DocumentCode :
681691
Title :
Short-term wind prediction using an ensemble of Particle Swarm Optimised FIR filters
Author :
Dowell, Jethro ; Weiss, Steven
Author_Institution :
Wind Energy Syst. Centre for Doctoral Training, Univ. of Strathclyde, Glasgow, UK
fYear :
2013
fDate :
2-3 Dec. 2013
Firstpage :
1
Lastpage :
5
Abstract :
Due to the large and increasing penetration of wind power around the world, accurate power production forecasts are required to manage power systems and wind power plants. In this paper we propose an ensemble of particle swarm optimised filtering technique for 1-hour-ahead prediction of hourly mean wind speed and direction. The performance of the new method is assessed by testing it on data from 13 locations around the UK where it performs comparably to linear techniques but is able to provide significant improvement at a subset of locations.
Keywords :
FIR filters; filtering theory; load forecasting; particle swarm optimisation; wind power plants; 1 hour ahead prediction; FIR Filters; filtering technique; hourly mean wind direction; hourly mean wind speed; particle swarm optimisation; power production forecast; short term wind prediction; wind power penetration; wind power plant;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Intelligent Signal Processing Conference 2013 (ISP 2013), IET
Conference_Location :
London
Electronic_ISBN :
978-1-84919-774-8
Type :
conf
DOI :
10.1049/cp.2013.2065
Filename :
6740514
Link To Document :
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