Optimal Power Flow Pursuit
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Abstract (arXiv)
This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall, the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jan 2016.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2024Towards a Systems Theory of Algorithmscited by 7
- 2026Residual Power Flow for Neural Solverscited by 1
- 2025A Data-Driven Real-Time Optimal Power Flow Algorithm Using Local Feedbackcited by 0
- 2026Residual Power Flow for Neural Solvers14 Jan 2026
- 2025A Data-Driven Real-Time Optimal Power Flow Algorithm Using Local Feedback21 Feb 2025
- 2024Towards a Systems Theory of Algorithms25 Jan 2024