RT info:eu-repo/semantics/article
T1 A New Approach to Estimate the Parameters of the Joint Distribution of the Wind Speed and the Wind Direction, Modelled with the Angular–Linear Model
A1 Martínez Gutiérrez, Samuel
A1 Sarabia Ortiz, Daniel
A1 Sarabia Peinador, Luis Antonio
A1 Ruiz González, Rubén
A1 Merino Gómez, Alejandro
K1 Wind speed
K1 Wind direction;
K1 Joint probability distributions
K1 Parameter estimation
K1 Computation time
K1 Viento-Medición
K1 Winds-Measurement
AB In order to assess the potential and suitability of a location to deploy a wind farm, it is essential to have a model of the joint probability density function of the wind speed and direction, fV,Θ(v,θ). The angular–linear model is widely used to obtain the analytical expression of the joint density from the parametric estimation of the probability density functions of wind speed, fV(v), and wind direction, fΘ(θ). In previous studies, the parameters of the marginal distributions were obtained by fitting the wind measurements to the cumulative distribution function (CDF) using the least squares method and then calculating the probability density function (PDF). In this study, we propose to directly fit the probability density function and then calculate the cumulative distribution function. It is shown that it has both computational and goodness-of-fit advantages. In addition, previous studies have been expanded, analysing the effect of the number of intervals on which wind speed and direction ranges are divided. The new parameter fitting method is evaluated and compared with the original proposal in terms of goodness of fit, using the coefficient of determination R2 as an estimator both in the probability density function (R2pdf) and in the cumulative distribution function (R2cdf). The computational times required to estimate the parameters using both methods will also be compared. The new approach is faster, and the goodness of the fitting is satisfactory for both estimators: it produces a better R2pdf, without significantly affecting the R2cdf, in contrast to the initial one where the R2pdf is smaller.
PB MDPI
SN 2227-7390
YR 2025
FD 2025-04
LK https://hdl.handle.net/10259/10878
UL https://hdl.handle.net/10259/10878
LA eng
NO The paper is part of the projects “Optimal Real-Time Management of the Power-to-H2-toPower cycle (OptiMaPH2P)”, TED2021-131220B-I00, funded by MCIN/AEI (Ministerio de Ciencia eInnovación del Gobierno de España/Agencia Estatal de Investigación) and by the European Union“NextGenerationEU”, “Optimal real-time management under uncertainty for digital twins (OptiDit)”,PID2021-123654OB-C33, funded by MCIN (Ministerio de Ciencia e Innovación del Gobierno deEspaña) and by the European Union “FEDER”. This paper is also part of the Doctoral Thesis of SamuelMartínez-Gutiérrez, funded with a pre-doctoral contract for University Teacher Training (FPU), call2022, awarded by the MUNI of Spain (Ministerio de Universidades del Gobierno de España).
DS Repositorio Institucional de la Universidad de Burgos
RD 29-abr-2026