  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 adequately. 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.
