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Nonconvexity induced by the nonlinear AC power flow equations challengessolution algorithms for AC optimal power flow (OPF) problems. While significantresearch efforts have focused on reliably computing high-quality OPF solutions,it is not always clear that there exists a feasible path to reach the desiredoperating point. Transitioning between operating points while avoidingconstraint violations can be challenging since the feasible space of the OPFproblem is nonconvex and potentially disconnected. To address this problem, wepropose an algorithm that computes a provably feasible path from an initialoperating point to a desired operating point. Given an initial feasible point,the algorithm solves a sequence of convex quadratically constrainedoptimization problems over conservative convex inner approximations of the OPFfeasible space. In each iteration, we obtain a new, improved operating pointand a feasible transition from the operating point in the previous iteration.In addition to computing a feasible path to a known desired operating point,this algorithm can also be used to improve the operating point locally.Extensive numerical studies on a variety of test cases demonstrate thealgorithm and the ability to arrive at a high-quality solution in fewiterations.

Feasible Path Identification in Optimal Power Flow with Sequential Convex Restriction