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Tracking performance of time-varying nonconvex optimization with application to OPF

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If you have a question about this talk, please contact Alberto Padoan .

Optimal power flow (OPF) problems at fundamental for power system operations. They are nonconvex and, in future applications, time-varying. We present a first-order proximal primal-dual algorithm and a second-order algorithm for general time-varying nonconvex optimization and bound their tracking performance. We incorporate real-time feedback in our algorithms for applications to time-varying OPF problems, and illustrate their tracking performance numerically.

(Joint work with Yujie Tang, Caltech, Emiliano Dall’Anese, U of Colorado, Andrey Berstein, NREL )

This talk is part of the CUED Control Group Seminars series.

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Cambridge University Expeditions Society https://timeout.srcf.net/oes22-ors-efn & https://youtu.be/MpfIqW0foJQ Zoom link to join: Zoom: https://maths-cam-ac-uk.zoom.us/j/95451181978?pwd=QTY1WDRxaW92L1BpQm9uSXRyT3JyUT09

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