Convexified Flexibility Area Identification at TSO-DSO Interface

Integrating controllable distributed energy resources (DERs) into power systems unlocks flexibility potential at the distribution level. This paper introduces an efficient approach for delineating Convex Flexibility Areas (CFAs) on the P-Q plane at the transmission-distribution interface. This work relies on solving an optimization problem to directly identify a convex region, instead of constructing it by tracing the boundary of the flexibility area via polygon approach. A Quadratic Constrained Quadratic Problem (QCQP) formulation is proposed to minimize the required control (DER) capacity to a specified CFA. Further, a bisection-style iterative algorithm is devised to maximize the CFA by solving sequential minimum control requirement problems. Simulation results, conducted on the IEEE 33-Bus and 69-Bus Systems, demonstrate the method's proficiency in charting CFAs under various control and loading conditions. The proposed iterative CFA maximization technique is shown to converge in ten iterations, significantly outperforming Monte-Carlo Simulation (MCS)-based area enumeration by being fifteen times less time-consuming. Furthermore, the method has been shown to accurately capture the impact of load variations and the control capacity of the system on the obtained CFAs.