首页 | 本学科首页   官方微博 | 高级检索  
     


Wind speed spatial estimation for energy planning in Sicily: Introduction and statistical analysis
Authors:M. Cellura   G. Cirrincione   A. Marvuglia  A. Miraoui
Affiliation:aDipartimento di Ricerche Energetiche ed Ambientali (DREAM), Università degli Studi di Palermo, Viale delle Scienze, 90128 Palermo, Italy;bISSIA-CNR (Institute on Intelligent Systems for the Automation), Section of Palermo, via Dante12, Palermo, Italy;cUniversité de Technologie de Belfort-Montbeliard (UTBM), Belfort, France
Abstract:The exploitation of the renewable energy sources plays a key role for achieving the CO2 emissions reduction targets established by the Kyoto Protocol, as well as for facing the shortage of world fossil fuels reserves.In countries like Italy, with an high potential in terms of wind power generation, an efficient energy planning based on renewables is a very complex task. It encompasses many aspects: the resource availability assessment, the compliance with environmental and legislative constraints and last, but not least, the technical aspects linked to the safe integration to the grid of the intermittent power generated by the wind farms.This paper is the first part of a study addressing the first of the aforementioned issues. The wind measurements recorded in several stations of Sicily (Italy) were used for the spatial modelling of the wind fields over the region.A statistical analysis of the wind data has allowed the estimation of the parameters of the wind probability distribution function, that is a Weibull, as predicted by theory.In the last sections of the paper the results of some traditional deterministic and geostatistical interpolation techniques are shown. In the companion paper the maps of the estimated wind fields have been obtained by using the results of the statistical investigation accomplished here and coupling neural and geostatistical techniques. For a comprehensive evaluation of the forecasting accuracy of this neural kriging approach, those maps have to be compared with the maps showed in this paper.
Keywords:Neural networks   IDW   Kriging   Weibull   Sicily   Wind
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号