Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures

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Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures

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Title: Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures
Author(s):
Gomez-Lazaro, Emilio;
Bueso, Maria C.;
Kessler, Mathieu;
Martin-Martinez, Sergio;
Zhang, Jie (UT Dallas);
Hodge, Bri-Mathias;
Molina-Garcia, Angel
Date Created: 2016-02-02
Item Type: article
Keywords: Wind power
Weibull distribution
Akaike Information Criterion
Electric power production
Abstract: The Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power data are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.
Publisher: MDPI AG
ISSN: 1996-1073
Persistent Link: http://dx.doi.org/10.3390/en9020091
http://hdl.handle.net/10735.1/5824
Bibliographic Citation: Gomez-Lazaro, Emilio, Maria C. Bueso, Mathieu Kessler, Sergio Martin-Martinez, et al. 2016. "Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures." Energies 9(2), doi: 10.3390/en9020091
Terms of Use: CC BY 4.0 (Attribution)
©2016 The Authors. All Rights Reserved.
Sponsors: ”Ministerio de Economía y Competitividad” and the European Union (ENE2012-34603); Fulbright/Spanish Ministry of Education Visiting Scholar (PRX14/00694); U.S. Department of Energy (DE-AC36-08-GO28308).

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CC BY 4.0 (Attribution) Except where otherwise noted, this item's license is described as CC BY 4.0 (Attribution)