eprintid: 39
rev_number: 5
eprint_status: archive
userid: 4
dir: disk0/00/00/00/39
datestamp: 2005-05-26
lastmod: 2015-05-29 19:45:54
status_changed: 2009-04-08 16:52:20
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Whiten, Bill
creators_name: Tsoularis, Tasos
creators_id: W.Whiten@uq.edu.au
creators_id: A.D.Tsoularis@massey.ac.nz
title: Prediction of power generation from a wind farm
ispublished: pub
subjects: utilities
studygroups: misg21
companyname: Transpower NZ Ltd
full_text_status: public
abstract: Wind farms produce a variable power output depending on the wind speed. For management of power networks and for bidding for the supply of power, the future power available needs to be predicted for time intervals ahead of a few minutes to about 24 hours.

This project used data from a wind farm and three meteorological stations to determine methods and ability to predict wind speed. Analyses using regression, neural networks, and a Kalman filter were examined. Prediction using a combination of local wind measure-ments and meteorological data appears to give the best results.
date: 2004
date_type: published
pages: 13
official_url: http://miis.maths.ox.ac.uk/past/MISG/2004/
citation:   Whiten, Bill and Tsoularis, Tasos  (2004) Prediction of power generation from a wind farm.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/39/1/misg2004wind.pdf
document_url: http://miis.maths.ox.ac.uk/miis/39/2/misg2004wind_efs.pdf