Abstract
Online identification of power system network branches is critical in modern electric power system operation. Availability of phasor measurement units (PMUs) can be used to identify branch events. Due to complexity of the power system, a distributed cellular computational network (CCN) is proposed. Comparison of centralized and distributed neural network based power system network branch events identification is studied. IEEE 12-bus benchmark power system is simulated on real-time digital simulator platform for this study. CCN based distributed neural network approach is computationally efficient compared to centralized approach.
| Original language | English |
|---|---|
| Title of host publication | 2020 IEEE Power and Energy Society General Meeting, PESGM 2020 |
| Publisher | IEEE Computer Society |
| ISBN (Electronic) | 9781728155081 |
| DOIs | |
| State | Published - Aug 2 2020 |
| Event | 2020 IEEE Power and Energy Society General Meeting, PESGM 2020 - Montreal, Canada Duration: Aug 2 2020 → Aug 6 2020 |
Publication series
| Name | IEEE Power and Energy Society General Meeting |
|---|---|
| Volume | 2020-August |
| ISSN (Print) | 1944-9925 |
| ISSN (Electronic) | 1944-9933 |
Conference
| Conference | 2020 IEEE Power and Energy Society General Meeting, PESGM 2020 |
|---|---|
| Country/Territory | Canada |
| City | Montreal |
| Period | 08/2/20 → 08/6/20 |
Funding
This work is supported in part by the US National Science Foundation (NSF) under grants 1408141, 1312260, 1738902 and 1544910 and the Duke Energy Distinguished Professor Endowment Fund.
Keywords
- Cellular Computational Network
- Neural Networks
- Phasor Measurement Units
- Real-time Digital Simulator
- Transmission Network Branch Events
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