Next Article in Journal
Concrete Infill Monitoring in Concrete-Filled FRP Tubes Using a PZT-Based Ultrasonic Time-of-Flight Method
Previous Article in Journal
Aerodynamic Drag Analysis of 3-DOF Flex-Gimbal GyroWheel System in the Sense of Ground Test
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(12), 2080; doi:10.3390/s16122080

Modeling of a Robust Confidence Band for the Power Curve of a Wind Turbine

1
Departamento de Ciencias de la Computación y Electrónica, Universidad Técnica Particular de Loja, Campus de la Universidad Técnica Particular de Loja, Calle San Cayetano Alto s/n, Loja 1101608, Ecuador
2
Departamento de Matemática a las Tecnologías de la Información y Comunicaciones, Universidad Politécnica de Madrid, Av. Complutense Nº 30, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 26 September 2016 / Revised: 16 November 2016 / Accepted: 23 November 2016 / Published: 7 December 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [4678 KB, uploaded 12 December 2016]   |  

Abstract

Having an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turbine under test conditions is presented. Here, the confidence band is bound by two curves which are estimated using parametric statistical inference techniques. However, the observations that are used for carrying out the statistical analysis are obtained by using the binning method, and in each bin, the outliers are eliminated by using a censorship process based on robust statistical techniques. Then, the observations that are not outliers are divided into observation sets. Finally, both the power curve of the wind turbine and the two curves that define the robust confidence band are estimated using each of the previously mentioned observation sets. View Full-Text
Keywords: SCADA system; power curve; power-curve confidence band SCADA system; power curve; power-curve confidence band
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Hernandez, W.; Méndez, A.; Maldonado-Correa, J.L.; Balleteros, F. Modeling of a Robust Confidence Band for the Power Curve of a Wind Turbine. Sensors 2016, 16, 2080.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top