Build Smart Grids on Artificial Intelligence − A Real-world Example
Edited book (chapter)
Chapter Title | Build Smart Grids on Artificial Intelligence − A Real-world Example |
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Book Chapter Category | Edited book (chapter) |
ERA Publisher ID | 9222 |
Book Title | Applications of Big Data and Artificial Intelligence in Smart Energy Systems Smart Energy System: Design and its State-of-The Art Technologies |
Authors | You, Shutang, Li, Hongyu, Liu, Shengyuan, Sun, Kaiqi, Zhao, Yinfeng, Xiao, Huangqing, Dong, Jiaojiao, Su, Yu, Wang, Weikang, Cui, Yi, Yin, He, Tan, Jin and Liu, Yilu |
Volume | 1 |
Page Range | 193-220 |
Chapter Number | 8 |
Number of Pages | 28 |
Year | 2023 |
Publisher | River Publishers |
ISBN | 9788770228244 |
9788770228251 | |
Web Address (URL) | https://ieeexplore.ieee.org/document/10137408 |
Abstract | Power grid data is getting “bigger” with the deployment of various sensors. The big data in power grids creates huge opportunities for applying artificial intelligence technologies to improve resilience and reliability. This chapter introduces multiple real-world applications based on artificial intelligence to improve power grid situational awareness and resilience. These applications include event identification, inertia estimation, event location and magnitude estimation, data authentication, control, and stability assessment. These applications are operating on a real-world system called FNET/GridEye, which is a wide-area measurement network and arguably the world’s largest cyber−physical system that collects power grid big data. These applications showed much better performance compared with conventional approaches and accomplished new tasks that are impossible to be realized using conventional technologies. These encouraging results demonstrate that combining power grid big data and artificial intelligence can uncover and capture the non-linear correlation between power grid data and its stability indices and will potentially enable many advanced applications that can significantly improve power grid resilience. |
Keywords | Artificial intelligence; power grid; wide-area measurements; big data; FNET/GridEye |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 400803. Electrical energy generation (incl. renewables, excl. photovoltaics) |
460308. Pattern recognition | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Tennessee, United States |
National Renewable Energy Laboratory, United States | |
Oak Ridge National Laboratory, United States |
https://research.usq.edu.au/item/yyz83/build-smart-grids-on-artificial-intelligence-a-real-world-example
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