Impact of different wind speed multivariate distributions on HV transmission lines connecting wind farms

An accurate wind power generation evaluation requires an adequate probabilistic description of the wind source which takes also into account the correlation among wind speeds at different wind generators installation sites. The problem has been addressed through the employment of several models for wind speed stochastic variable, i.e. Weibull, Lognormal, Gamma, Burr, Rayleigh, extending a previous work. Indeed different model assumptions, although all able to provide a global good fitting of the wind speeds data, may lead to quite different estimates of producibility. This is theoretically crucial both at planning and operating stage when the electrical infrastructures (e.g. transmission lines, transformers, etc.) devoted to transfer green energy have to be designed and managed. Indeed, the paper will demonstrate that while at planning stage a different probabilistic description of the wind resource does not affect in significant manner the transmission line design, at the operating stage instead different assumptions on WS distribution lead to different measures, in probabilistic terms, of the their loadability. This is accomplished by comparing the distribution quantiles of the entire wind farm producibility, estimated through a proper methodology of wind speeds simulation based upon an extensive Monte Carlo procedure.