Decentralized power grid control scheme utilizing photonic sensing and computing

Benedict X. Vergara; Cooter P. McGrew; Payman Dehghanian; Volker J. Sorger

doi:10.1117/12.2650992

15 March 2023 Decentralized power grid control scheme utilizing photonic sensing and computing

Benedict X. Vergara, Cooter P. McGrew, Payman Dehghanian, Volker J. Sorger

Proceedings Volume 12438, AI and Optical Data Sciences IV; 124380F (2023) https://doi.org/10.1117/12.2650992
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

A shift in the way we generate and distribute electricity from few, large-scale units; to many, small-scale, decentralized units has created power distribution complications that cannot be managed by one centralized authority in reasonable time. We hypothesize that through the utilization of photonic-based computing, physics-based hierarchical machine learning frameworks will allow for optimized grid operation at lower computational cost. Behavioral analysis of trained agents demonstrates that local, modular control of microgrids could provide a reliable alternative to the existing method of power grid control. It is our vision that these agents could discover new methods for optimal grid control.

Conference Presentation

Citation Download Citation

Benedict X. Vergara, Cooter P. McGrew, Payman Dehghanian, and Volker J. Sorger "Decentralized power grid control scheme utilizing photonic sensing and computing", Proc. SPIE 12438, AI and Optical Data Sciences IV, 124380F (15 March 2023); https://doi.org/10.1117/12.2650992

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