<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

Published Online: Jan 19, 2018

Page range: 425 - 434

Received: Sep 21, 2017

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

Keywords
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

Published Online: Jan 19, 2018

Page range: 425 - 434

Received: Sep 21, 2017

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

Keywordspower 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.

Keywords
power system, nonlinear model reduction, empirical Gramians, balanced truncation