<abstract xmlns="http://www.w3.org/1999/xhtml"><p>An effective nonlinear model reduction approach, empirical Gramians balanced reduction approach, is studied, to reduce the computation complexity in nonlinear power system model application. The realization procedure is: firstly, computing the empirical controllable and observable Gramians matrices of nonlinear power system model, secondly, by these two matrices, computing the balance transformation matrix to obtain the balanced system model of the original model, then, computing the controllable and observable matrices of the balanced system to obtain the diagonal Hankel singular matrix. Finally, deciding the lower-order subspace to obtain the reduced power system model. A 15-machine power system model is taken as an example to perform the reduction simulation analysis.</p></abstract>

An effective nonlinear model reduction approach, empirical Gramians balanced reduction approach, is studied, to reduce the computation complexity in nonlinear power system model application. The realization procedure is: firstly, computing the empirical controllable and observable Gramians matrices of nonlinear power system model, secondly, by these two matrices, computing the balance transformation matrix to obtain the balanced system model of the original model, then, computing the controllable and observable matrices of the balanced system to obtain the diagonal Hankel singular matrix. Finally, deciding the lower-order subspace to obtain the reduced power system model. A 15-machine power system model is taken as an example to perform the reduction simulation analysis.

Nonlinear power system model reduction based on empirical Gramians

School of Electrical and Electronic Engineering

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Nonlinear power system model reduction based on empirical Gramians"}

An effective nonlinear model reduction approach, empirical Gramians balanced reduction approach, is studied, to reduce the computation complexity in nonlinear...

Nonlinear power system model reduction based on empirical Gramians

Publié en ligne: 19 janv. 2018

Pages: 425 - 434

Reçu: 21 sept. 2017

DOI: https://doi.org/10.1515/jee-2017-0077

Mots clés
power system, nonlinear model reduction, empirical Gramians, balanced truncation

© 2017 Hongshan Zhao et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Nonlinear power system model reduction based on empirical Gramians

Publié en ligne: 19 janv. 2018

Pages: 425 - 434

Reçu: 21 sept. 2017

DOI: https://doi.org/10.1515/jee-2017-0077

Mots cléspower system, nonlinear model reduction, empirical Gramians, balanced truncation

© 2017 Hongshan Zhao et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Mots clés
power system, nonlinear model reduction, empirical Gramians, balanced truncation