Mixed Copula-Based Uncertainty Modeling of Hourly Wind Farm Production for Power System Operational Planning Studies

Abstract

An effective model to represent real-world wind power production scenarios is essential for an accurate assessment of the impact of wind power generation on power systems. Such a model should capture the spatial and temporal correlations between different wind turbines that are part of a wind farm. Accurate modeling of these correlations will ensure that the wind power uncertainty can be properly quantified. This is especially critical when analyzing systems with high penetration of wind power productions. This paper addresses this critical need by developing the Hourly Mixed Copula Model, a new probabilistic model, based on Gaussian and Archimedean copulas, to model the uncertainty and variability of wind power generation. This model enables the simulation of realistic scenarios of a wind farm power production. Metrics such as the Euclidean distance and Kullback-Leibler divergence are used to demonstrate the effectiveness of the developed model in incorporating the spatio-temporal dependence among the turbine power productions. The impact of accurate characterization of uncertainty in wind power modeling on power system steady-state operational planning is also demonstrated by case studies. These studies indicate that, in order to correctly evaluate the effect of wind power variation on steady-state operational planning, the dependence among wind power resources should not be neglected for power flow studies.