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Power Systems Transformation Summer School
NPT-03/04: Localization Tracking and Classification of On-Ice and Underwater Noise Sources Using Machine Learning
BPT-03/04: Localization Tracking and Classification of On-Ice Underwater Noise Sources Using Machine Learning
Developing Anisotropic Media for Transformation Optics by Using Dielectric Photonic Crystals
Career: Online Learning-based Underwater Acoustic Communications and Networking
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.