Affiliation:
1. Federal Institute of Education, Science and Technology of Paraíba
2. Federal Rural University of Pernambuco
3. Federal Institute of Education, Science and Technology of Pernambuco
4. Paraíba State University
Abstract
Characterizing the wind speed distribution properly is essential for the satisfactory production of potential energy in wind farms, being the mixture models usually employed in the description of such data. However, some mixture models commonly have the undesirable property of non-identifiability. In this work, we present an alternative distribution which is able to fit the wind speed data decently. The new model, called Normal-Weibull-Weibull, is identifiable and its cumulative distribution function is written as a composition of two baseline functions. We discuss structural properties of the class that generates the proposed model, such as the linear representation of the probability density function, moments and moment generating function. We perform a Monte Carlo simulation study to investigate the behavior of the maximum likelihood estimates of the parameters. Finally, we present applications of the new distribution for modelling wind speed data measured in five different cities of the Northeastern Region of Brazil.
Subject
Geometry and Topology,Statistics and Probability,Algebra and Number Theory,Analysis
Cited by
1 articles.
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