Chance Constrained Framework for AC Security Constrained Optimal Power Flow

Authors

Chacko K., Alizadeh M., Capitanescu F., Li P.

Reference

2024 International Conference on Smart Energy Systems and Technologies: Driving the Advances for Future Electrification, SEST 2024 - Proceedings, 2024

Description

The increasing amount of renewable energy penetrating to power systems poses significant challenges for ensuring reliable and secure operations. Due to the strong uncertainty of renewable energy generation, it is challenging to hold the operational constraints for optimal power flow, particularly when contingency-related constraints are considered. In this study, we propose an optimization framework for AC security-constrained optimal power flow under uncertainty. A chance-constrained optimization (CCOPT) problem is formulated aiming to satisfy the operational constraints with a user-defined confidence level for all N-l contingencies simultaneously. As a result, the optimal solution guarantees operational security if any of the contingencies may take place. The CCOPT problem is solved by the inner-outer approximation method which transfers the original problem to two nonlinear programming (NLP) problems, making it tractable for addressing complex optimization problems under non-Gaussian distributed uncertainties. As a case study, a 5-bus power system with uncertain wind power penetration is employed to illustrate the efficacy of the proposed approach.

Link

doi:10.1109/SEST61601.2024.10694549