Application of sparse symmetric factor table method in PQ decomposition method-based load flow calculation in rectangular coordinate system

Abstract

The invention provides the application of the sparse symmetric factor table method in the PQ decomposition method-based load flow calculation in a rectangular coordinate system and belongs to the field of power system analysis and computation. According to the technical scheme of the invention, data are read from a data file of a given structure, so that the data reading speed, the Ipi and Iqi or the delta Pi and delta Qi computation speed are greatly improved. Based on a rapidly formed table of sparse and symmetric factors, the column numbers and the numbers of triangular non-zero elements in the table are recorded. Meanwhile, the symmetric and sparse technology is adopted for the subsequent fast forward substitution and backward substitution calculation. During the active and reactive iteration process, the seidel way is introduced to accelerate the power flow calculation speed. Compared with the prior art, the time spend in reading the data file, forming the factor table, conducting the active and reactive iteration process and completing the power flow calculation total time are respectively 6.12%, 6.15%, 11.86% and 6.16% of those in the prior art for an IEEE-118 system. Meanwhile, the application is more obvious in advantage when the node number of a system is larger.

Description

technical field [0001] The invention belongs to the field of power system analysis and calculation, and relates to the power flow calculation of a Cartesian coordinate PQ decomposition method. Background technique [0002] Newton-Raphson method (Newton method) is the most commonly used method in power system power flow calculation. According to the calculation process, it can be divided into Cartesian coordinate and polar coordinate Newton method. After simplification, Cartesian coordinate and polar coordinate PQ decomposition method can be derived respectively. From the point of view of the calculation process, the polar coordinate Newton method has fewer equations than the Cartesian coordinate Newton method, the type and number of Jacobian matrix elements are also small, and sometimes the number of power flow iterations is one less, so the polar coordinate is better than the Cartesian coordinate Newton method. Applications appear to be broader. Similarly, the polar coordi...

AI Technical Summary

Problems solved by technology

If the B′ and B″ array elements are directly taken from the imaginary part of the Y array element, or if only the B′ and B″ array elements are the same but different from the imaginary part of the Y array element, it may affect the number of iterations of the PQ decomposition method power flow or convergence

[0007] (2) The storage and reading methods of Y, B', B" array elements are unreasonable

In addition, the feature that most of the non-zero elements in the three matrices have the same position is not used when storing and reading the Y, B', B" array elements

[0009] (3) Y, B', B" array data files have a large number of storage, and the reading and writing time is long

[0011] (4) The relationship between the non-zero element positions of Y, B', B" arrays is not fully utilized

In the traditional method, due to the lack of utilization of this feature, the waste of storage units and some unnecessary calculations in the process of forming the factor table

[0013] (5) The way of forming factor arrays for B', B" arrays is not suitable

[0015] 2) Insufficient application of sparse technology when forming factor tables

B′, B″ array and Y array have almost the same element structure, and are extremely sparse. If sparse technology is not used, the calculation efficiency is extremely low

The application of sparse technology in the triangular decomposition method is rare, while the application of sparse technology in the factor table method is extremely extensive, but not fully in place

Within the scope of the PQ node, the element structure of the B' and B" arrays is exactly the same, if the factor table of the B" array cannot be quickly formed according to the process of forming the factor table of the B' array, it will be wasteful to form the factor table of the B" array time

[0017] (6) Inadequate application of sparse technology in the process of using factor table for previous generation and back generation

[0018] After forming the factor table, sometimes the traditional method uses the non-zero elements of the triangle on the factor table to quickly return to find Δf i 、Δe i , but the number of non-zero elements in each row and the column number are stored separately, which does not make the calculation method optimal, and for ΔP i / e i , ΔQ i / e i The previous generation of computing did not take advantage of sparse technology

[0019] (7) The Seidel iteration method is not introduced in the active and reactive iteration process

[0020] The introduction of the Seidel iteration method not only has a great impact on the calculation speed of the PQ decomposition method, but also sometimes affects its convergence, while the Seidel iteration method is rarely introduced in the traditional PQ decomposition method

[0021] Due to the above reasons, the calculation speed of the traditional Cartesian coordinate PQ decomposition method is far from optimal, so it is hardly used.

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