Computationally Transparent Power Flexibility Aggregation via Directional Support Evaluation

Abstract

The growing penetration of distributed energy resources (DERs) creates new opportunities for improving resource adequacy, operational flexibility, and power-system reliability. However, efficiently characterizing the aggregate flexibility of heterogeneous DER portfolios remains challenging because of high dimensionality, diverse operating dynamics, and spatio-temporal coupling constraints. This paper proposes a computationally transparent framework that formulates aggregate flexibility characterization as a sequence of linear programming (LP)-based directional support evaluations. The framework accommodates heterogeneous DER technologies and configurable device-, feeder-, and portfolio-level constraints. The convex hull of the resulting boundary trajectories provides a feasible inner approximation of the coupled aggregate power flexibility region. Theoretical analysis establishes feasibility and non-overestimation guarantees and characterizes the computational dependence on portfolio size, scheduling horizon, and direction budget. In the small-scale case, the proposed method produces tighter projected regions than box, zonotope, and Chebyshev inner-ball benchmarks and matches a dense directional reference within numerical tolerance using 16--64 construction directions. Large-scale simulations with up to 2000 DERs demonstrate approximately linear empirical runtime scaling with the portfolio size and direction budget over the tested ranges. The results establish a scalable and theoretically grounded approach for aggregate DER flexibility characterization.