DocumentCode :
535625
Title :
Renewable resource dataset generators
Author :
Edwards, Gruffudd A. ; Dunn, Rod W.
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. of Bath, Bath, UK
fYear :
2010
fDate :
Aug. 31 2010-Sept. 3 2010
Firstpage :
1
Lastpage :
5
Abstract :
Designing flexible networks to cope with the broad range of plausible scenarios for the future of the electricity system in Great Britain (GB) demands adequate and appropriate renewable resource data. This paper reports on research aimed at developing algorithms capable of producing synthetic time series datasets of arbitrary length to represent the variable renewable resources available to generators. Attention to date has been on the wind resource, as this is the dominant technology. The algorithms will produce the datasets using time series models - building upon an existing `Bath Wind Model´ methodology, but modelling the resources as seasonal long memory processes. The datasets will be suitable for a range of studies, but particularly system adequacy studies using Monte-Carlo simulation.
Keywords :
Monte Carlo methods; data handling; renewable energy sources; time series; wind power plants; Great Britain demand; Monte-Carlo simulation; bath wind model methodology; electricity system future; flexible network design; long memory processes; plausible scenarios; renewable resource dataset generator; synthetic time series datasets; wind resource; Availability; Biological system modeling; Data models; Time series analysis; Wind speed; Monte-Carlo Simulation; seasonal long-memory process; solar energy; wind energy; wind modelling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Universities Power Engineering Conference (UPEC), 2010 45th International
Conference_Location :
Cardiff, Wales
Print_ISBN :
978-1-4244-7667-1
Type :
conf
Filename :
5649322
Link To Document :
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