Copula-based joint distribution analysis of wind speed and wind
direction: wind energy development for Hong Kong
Abstract
Accurate assessment of wind energy potential can provide important
implication regarding the optimalization of micro-siting of wind
turbines and increase of wind power generation. It is, however,
noteworthy that most previous studies on wind energy resource assessment
focused solely on wind speed, whereas the dependence of wind energy on
wind direction was much less considered and documented. In the current
study, a copula-based method is proposed to better characterize the
direction-related wind energy potential at six typical sites in Hong
Kong. In the first step, several widely used statistical models are
adopted to fit the marginal distributions of wind speed and direction.
The joint probability density function (JPDF) of wind speed and wind
direction is therewith constructed by various copula models. The
goodness-of-fit evaluation indicates that Frank copula has the best
performance to fit the JPDF at hilltop and offshore sites, while Gumbel
copula outperforms other models at downtown sites. More importantly, the
derived JPDFs are applied to estimate the direction-related wind power
density at each of the considered sites, finding a maximum value of wind
energy potential of 506.4 W/m2 at a hilltop site. In addition,
site-to-site variability is also identified regarding the prevailing
wind resource directions. The outcome of this study is expected to be
useful for the site selection of wind turbines, as well as the strategic
development of wind energy in Hong Kong. Notably, the proposed
copula-based method can also be applied to characterize the
direction-related wind energy potential somewhere other than Hong Kong.