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ERI: Memristor-based Neuromorphic Circuit Design for Closed-Loop Deep Brain Stimulation
IRES Track I: Collaborative Research: Interdisciplinary Research in Korea on Applied Smart Systems (IRiKA) for Undergraduate
NSF Convergence Accelerator Track I: Energy-efficient MetaConductors for Convergence of Sustainable Electronics (E-MC2 of Sustainable Electronics)
I-Corps: Prototyping Power Substation Blackbox
Enterprise: NSWG 801 Electronic Operations Manual for Submersible Maritime Platform (Everything Tablet)
CRII:CNS: IoT-aware Federated On-Device Intelligence
Competitive Distributed Control Methodologies for Small-Scale Power Systems
The objective of this research is to study the fundamental interactions and influences that individual components of a power system have on each other and the overall effect of these interactions on system performance. The approach uses a game-theoretic model of the power system to develop a framework for a new class of distributed control methods. In this new model, system components use energy resources to compete for local and global objectives such as voltage, current, power, or energy.
The intellectual merit is of this work is in its potential to improve control of interconnected power components. Control has typically been one of two extremes: either completely localized control (focused on local objectives) or a centralized control scheme requiring extensive communications, infrastructure, and a single-point of failure. The proposed approach considers how each different local objective interacts across the system. This will result in an operating point that is a global balance of local objectives. This work will determine how the fundamental interactions of the components contribute to, or degrade from, the higher-level objectives of the overall system, such as stability, survivability, and efficiency.
The broader impacts will extend to electrical power networks at all levels where more diverse sources and loads are being utilized, and new technologies are being driven by an ever-increasing demand for performance, stability, efficiency, and flexibility. This new approach to energy control and management will strengthen education objectives by enhancing the content of graduate and undergraduate classes, as well as adding meaningful laboratory experiences.