Hybrid Learning Aided Inactive Constraints Filtering Algorithm to Enhance AC OPF Solution Time

Understand

The Optimal power flow (OPF) problem contains many constraints.

• However, equality constraints along with a limited set of active inequality constraints encompass sufficient information to determine the feasible space of the problem.
• In this paper, a hybrid supervised regression and classification learning based algorithm is proposed to identify active and inactive sets of inequality constraints of AC OPF solely based on nodal power demand information.
• The proposed algorithm is structured using several classifiers and regression learners.