eprintid: 729
rev_number: 8
eprint_status: archive
userid: 17
dir: disk0/00/00/07/29
datestamp: 2018-05-27 18:02:50
lastmod: 2018-05-27 18:02:50
status_changed: 2018-05-27 18:02:50
type: report
metadata_visibility: show
creators_name: Benjamin, Oscar
creators_name: Mina, Petros
creators_name: Arany, Laszlo
creators_name: Connaughton, Colm
creators_name: Cox, Sam
creators_name: Kresoja, Milena
creators_name: Shukla, Abhishek
creators_name: Wheatcroft, Ed
creators_name: Tull, James
creators_name: Groth, Samuel
creators_name: Jenkins, Sian
creators_name: Budd, Chris
creators_name: Smith, Leonard
corp_creators: Jeremy Parkes
title: Short term power forecasts for large offshore wind turbine arrays
ispublished: pub
subjects: environment
subjects: utilities
studygroups: esgi91
companyname: GL Garad Hassan
full_text_status: public
abstract: Methods are presented for precise prediction of windspeeds at a wind- farm using a combination of numerical weather prediction models and on-site wind speed measurements. Simple techniques are used to inves- tigate the properties of the data. More advanced techniques are tested for the predictive value in forecasting including techniques from autore- gressive models, data assimilation, artificial neural networks and kernel dressing. The performance of the resulting forecasts are compared with the measured wind speeds using a range of forecast windows.
date: 2013
citation:   Benjamin, Oscar and Mina, Petros and Arany, Laszlo and Connaughton, Colm and Cox, Sam and Kresoja, Milena and Shukla, Abhishek and Wheatcroft, Ed and Tull, James and Groth, Samuel and Jenkins, Sian and Budd, Chris and Smith, Leonard  (2013) Short term power forecasts for large offshore wind turbine arrays.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/729/1/ESGI91-Garad_CaseStudy.pdf