Title :
Statistical Quantification of Voltage Violations in Distribution Network with Small Wind Turbines
Author :
Long, Chao ; Farrag, Mohamed Emad ; Zhou, Chengke
Author_Institution :
Sch. of Eng. & Built Environ., Glasgow Caledonian Univ., Glasgow, UK
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 :
distribution networks; statistical analysis; wind turbines; SWTs; commercial area; industrial area; residential area; small wind turbine; statistical quantification; typical UK distribution network model; voltage violation; Load modeling; Probabilistic logic; Production; Time series analysis; Voltage control; Wind speed; Wind turbines;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-0545-8
DOI :
10.1109/APPEEC.2012.6307216