Wind speed modeling using a vector autoregressive process with a time-dependent intercept term
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- 作者：Matti Koivistoa ; matti.koivisto@aalto.fi" class="auth_mail" title="E-mail the corresponding author ; Janne Seppä ; nenb ; janne.seppanen@fingrid.fi" class="auth_mail" title="E-mail the corresponding author ; Ilkka Mellinc ; ilkka.mellin@aalto.fi" class="auth_mail" title="E-mail the corresponding author ; Jussi Ekströ ; ma ; jussi.ekstrom@aalto.fi" class="auth_mail" title="E-mail the corresponding author ; John Millara ; john.millar@aalto.fi" class="auth_mail" title="E-mail the corresponding author ; Ivan Mammarellad ; ivan.mammarella@helsinki.fi" class="auth_mail" title="E-mail the corresponding author ; Mika Komppulae ; mika.komppula@fmi.fi" class="auth_mail" title="E-mail the corresponding author ; Matti Lehtonena ; matti.lehtonen@aalto.fi" class="auth_mail" title="E-mail the corresponding author
- 关键词：Forecasting ; Generalized Pareto distribution ; Monte Carlo simulation ; Rank correlation ; Vector autoregressive model ; Wind speed
- 刊名：International Journal of Electrical Power & Energy Systems
- 出版年：2016
- 出版时间：May 2016
- 年：2016
- 卷：77
- 期：Complete
- 页码：91-99
- 全文大小：1734 K
文摘
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A time series model is presented to analyze wind speeds in multiple locations.
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A semi-parametric distribution is fitted for each individual location.
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A vector autoregressive model with a time-dependent intercept term is used.
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Both the spatial and temporal dependencies are considered in detail.
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Applications for the risk assessment of power systems are presented.