Probability analysis of weather data for energy assessment of Hybrid Solar/Wind Power System

In this paper a procedure for the probabilistic treatment of irradiance and wind meteorological data is reported in order to evaluate the energy potential of a given site as well as the generation of electricity from photovoltaic systems (PVSs) and wind systems (WECSs). In particular the aim of the proposed analysis of recorded meteorological data is twofold: first of all to check if the real probability distribution functions (PDF) of both clearness index and wind speed are respectively overlapped with Hollands-Huget distribution and Weibull distribution then to find the parameters of these two distributions. The results of this procedure stands for the input of an algorithm for the optimized design of grid-connected Hybrid Solar Wind Power Systems (HSWPS). The core of this algorithm is a probabilistic model based on the convolution technique, that allows to assess the long-term performance of a hybrid solar-wind power system for both stand-alone and grid-linked applications. In this paper, the applicability of this procedure has been tested for a site, Acireale (Italy), finding the fitting parameters of the probabilistic models.