Invention Grant
- Patent Title: Methods, systems, and computer readable mediums for determining a system state of a power system using a convolutional neural network
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Application No.: US16381934Application Date: 2019-04-11
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Publication No.: US11544522B2Publication Date: 2023-01-03
- Inventor: Fangxing Li , Yan Du
- Applicant: University of Tennessee Research Foundation
- Applicant Address: US TN Knoxville
- Assignee: University of Tennessee Research Foundation
- Current Assignee: University of Tennessee Research Foundation
- Current Assignee Address: US TN Knoxville
- Agency: Jenkins, Wilson, Taylor & Hunt, P.A.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; H02J13/00 ; G05B13/02

Abstract:
Methods, systems, and computer readable mediums determining a system state of a power system using a convolutional neural network using a convolutional neural network are disclosed. One method includes converting power grid topology data corresponding to a power system into a power system matrix representation input and applying the power system matrix representation input to a plurality of convolutional layers of a deep convolutional neural network (CNN) structure in a sequential manner to generate one or more feature maps. The method further includes applying the one or more feature maps to a fully connected layer (FCL) operation for generating a respective one or more voltage vectors representing a system state of the power system.
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