Sizing energy storage to reduce renewable power curtailment considering network power flows: a distributionally robust optimisation approach.

The limited reserve of fossil fuels and public awareness of environmental issues prompt the rapid development of renewable energy generation. However, the centralised utilisation of renewable energy in bulk power systems is impeded mainly by its volatile nature and transmission congestion, leading to the spillage of renewable power. The energy storage unit is expected to be a promising measure to smooth the output of renewable plants and reduce the curtailment rate. This study addresses the energy storage sizing problem in bulk power systems. To capture the operating status of the power system more accurately, the authors use a dedicated power flow model which involves voltage and reactive power. The uncertainty of renewable generation is described via inexact probability distributions encapsulated in a data‐driven Wasserstein‐metric based ambiguity set, based on which the renewable energy curtailment rate is formulated as a distributionally robust chance constraint. The objective is to minimise the total investment cost, and the optimal sizing problem gives rise to a distributionally robust chance‐constrained program, and is reformulated as a tractable linear program via conservative approximation. Case studies conducted on the modified IEEE 30‐bus and 118‐bus systems demonstrate the effectiveness and performance of the proposed approach. [ABSTRACT FROM AUTHOR]