Dynamic prediction of energy delivery capacity of power networks: Unlocking the value of real-time measurements

The paper focuses on advances in short-term prediction (1-4 Hours) of dynamic line rating as an example of what can be achieved by the combination of advanced network sensors and the latest machine learning, data-mining tools. Combining these tools has allowed us to achieve reliable and usable predi...

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Bibliographic Details
Main Authors: Schell, P., Jones, L., Mack, P., Godard, B., Lilien, Jean-Louis
Format: Conference Proceeding
Language:English
Subjects:
Dynamic Line Rating
Forecasting
Machine Learning
Overheadline monitoring
Real time systems
Security
Sensors
Short-term predictions
smart grid
Uncertainty
Weather forecasting
Online Access:Request full text
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Summary:The paper focuses on advances in short-term prediction (1-4 Hours) of dynamic line rating as an example of what can be achieved by the combination of advanced network sensors and the latest machine learning, data-mining tools. Combining these tools has allowed us to achieve reliable and usable predictions that allow the network operators to switch from a static approach to a manageable dynamic one that significantly increases asset utilisation without reducing security of supply.
DOI:10.1109/ISGT.2012.6175690