Security Constrained Optimal Power Flow via proximal message passing

TLDR: The proximal message passing framework is extended to handle reliability constraints across scenarios, and the resulting algorithm is extremely scalable with respect to both network size and the number of scenarios.

Abstract: In this paper, we propose a distributed algorithm to solve the Security Constrained Optimal Power Flow (SC-OPF) Problem. We consider a network of devices, each with its own dynamic constraints and objective, subject to reliability constraints across multiple scenarios. Each scenario corresponds to the failure or degradation of a set of devices and has an associated probability of occurrence. The network objective is to minimize the cost of operation of all devices, over a given time horizon, across all scenarios subject to the constraints of transmission limit, upper and lower generating limits, generation-load balance etc. This is a large optimization problem, with variables for consumption and generation for each device, in each scenario. In this paper, we extend the proximal message passing framework to handle reliability constraints across scenarios. The resulting algorithm is extremely scalable with respect to both network size and the number of scenarios.