文章基本信息

标题：A Novel Approach to Generate Synthetic Wind Data
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作者：Arianna Naimo ; Arianna Naimo
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2014
卷号：108
页码：187-196
DOI：10.1016/j.sbspro.2013.12.830
语种：English
出版社：Elsevier
摘要：AbstractThe use of wind energy sources and its integration into power generation systems is assuming increasing importance. For this reason, new generation models for synthetic wind data are needed, in order to properly generate forecasts of wind speed and power. This data is fundamental in simulations carried out to analyze and improve the performances of wind generating units, and individuating the technical parameters of wind turbines that directly affect power production. In the present study a new model is developed in order to generate realistic synthetic wind data. Wind speed is modeled as a Weibull distribution, while wind speed forecast error is simulated using First-Order Auto-Regressive Moving Average-ARMA time-series models. Mathematical programming formulations for the Assignment Problem are used to model wind speed persistence features, which, as simulation results show in this work, are essential to properly obtain wind speed and power output forecasts.
关键词：electrical systems;synthetic wind forecast data generation;wind persistence;time-series models;Assignment Problem