VOLTNET: Smart Sensor Network for Powerline Monitoring with Machine Learning
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Description
The project aims to develop a demonstrator for a semi-autonomous smart sensor network platform to monitor, detect and classify voltage, power quality and fault events on low voltage (LV) powerlines.
The sensors will be be designed to be deployed in low voltage substations, and downstream feeder cables, and will employ innovative machine learning algorithms to detect and classify a range of known power quality events, and to identify transient and incipient fault conditions which are currently difficult to identify economically.
They will use broadband powerline communications technology to transmit data and messages and to share knowledge between sensors in the network, enabling better performance to be achieved.
The technology to be developed represents an important capability with signification opportunities for exploitation in the rapidly growing Smart Grid market segment.
| POWERLINE TECHNOLOGIES LIMITED | LEAD_ORG |
| POWERLINE TECHNOLOGIES LIMITED | PARTICIPANT_ORG |
| UNIVERSITY COLLEGE LONDON | PARTICIPANT_ORG |
| UNIVERSITY COLLEGE LONDON | PARTICIPANT_ORG |
| Brian Lasslett | PM_PER |
Subjects by relevance
- Machine learning
- Voltage
- Sensor networks
- Data communications networks
- Quality
- Sensors
- Distribution of electricity
- Defects
- Electrical power networks
- Broadband networks
Extracted key phrases
- Smart Sensor Network
- Autonomous smart sensor network platform
- Powerline Monitoring
- Machine Learning
- Smart Grid market segment
- VOLTNET
- Low voltage substation
- Power quality event
- Broadband powerline communication technology
- Signification opportunity
- Fault event
- Incipient fault condition
- Important capability
- Project
- Downstream feeder cable