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Dynamic monitoring and decision systems (dymonds) framework for data-enabled integration in complex electric energy systems

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MESW03 - Closing workshop: Looking forward to 2050

In this talk we introduce a unifying Dynamic Monitoring and Decision Systems (DyMonDS) framework that is based on a multi-layered modeling for aggregation and minimal coordination of interactions between the layers of complex electric energy systems. Using this approach, distributed control and optimization problems are formulated so that: (1) the low-level decision makers optimize cost of local interactions while accounting for their heterogeneous technologies, as well as for their social and risk preferences; and, (2) the higher layer aggregators and coordinators optimize the cost of all interactions at their levels to enable cooperative control. The interactions of each layer are abstracted by using unifying energy state space and the Lagrange coefficients associated with the general physical laws. This sets the bases for both nonlinear control of power electronically-switched automation and for market design formulation. Potential benefits (such as enhanced reliability, resiliency, and efficiency) from integrating flexible technologies, storage, and control, in particular, are illustrated on simple IEEE test systems.

This talk is part of the Isaac Newton Institute Seminar Series series.

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