TY - JOUR
T1 - A New H-IRKA Approach for Model Reduction with Explicit Modal Preservation
T2 - Application on Grids with Renewable Penetration
AU - Yogarathinam, Amirthagunaraj
AU - Kaur, Jagdeep
AU - Chaudhuri, Nilanjan Ray
N1 - Funding Information:
Manuscript received October 3, 2017; accepted November 26, 2017. Date of publication December 25, 2017; date of current version February 8, 2019. Manuscript received in final form November 27, 2017. This work was supported by NSF under Grant CNS 1657024. Recommended by Associate Editor P. Korba. (Corresponding author: Nilanjan Ray Chaudhuri.) The authors are with the School of Electrical Engineering and Computer Science, The Pennsylvania State University, State College, PA 16802 USA (e-mail: [email protected]; [email protected]; [email protected]). Digital Object Identifier 10.1109/TCST.2017.2779104
Publisher Copyright:
© 1993-2012 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Multi-input multi-output (MIMO) model reduction is essential for applying many modern control design methods in power systems. The challenges of MIMO model order reduction of the modern power grid increases with the inclusion of renewables such as inverter-interfaced wind farms, which introduces complexity in such power system models. The difficulty in reducing such models using gramian-based and modal truncation approaches is demonstrated, whereas a relatively new Interpolatory approach of the Iterative Rational Krylov Algorithm (IRKA) shows promising results. Next, a heuristic-based IRKA is proposed to improve the accuracy of model order reduction of modern grids with explicit preservation of the 'critical modes' of the system. Tests on a 16-machine New England-New York system with two doubly-fed induction generator-based wind farms and a larger Brazilian system model demonstrate the effectiveness of the proposed approach.
AB - Multi-input multi-output (MIMO) model reduction is essential for applying many modern control design methods in power systems. The challenges of MIMO model order reduction of the modern power grid increases with the inclusion of renewables such as inverter-interfaced wind farms, which introduces complexity in such power system models. The difficulty in reducing such models using gramian-based and modal truncation approaches is demonstrated, whereas a relatively new Interpolatory approach of the Iterative Rational Krylov Algorithm (IRKA) shows promising results. Next, a heuristic-based IRKA is proposed to improve the accuracy of model order reduction of modern grids with explicit preservation of the 'critical modes' of the system. Tests on a 16-machine New England-New York system with two doubly-fed induction generator-based wind farms and a larger Brazilian system model demonstrate the effectiveness of the proposed approach.
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U2 - 10.1109/TCST.2017.2779104
DO - 10.1109/TCST.2017.2779104
M3 - Article
AN - SCOPUS:85039766327
SN - 1063-6536
VL - 27
SP - 880
EP - 888
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
IS - 2
M1 - 8239650
ER -