the boundary node current, Indicates the change in external node current.

4. A distributed calculation method for power system characteristic values ​​according to claim 3, characterized in that: The equivalent simplification processing of the system node admittance matrix to obtain the equivalent node admittance equation includes: ； ； In the formula, represents the equivalent admittance of the boundary nodes.

5. A distributed calculation method for power system characteristic values ​​according to claim 1, characterized in that: The establishing of the state equation for the equivalent system comprises: ； In the formula, Indicates generator j The change in the state variable, A j Indicates generator j The first coefficient matrix of B j Indicates generator j The second coefficient matrix of Indicates the generator node voltage The change in the column vector consisting of the real and imaginary parts of Represents the generator node current The change in the column vector consisting of the real and imaginary parts of C j Indicates generator j The third coefficient matrix of D j Indicates generator j The fourth coefficient matrix of .

6. A distributed calculation method for power system characteristic values ​​according to claim 1, characterized in that: The obtaining of the state matrix by using the matrix inversion lemma based on the equivalent node admittance equation and the state equation comprises: The state equation is combined with the equivalent node admittance equation to obtain a linearized equation of the system at a steady-state operating point; Eliminating the system node voltage variation in the linearized equation; Calculate auxiliary inversion factors; The matrix inversion lemma is used to obtain a state matrix based on the linearized equation after eliminating the system node voltage variation and the auxiliary inversion factor.

7. A distributed calculation method for power system characteristic values ​​according to claim 6, characterized in that: The state equation is combined with the equivalent node admittance equation to obtain the linearized equation of the system at the steady-state operation point, which includes: ； ； ； ； ； ； In the formula, represents the change of all state variables of the system, represents the fifth coefficient matrix, represents the sixth coefficient matrix, represents the seventh coefficient matrix, represents the eighth coefficient matrix, Represents the change in system node voltage, represents the simultaneous first coefficient matrix of the system generators, represents the simultaneous second coefficient matrix of the system generators, represents the third coefficient matrix of the simultaneous generators of the system, represents the fourth coefficient matrix of the simultaneous generators of the system, represents the self-admittance of the internal node, represents the mutual admittance between internal nodes and boundary nodes, represents the mutual admittance between the boundary nodes and the internal nodes, represents the equivalent admittance of the boundary nodes, Indicates n The first coefficient matrix of the generator, Indicates n The second coefficient matrix of the generator, Indicates n The third coefficient matrix of the generator, Indicates n The fourth coefficient matrix of the generator.

8. A distributed calculation method for power system characteristic values ​​according to claim 7, characterized in that: Eliminating the system node voltage variation in the linearized equation includes: ； In the formula, A represents the state matrix; The calculation of auxiliary inversion factors includes: ； In the formula, a represents the auxiliary inversion factor, From , .

9. A distributed calculation method for power system characteristic values ​​according to claim 8, characterized in that: The state matrix is ​​obtained by using the matrix inversion lemma based on the linearized equation after eliminating the system node voltage variation and the auxiliary inversion factor, including: 。 10. A distributed computing system for power system characteristic values, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, each step in the distributed calculation method of power system characteristic values ​​described in any one of claims 1 to 9 is implemented.

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