Storage Sizing in Power Networks to Reduce Renewable Generation Curtailment

This chapter tackles the issue of sizing energy storage in bulk power systems. To accurately represent the operational status of the power system, a specialized power flow model incorporating voltage and reactive power is utilized. The uncertainty of renewable energy production is expressed through inexact probability distributions, encapsulated in a data-driven ambiguity set based on Wasserstein distance. Using this data, the rate of renewable energy curtailment is formulated as a distributionally robust chance constraint. The aim is to minimize the overall investment cost, leading to a distributionally robust chance-constrained program for the optimal sizing problem. This is then reformulated into a manageable linear programming problem through conservative approximation. This chapter introduces the work in Guo et al. (2020).