Transient Stability‐Constrained Optimal Power Flow under Uncertainties

In previous chapters, different methods to solve TSC-OPF and TSCUC were introduced. However, these TSC-OPF and TSCUC models are based in a deterministic manner. Namely, the uncertainties such as load and renewable energy are not considered. Meanwhile, the load models are always assumed to be static during the simulation. Therefore, to fully address the mentioned issues, this chapter proposes two TSC-OPF models with uncertainties: (i) considering dynamic load models and uncertain variations in the model parameters; (ii) considering variable and uncertain wind power generation. The uncertainty of the dynamic loads and wind power generation are both modeled by selecting a small representative number of deterministic scenarios that approximate the whole uncertainty space, based on Taguchi 's orthogonal array testing (TOAT). A decomposition-based solution approach is then developed, which iterates between a master problem corresponding to the ordinary optimal power flow (OPF) and a set of subproblems corresponding to transient stability assessment and stabilization constraint generation under uncertainties. The simulation results show good immunization against random realizations of uncertainties while maintaining transient stability.