Polyhedral Uncertainty Set Based Power System Flexibility Quantitative Assessment

With the continuous increase in the proportion of renewable energy sources such as wind and solar PV integrated into the power system, the rise in source-load uncertainty has exacerbated the demand for operational flexibility within the grid. To accurately quantify this flexibility demand and devise an optimization scheme that balances both flexibility and economy, a quantification and assessment methodology for power system flexibility is proposed, based on polyhedral uncertainty sets. Firstly, the volatility, uncertainty, and correlation characteristics of multiple photovoltaic power stations' outputs are quantified using polyhedral uncertainty sets. Subsequently, the net load fluctuation interval is analyzed, and a quantification model for power system flexibility demand is constructed. Secondly, an affine adjustable robust optimization model that incorporates flexibility demands is established based on affine strategies. This robust optimization model is then transformed into a mixed-integer linear programming (MILP) model for solution. Finally, the optimization results of the proposed model are compared under different uncertainty scenarios using a 6-node system and the IEEE 57-bus system, verifying the effectiveness of the proposed methodology in quantifying and assessing system flexibility demands.