@inproceedings{723754905e2b4ee8b1ad0bf747aa8851,
title = "Statistical quantification of voltage violations in distribution network with small wind turbines",
abstract = "This paper develops a statistical methodology to identify the probabilities of when and where the voltage violations occurring in residential, industrial and commercial areas respectively with cumulative penetration of SWTs. The proposed methodology is applied to a typical U.K. distribution network model, and results indicate that industrial and commercial weekends have the highest probabilities of voltage violations, and voltage violations are more likely to occur on residential weekdays and weekends than that of industrial and commercial weekdays.",
keywords = "small wind turbines (SWTs), statistic methodology, time-series approach, voltage violations",
author = "Chao Long and Farrag, {Mohamed Emad} and Chengke Zhou",
year = "2012",
month = sep,
day = "20",
doi = "10.1109/APPEEC.2012.6307216",
language = "English",
isbn = "9781457705458",
publisher = "IEEE",
booktitle = "2012 Asia-Pacific Power and Energy Engineering Conference: Proceedings",
address = "United States",
note = "2012 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2012 ; Conference date: 27-03-2012 Through 29-03-2012",
}