Publication

Stability Study of a Complete Hydroelectric Production Site by Eigenvalues Analysis Method Based on Phase Variables

François Avellan, Jean-Jacques Simond, Basile Kawkabani
2010
Conference Papers

Abstract

The eigenvalues analysis method is generally applied to synchronous machines by using d,q-components. This paper presents the application of this method on an equivalent model for the synchronous machine based on phase variables a,b,c instead of d,q-components. The advantages of this approach, essential for programs using phase variables as state variables, are presented. The application of this method to a complete hydroelectric production site including hydraulic components (pump-turbine, penstock, gallery, reservoir…), permits the study and analysis of the interactions between the hydraulic, electric and regulation parts of the system. Results coming from the proposed eigenvalues analysis method and the numerical simulations confirm the interest of the presented approach.

Official source

https://infoscience.epfl.ch/entities/publication/983a01d4-c1af-4900-82ff-c8c80d4886d2

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François Avellan, Jean-Jacques Simond, Basile Kawkabani
2010
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/983a01d4-c1af-4900-82ff-c8c80d4886d2

About this result

Related concepts (32)

Principal component analysis

Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.

Eigenvalues and eigenvectors

In linear algebra, an eigenvector (ˈaɪgənˌvɛktər) or characteristic vector of a linear transformation is a nonzero vector that changes at most by a constant factor when that linear transformation is applied to it. The corresponding eigenvalue, often represented by , is the multiplying factor. Geometrically, a transformation matrix rotates, stretches, or shears the vectors it acts upon. The eigenvectors for a linear transformation matrix are the set of vectors that are only stretched, with no rotation or shear.

Electric machine

In electrical engineering, electric machine is a general term for machines using electromagnetic forces, such as electric motors, electric generators, and others. They are electromechanical energy converters: an electric motor converts electricity to mechanical power while an electric generator converts mechanical power to electricity. The moving parts in a machine can be rotating (rotating machines) or linear (linear machines).

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Stability Study of a Complete Hydroelectric Production Site by Eigenvalues Analysis Method Based on Phase Variables

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