@inproceedings{dcfdd9dc280f4246ac7b1c26e982e897,
title = "Nonlinear network reduction for distribution networks using the holomorphic embedding method",
abstract = "This paper presents three different true nonlinear reduction methods to obtain network equivalents for radial (distribution-type) networks (using the holomorphically embedded power flow algorithm), which are exact, given computational precision limitations, even when the loads and the real-power generations are scaled. The proposed reduction methods are applied in this paper to reduce a radial distribution system and provide a two-bus-model equivalent which accurately models the real and reactive power load seen at the transmission network due to random changes in the distribution system load. Numerical results are provided for a radial 14-bus system to show the accuracy of the proposed methods in preserving voltages and slack bus power. The approach is shown to have better performance than Ward reduction even when the loads are increased in a random manner.",
keywords = "Extended Ward, Network reduction, REI, Ward, analytic continuation, holomorphic embedding method, power-flow",
author = "Shruti Rao and Daniel Tylavsky",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 48th North American Power Symposium, NAPS 2016 ; Conference date: 18-09-2016 Through 20-09-2016",
year = "2016",
month = nov,
day = "17",
doi = "10.1109/NAPS.2016.7747978",
language = "English (US)",
series = "NAPS 2016 - 48th North American Power Symposium, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Gao, {David Wenzhong} and Jun Zhang and Amin Khodaei and Eduard Muljadi",
booktitle = "NAPS 2016 - 48th North American Power Symposium, Proceedings",
}