Physically Consistent Overload Scenario Generation for Transmission Networks

Studies of corrective congestion management, including solver benchmarking, operator training, security assessment and data-driven control, require a collection of operating points in which one or more branches are overloaded. Such cases are scarce in historical records, and although random perturbation of a base case does produce overloads, these concentrate on a small number of corridors and their severity cannot be prescribed. This paper presents a generator that produces reproducible corpora of physically consistent overloaded states, that is, converged AC solutions satisfying declared limits on the slack, on generator active power and on individual loads, but not a voltage band or generator reactive limits. The method combines a predictor–corrector sweep over a load-stress parameter with Newton–Raphson correction, a library of stress directions derived from distribution factors, and progressive tripping of overloaded branches to reach post-outage topologies. Each scenario is stored as a compact genotype that enables reconstruction of the complete operating point, so the corpus can be distributed as parameter vectors rather than solved cases. Applied to the IEEE 118-bus system extended with a VSC-HVDC link, the generator produced 253,378 overloaded states with maximum branch loadings from 101% to 199.82%, covering 60 distinct overloaded branches across intact-grid, single-outage and double-outage topologies. In the full-state reconstruction test the voltage magnitude discrepancy did not exceed 1.9×10−7 pu.