DocumentCode :
70987
Title :
Statistical profiling of site wind resource speed and directional characteristics
Author :
Stephen, Brendan ; Galloway, Stuart ; McMillan, David ; Anderson, Lindsay ; Ault, G.
Author_Institution :
Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK
Volume :
7
Issue :
6
fYear :
2013
fDate :
Nov. 2013
Firstpage :
583
Lastpage :
592
Abstract :
Construction of a wind farm without a reliable plant margin forecast can jeopardise potential returns on investment from the outset. Meteorological and topological factors influence the wind characteristics across any site which in turn affects wind farm output, critical for localised generation, and also the dynamic loading of the turbine structure. The models developed in this study follow the generally advocated use of probability density estimation as a means of representing wind resource characteristics but, owing to differences, in characterisation that may be encountered, do not assume a single distribution form across all sites. A mixture modelling approach is adopted that removes the need for choosing distribution forms on a site by site basis. Advancing previous work constructing statistical distributions over congruent wind speed and direction observations of the wind resource characteristics at a given site, the proposed model, as a consequence of using a mixture distribution, captures both recurring regimes in the site behaviour along with their frequency of occurrence. Preliminary results using data sets from a diverse range of locations in Scotland demonstrate the variation in the forms of model learned; comparisons of the model with current and alternate practices are given through visualisation and resource assessment illustrations.
Keywords :
power generation economics; power system simulation; probability; statistical analysis; statistical distributions; wind power plants; wind turbines; Scotland; Statistical profiling; directional characteristics; dynamic loading; meteorological factor; mixture modelling approach; power system modeling; probability density estimation; reliable plant margin forecasting; resource assessment illustration; site wind resource speed representation; statistical distribution; topological factor; turbine structure; visualisation; wind farm construction;
fLanguage :
English
Journal_Title :
Renewable Power Generation, IET
Publisher :
iet
ISSN :
1752-1416
Type :
jour
DOI :
10.1049/iet-rpg.2012.0202
Filename :
6648796
Link To Document :
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