@article{Scarciotti:2016:10.1109/TPWRS.2016.2556747,
author = {Scarciotti, G},
doi = {10.1109/TPWRS.2016.2556747},
journal = {IEEE Transactions on Power Systems},
pages = {743--752},
title = {Low computational complexity model reduction of power systems with preservation of physical characteristics},
url = {http://dx.doi.org/10.1109/TPWRS.2016.2556747},
volume = {32},
year = {2016}
}

Download

TY  - JOUR
AB  - A data-driven algorithm recently proposed to solvethe problem of model reduction by moment matching is extendedto multi-input, multi-output systems. The algorithm isexploited for the model reduction of large-scale interconnectedpower systems and it offers, simultaneously, a low computationalcomplexity approximation of the moments and the possibilityto easily enforce constraints on the reduced order model. Thisadvantage is used to preserve selected slow and poorly dampedmodes. The preservation of these modes has been shown to beimportant from a physical point of view and in obtaining anoverall good approximation. The problem of the choice of the socalledtangential directions is also analyzed. The algorithm andthe resulting reduced order model are validated with the studyof the dynamic response of the NETS-NYPS benchmark system(68-Bus, 16-Machine, 5-Area) to multiple fault scenarios.
AU  - Scarciotti,G
DO  - 10.1109/TPWRS.2016.2556747
EP  - 752
PY  - 2016///
SN  - 1558-0679
SP  - 743
TI  - Low computational complexity model reduction of power systems with preservation of physical characteristics
T2  - IEEE Transactions on Power Systems
UR  - http://dx.doi.org/10.1109/TPWRS.2016.2556747
UR  - http://hdl.handle.net/10044/1/31257
VL  - 32
ER  - 

Download