Dynamic event-triggered hierarchical coordination for TSO-DSO systems: Communication-efficient optimization under practical constraints

This research project explores the development of a communication-efficient optimization framework for Transmission System Operator (TSO) and Distribution System Operator (DSO) coordination. Modern power grids require seamless hierarchical coordination between TSOs and DSOs to manage distributed energy resources while maintaining system stability. However, continuous data exchange imposes significant communication overhead and bandwidth constraints. To address these challenges, this work investigates a dynamic event-triggered coordination mechanism designed to optimize power flow and resource allocation under practical operational constraints. By initiating communication only when specific state-deviation thresholds are breached, the proposed framework significantly reduces the transmission of redundant data without compromising the convergence or accuracy of the optimization process. The methodology involves

modeling the hierarchical TSO-DSO interaction as a bi-level optimization problem, solved via distributed algorithms such as the Alternating Direction Method of Multipliers (ADMM). Simulation models will evaluate the trade-offs between communication frequency, computational latency, and optimization accuracy under varying grid conditions. This research direction provides valuable guidance for implementing scalable, communication-resilient coordination strategies in next-generation smart grids.

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