Dynamic Prediction of Energy Delivery Capacity of Power Networks : Unlocking the Value of Real-Time Measurements.

This paper describes recent advances in prediction software using advanced data-mining tools, and shows how this can significantly increase the operational value of the data gathered. These new tools allow for new operational procedures to be defined that increase the usages of the network without decreasing security of supply. We will use the example of dynamic line rating, i.e. determining the thermal rating of an overhead line based on real-time environmental parameters (temperature, wind speed & direction and solar radiation) to highlight how the use of numerical data-mining tools can help us reliably predict future behavior of power networks.