Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand

As the integration of renewable energy sources, such as wind power and photovoltaics, continues, the issue of system uncertainty has become more pronounced. This paper proposes a stochastic power system dispatch method based on affinely adjustable robust optimization (AARO) with a generalized linear polyhedron (GLP) uncertainty set that can accurately quantify the flexibility of the power system supply and demand as well as enhance the optimality of dispatch strategies. First, a GLP uncertainty set was established to characterize both the temporal stochasticity and spatial correlation of multiple renewable energy outputs. A correlation envelope was employed to reflect renewable energy outputs from historical data, and a polyhedral set was proposed to accurately describe the uncertainty for model formulation, which can effectively reduce model conservatism by minimizing empty regions. Furthermore, the range of net load variations was analysed to build a demand flexibility quantification model for the power system. Next, based on the expected operational value, a robust optimization dispatch model that considers the flexible supply and demand balance is developed within the affine strategy framework. Finally, simulations of a modified 6-bus system and modified IEEE 57-bus system validate the effectiveness of the proposed GLP-AARO method for power system flexibility quantification and dispatch strategy optimization.