This project investigates the co-design of automated mechanisms and economic incentives to procure complex grid services from distribution system operators when the transmission system operator does not have direct control over distributed resources.
Current efforts have focused on slow time-scale services or aggregate response requirements, but recent research results suggest that a fine-grained network of controllable resources can provide more complex services, such as real-time voltage regulation, congestion control, generation rescheduling, reactive power compensation, energy storage, and even N-1 curative actions.
The availability of these services removes a major roadblock on the path to the massive integration of renewable energy sources without resorting to expensive transmission grid reinforcement.
The proposed research will build on novel computational methods that allow the design and solution of large-scale hierarchical games. The resulting automation-incentive co-design methods will be made computationally scalable and translated into protocols with efficiency, fairness, and safety guarantees.
Jonas Matt, Zhisen Jiang, and Dhruv Sirohi represented MAESTRO at the first PowerUp 2026 conference in Boulder, Colorado (September 9-11) with three posters.
The paper "Optimal Functional Incentives for Control: The Linear-Quadratic Case with Bilinear Incentives", authored by Jonas Matt, Saverio Bolognani, and Florian Dörfler, was accepted for publication at CDC 2026.