Journal
ANNUAL REVIEW OF CONTROL ROBOTICS AND AUTONOMOUS SYSTEMS
Volume 5, Issue -, Pages 689-716Publisher
ANNUAL REVIEWS
DOI: 10.1146/annurev-control-042820-011148
Keywords
power grids; stability; network systems; distributed control; machine learning; deep learning
Categories
Funding
- Research Grants Council of the Hong Kong Special Administrative Region [T23-701/14-N, 17202414, 17208817, 17207918, 17256516, 17209219]
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This article surveys classic and novel results on the stability and control of power grids, providing a perspective on the ongoing transition and development of new stability and control paradigms.
Power grids are critical infrastructure in modern society, and there are well-established theories for the stability and control of traditional power grids under a centralized paradigm. Driven by environmental and sustainability concerns, power grids are undergoing an unprecedented transition, with much more flexibility as well as uncertainty brought by the growing penetration of renewable energy and power electronic devices. A new paradigm for stability and control is under development that uses graph-based, data-based, and distributed analysis tools. This article surveys classic and novel results on the stability and control of power grids to provide a perspective on this both old and new subject.
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