Modeling the uncertainty in farm performance introduced by the ill-predictability of the wind resource

A wind farm planning strategy that simultaneously accounts for the key engineering design factors, and addresses the major sources of uncertainty in a wind farm, can offer a powerful impetus to the development of wind energy. The distribution of wind conditions, including wind speed, wind direction, and air density, vary significantly from year to year. The resulting ill-predictability of the annual distribution of wind conditions introduces significant uncertainties in the estimated resource potential as well as in the predicted performance of the wind farm. In this paper, a new methodology is developed (i) to characterize the uncertainties in the annual distribution of wind conditions, and (ii) to model the propagation of uncertainty into the local Wind Power Density (WPD) and the farm performance: Annual Energy Production (AEP) and Cost of Energy (COE). Both parametric and non-parametric uncertainty models are formulated, which can be leveraged in conjunction with a wide variety of stochastic wind distribution models. The AEP and the COE are evaluated using advanced analytical models, adopted from the Unrestricted Wind Farm Layout Optimization (UWFLO) framework. The year-to-year variations in the wind distribution and the quantified uncertainties are illustrated using two case studies: (i) an onshore wind site at Baker, ND, and (ii) an offshore wind site near Boston, MA. Appreciable uncertainties are observed in the estimated yearly WPDs over the ten year period approximately 11% for the onshore site, and 30% for the offshore site. Likewise, an appreciable uncertainty of 4% is observed in the performance of an optimized wind farm layout at the onshore site.