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Article

Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data

by
Daniel Villanueva
*,
Adrián Sixto
,
Andrés Feijóo
,
Antonio Fernández
and
Edelmiro Miguez
Electrical Engineering Department, University of Vigo, 36310 Vigo, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(9), 3317; https://doi.org/10.3390/app10093317
Submission received: 24 April 2020 / Revised: 6 May 2020 / Accepted: 7 May 2020 / Published: 10 May 2020
(This article belongs to the Special Issue Wind Turbine Data, Analysis and Models)
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Abstract

Power curves provided by wind turbine manufacturers are obtained under certain conditions that are different from those of real life operation and, therefore, they actually do not describe the behavior of these machines in wind farms. In those cases where one year of data is available, a logistic function may be fitted and used as an accurate model for such curves, with the advantage that it describes the power curve by means of a very simple mathematical expression. Building such a curve from data can be achieved by different methods, such as using mean values or, alternatively, all the possible values for given intervals. However, when using the mean values, some information is missing and when using all the values the model obtained can be wrong. In this paper, some methods are proposed and applied to real data for comparison purposes. Among them, the one that combines data clustering and simulation is recommended in order to avoid some errors made by the other methods. Besides, a data filtering recommendation and two different assessment procedures for the error provided by the model are proposed.
Keywords: wind power; power curve; logistic function; spline; Monte Carlo simulation; interior point algorithm; MAPE wind power; power curve; logistic function; spline; Monte Carlo simulation; interior point algorithm; MAPE

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MDPI and ACS Style

Villanueva, D.; Sixto, A.; Feijóo, A.; Fernández, A.; Miguez, E. Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data. Appl. Sci. 2020, 10, 3317. https://doi.org/10.3390/app10093317

AMA Style

Villanueva D, Sixto A, Feijóo A, Fernández A, Miguez E. Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data. Applied Sciences. 2020; 10(9):3317. https://doi.org/10.3390/app10093317

Chicago/Turabian Style

Villanueva, Daniel, Adrián Sixto, Andrés Feijóo, Antonio Fernández, and Edelmiro Miguez. 2020. "Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data" Applied Sciences 10, no. 9: 3317. https://doi.org/10.3390/app10093317

APA Style

Villanueva, D., Sixto, A., Feijóo, A., Fernández, A., & Miguez, E. (2020). Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data. Applied Sciences, 10(9), 3317. https://doi.org/10.3390/app10093317

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