Fast Analysis Method of Small Disturbance Stable Eigenvalues Based on Cluster Computing Mode
A fast analysis and eigenvalue technology, applied in computing, resource allocation, program control design, etc., can solve problems such as the inability to guarantee that the search disc completely covers the specified search area, and meet the requirements of accuracy and real-time performance of calculation conclusions, The effect of improving utilization efficiency
Inactive Publication Date: 2020-11-03
CHINA SOUTHERN POWER GRID COMPANY +3
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In addition, another difficulty in eigenvalue search is the need to automatically determine whether the search disc covers the specified search area
If the new displacement point is determined according to the intersection of adjacent search discs, the area to be searched can only be continuously narrowed, and there is no guarantee that the search disc can completely cover the specified search area
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[0033] The present invention will be further described in detail below in conjunction with the embodiments and with reference to the accompanying drawings.
[0034] An embodiment of the present invention, its steps are as figure 1 Shown:
[0035] figure 1 In step 1, the power flow calculation is performed according to the power flow data, and the steady-state values of the variables under steady-state operating conditions are obtained; the nonlinear differential-algebraic equations are linearized near the steady-state values according to the stable data, and the linear differential-algebraic equations are obtained. Equation system, initialize the number of iterations k to 1;
[0036] figure 1 In step 2, it is described that the area to be searched is determined according to the eigenvalue frequency and damping ratio range defined by the user, and the area to be searched is divided into multiple sides with a side length of l according to the total number of CPU cores ava...
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The present invention discloses a fast analysis method for a small disturbance stability eigenvalue based on a cluster computing model, and belongs to the technical field of power systems and automation thereof. The method is applicable to automatically searching for all eigenvalues in a specified area based on cluster computing when small disturbance stability analysis is performed using an implicit restart Arnoldi algorithm, so as to meet requirements of huge-scale power grid small disturbance stability online analysis for accuracy and real-time performance of computing results. A specified to-be-searched area on a complex plane is divided into multiple square areas according to a quantity of idle CPU cores, and a center of the square area is selected as a displacement point of the implicit restart Arnoldi algorithm. If a search disc cannot cover a pre-specified square area, the square area is divided into four new square areas and a displacement point to be computed in a next round is determined, and the above process is repeated until a search area is fully covered. The method disclosed by the present invention can further improve utilization efficiency of computing resources.
Description
technical field [0001] The invention belongs to the technical field of power system automation, and in particular the invention relates to a fast analysis method for small disturbance stable eigenvalues based on a cluster computing mode. Background technique [0002] When the state matrix dimension of the small disturbance stability analysis is large, it is necessary to use the partial eigenvalue method to solve the eigenvalues that have a key impact on the stability judgment, so as to ensure that the calculation accuracy and speed can meet the requirements of large-scale power systems, but cannot Guaranteed to compute all weakly damped modes. The expansion of the grid scale and the increase of installed capacity will lead to a decrease in the frequency of oscillation modes, while the distribution of the modes is more dense. In addition to the weak damping mode, the dispatching operators are also concerned about the typical oscillation mode and its related characteristi...
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IPC IPC(8): G06F17/11G06F9/50
CPCG06F9/5027G06F17/11
Inventor 程哲鲍颜红徐伟王坚徐泰山刘韶峰邱生敏任先成夏小琴严明辉张金龙
Owner CHINA SOUTHERN POWER GRID COMPANY