Rapid-reading-writing electric-power-system PQ-decomposition-method flow data storage method based on sparse technology

Abstract

The invention discloses a rapid-reading-writing electric-power-system PQ-decomposition-method flow data storage method based on the sparse technology.The method includes the step that nonzero elements at the upper triangles and the lower triangles of arrays of Y(n, 2n), B'(n-1, n-1) and B''(m, m) in a traditional method are stored into an A(n, d) array formed by three virtual arrays of Y(n, d<1>), B'(n-1, d<2>) and B''(m, d<3>).The number of storage units is greatly decreased, the reading-writing speed of a data file and the calculating speed of I<pi> or I<qi> or P or Q during PQ-decomposition-method flow calculation are increased, the number of the storage units is also greatly decreased, and efficiency is greatly improved.Compared with the traditional method, the method has the advantages that as for an IEEE-118 node system, the largest number of the storage units is only 14.69% of that of the traditional method, the practical number of the storage units is only 6.66% of that of the traditional method, the data file writing time and the data file reading time are 14.32% and 7.29% of the data file writing time and the data file reading time of the traditional method respectively, and the larger the number of nodes is, the more obvious the advantages of the method are.

Description

technical field [0001] The invention belongs to the field of power system analysis and calculation. Background technique [0002] The power flow calculation of PQ decomposition method in power system involves the application of multiple symmetrical and extremely sparse coefficient matrices. If the sparsity of these coefficient matrices is not considered, a large number of zero-element data will lead to a great waste of storage space in the process of storage, reading and calculation, long time to read and write data files and calculation process, and low calculation efficiency. Therefore, considering the storage method of sparse matrix elements can not only save a lot of storage units, but also greatly reduce the time of storage, reading and calculation of data files. [0003] Three coefficient matrices are needed in the power flow calculation of the PQ decomposition method, among which the admittance matrix Y is used to calculate the node current (I pi , I qi ) and node ...

AI Technical Summary

Problems solved by technology

[0006] (2) The storage method of Y, B', B" array elements is unreasonable

Store corresponding elements in Y(n,2n), B′(n-1,n-1), B″(m,m) arrays, which will cause a great waste of storage space, read and write data files and calculate It takes too long to calculate I with Y(n,2n) array pi , I qi or P i , Q i The calculation efficiency is extremely low

If considering element sparsity, store Y, B', B" array elements by means of coordinate storage, sequential storage, linked list storage, etc., although a lot of storage units can be saved, but due to its complex storage method and structure , the diagonal elements and non-diagonal elements are stored separately, which makes the data reading process cumbersome, which is not conducive to the calculation and processing of data. Calculating I pi , I qi or P i , Q i , the process of importing corresponding elements is more complicated and the efficiency is not high

If considering the symmetry of the Y, B', B" array elements, only the non-zero elements of the upper triangle are stored, and the non-zero elements of the lower triangle are obtained according to the symmetry, the transformation of the subscripts and the assignment between elements also take a lot of time. not much advantage

[0008] (3) Y, B', B" array data files have a large number of storage, and the reading and writing time is long

The more data files are stored, the longer it takes to write data files, which also leads to more data files to be opened and longer time to read data files in the PQ decomposition method power flow calculation program, which is especially unfavorable for PQ Real-time calculation effect of decomposition method

Images