Stochastic Wind Farm Expansion Planning With Decision-Dependent Uncertainty Under Spatial Smoothing Effect

Abstract

The global experience on wind farm development reveals that the wind power uncertainty is affected by large-scale wind farm sizes due to the spatial smoothing effect. The dependence on wind farm sizes features the wind power uncertainty as decision-dependent uncertainty (DDU) during the wind farm expansion process. This paper proposes a stochastic expansion planning model for large-scale wind farms considering the DDU and addresses the coupling relationship between expansion decisions and DDU. Specifically, to explore how the structural features of the expansion model change with DDU in different forms, the proposed expansion model with DDU is established based on Point Estimate Method (PEM). Via the explicit expression between decisions and decision-dependent statistical moments of uncertain parameters in the PEM-based model, an in-depth discussion of model features is implemented. An iterative solution method with convergence analysis is proposed based on the explored model features to tackle the DDU. Besides, a modified Benders decomposition method is adopted in each iteration for the PEM-based two-stage optimization model potentially containing both min-min and min-max terms. The effects of DDU on wind farm expansion schemes are analyzed. Case studies verify the proposed expansion model and the solution method.