A Fast Gauss-Seidel Power Flow Algorithm Based on Sparse Technology

Abstract

The invention provides a sparse technology-based fast Gauss-Seidel power flow algorithm for a power system and belongs to the analyzing and computing field of the power system. According to the technical scheme of the algorithm, data only containing non-zero elements in a data file are quickly read into an array Y(n, d), so that the reading time of a storage unit and the data file is greatly reduced. Vi and the Qi of a PV node are quickly calculated based on the array Y(n, d), so that the invalid computation of a large amount of zero elements is avoided. Meanwhile, an optimal acceleration factor is quickly determined based on the improved heuristics method, so that the iterative computation speed is greatly improved. The above algorithm is completely applicable to the checking calculation process of all IEEE systems, such as an IEEE-118 system. Compared with the prior art, the time spent in reading the data file is reduced by about 85%, and the time spent on the power flow iteration process is reduced by about 90%. Moreover, the entire computation time is reduced by about 88%. In addition, the more the nodes of a system, the greater the advantages of the algorithm.

Description

technical field [0001] The invention belongs to the field of power system analysis and calculation. Background technique [0002] Power flow calculation is the most basic and important calculation in power system analysis. It is the basis for power system operation, planning, safety and reliability analysis and optimization, and also the basis and starting point for various electromagnetic transient and electromechanical transient analysis. [0003] The Gaussian method was first introduced into the power flow calculation of the power system and can directly iteratively solve the node voltage equation. The principle of this method is simple, the memory requirement is small, the programming is easy, and the initial voltage requirement is low, such as 0.1, while the Newton method generally cannot be lower than 0.65, so it has a certain application range. In some of the higher requirements for the initial value of the iteration, such as the Newton-Raphson method (Newton method)...

AI Technical Summary

Problems solved by technology

Due to the high sparsity of the Y matrix, only a few non-zero elements have an impact on the change of node voltage in the iterative process, so that the change of each node voltage to the solution point is very slow, and the method of judging non-zero elements or traditional Sparse techniques are also not ideal

In addition, for the PV node, use the Y(n,2n) array to calculate Q i The efficiency is also extremely low, and the process of determining the best acceleration factor is too cumbersome

[0005] The Gauss-Seidel power flow algorithm (referred to as the Gaussian method) can be formed after introducing the Seidel iterative method into the Gaussian method. Although the above problems have been improved, the effect is still not ideal.

In addition, the node impedance matrix Z has also been considered for the Gaussian method power flow, but because the Z matrix is ​​full, the Gaussian method power flow iteration with the Z matrix has better convergence, but the calculation effect is still not ideal

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