Spatial Modelling of Extreme Wind Speed Distributions in Switzerland

被引：9

作者：

Laib, Mohamed ^{[1
]}

Kanevski, Mikhail ^{[1
]}

机构：

[1] Univ Lausanne, Fac Geosci & Environm, Inst Earth Surface Dynam, CH-1015 Lausanne, Switzerland

来源：

EUROPEAN GEOSCIENCES UNION GENERAL ASSEMBLY 2016 | 2016年 / 97卷

关键词：

Wind speed; Extreme values; Machine learning algorithms; Spatial modelling; Switzerland; PREDICTION; EVENTS;

D O I：

10.1016/j.egypro.2016.10.029

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The understanding of wind phenomena is of primary importance, especially regarding the renewable energy. One traditional way of wind modelling concerns the use of parametric probability distributions. This work presents a method in two steps to model this phenomena. The first of which studies and compares different extreme distributions by modelling data collected from the Swiss meteorological service. This comparison should serve as a basis for the second step, which applies spatial modelling of distribution parameters throughout the country. The modelling is performed in a high dimensional input space with the help of extreme learning machine. The knowledge of probability distributions allows us to give a comprehensive information about a wind speed distribution. (C) 2016 The Authors. Published by Elsevier Ltd.

引用

页码：100 / 107

页数：8

共 32 条

[1] [Anonymous], MACHINE LEARNING SPA
[2] Analysis of wind energy prospect for power generation by three Weibull distribution methods
Azad, A. K.
Rasul, M. G.
Islam, Rubayat
Shishir, Imrul R.
[J]. CLEAN, EFFICIENT AND AFFORDABLE ENERGY FOR A SUSTAINABLE FUTURE, 2015, 75 : 722 - 727
[3] Beirlant J., 2004, STAT EXTREMES THEORY, P500
[4] Linking extreme climate events and economic impacts: Examples from the Swiss Alps
Beniston, Martin
[J]. ENERGY POLICY, 2007, 35 (11) : 5384 - 5392
[5] Forest damages by the storm 'Lothar' in permanent observation plots in Switzerland:: The significance of soil acidification and nitrogen deposition
Braun, S
Schindler, C
Volz, R
Flückiger, W
[J]. WATER AIR AND SOIL POLLUTION, 2003, 142 (1-4) : 327 - 340
[6] Statistical inference for exploratory data analysis and model diagnostics
Buja, Andreas
Cook, Dianne
Hofmann, Heike
Lawrence, Michael
Lee, Eun-Kyung
Swayne, Deborah F.
Wickham, Hadley
[J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2009, 367 (1906): : 4361 - 4383
[7] One year of vertical wind profiles measurements at a Mediterranean coastal site of South Italy
Calidonna, Claudia Roberta
Gulli, Daniel
Avolio, Elenio
Federico, Stefano
Lo Feudo, Teresa
Sempreviva, Annamaria
[J]. EUROPEAN GEOSCIENCES UNION GENERAL ASSEMBLY 2015 - DIVISION ENERGY, RESOURCES AND ENVIRONMENT, EGU 2015, 2015, 76 : 121 - 127
[8] Castillo E., 1988, EXTREME VALUE THEORY, P380
[9] Coles S, 2001, An introduction to statistical modeling of extreme values, P221
[10] Wind speed prediction for wind farm applications by Extreme Value Theory and Copulas
D'Amico, Guglielmo
Petroni, Filippo
Prattico, Flavio
[J]. JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2015, 145 : 229 - 236

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