Interior-Point Methods for Optimal Power Flow with Scheduled Topological Changes under Uncertain Demand
Year: 2026
Type: article
Abstract: Effective operation of modern power systems relies on optimization models that can account for both demand uncertainty and scheduled network reconfigurations. This paper presents a two-stage stochastic formulation of the pre-dispatch problem with scheduled line and bus switching, formulated within the linearized DC power flow framework. In the first stage, generation setpoints are scheduled before demand is realized; in the second stage, these decisions are adapted to multiple demand scenarios and the resulting topologies after switching. Network maneuvers are represented through a unified binary configuration matrix, which compactly represents simultaneous line and bus events while preserving the sparsity of the model. The resulting block-structured problem is solved efficiently with a specialized primal-dual interior-point method. The proposed approach integrates stochastic modeling, explicit representation of switching actions, and advanced solution techniques into a unified and scalable framework. By contrasting the method with chance-constrained DC-OPF, the paper highlights the advantages of scenario-based redispatch in capturing both uncertainty and topological flexibility. This work advances the state of the art in stochastic optimization for power system operation, providing a rigorous yet practical foundation for secure and economical decision making in increasingly uncertain and dynamic environments.
Source: Annals of Operations Research
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
OpenAlex ID: W7222182749