An Improved Poincaré-like Carleman Linearization Approach for Power System Nonlinear Analysis

Title & Authors
An Improved Poincaré-like Carleman Linearization Approach for Power System Nonlinear Analysis
Wang, Zhou-Qiang; Huang, Qi; Zhang, Chang-Hua;

Abstract
In order to improve the performance of analysis, it is important to consider the nonlinearity in power system. The Carleman embedding technique (linearization procedure) provides an effective approach in reduction of nonlinear systems. In the approach, a group of differential equations in which the state variables are formed by the original state variables and the vector monomials one can build with products of positive integer powers of them, is constructed. In traditional Carleman linearization technique, the tensor matrix is truncated to form a square matrix, and then regular linear system theory is used to solve the truncated system directly. However, it is found that part of nonlinear information is neglected when truncating the Carleman model. This paper proposes a new approach to solve the problem, by combining the Poincar$\small{\acute{e}}$ transformation with the Carleman linearization. Case studies are presented to verify the proposed method. Modal analysis shows that, with traditional Carleman linearization, the calculated contribution factors are not symmetrical, while such problems are avoided in the improved approach.
Keywords
Carleman embedding;Poincar$\small{\acute{e}}$ transformation;Nonlinear analysis;Power system;
Language
English
Cited by
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