With the increased focus on climate change policies, more transmission capacity is needed to accommodate new renewable generation. Traditionally, the capacity of a transmission line is determined using reasonable, outer-range environmental conditions, based on air temperature, wind speed and wind direction. Dynamic Thermal Line Rating (DTLR) can be used to increase the capacity of an existing system by updating the line rating based on real-time environmental conditions. Previous research demonstrates the benefits of implementing DTLR but are mainly focused on smaller pilot projects over limited periods of time. My PhD project investigates the implementation of DTLR, considering the impact on the rest of the electrical system and the spatial and temporal differences in potential line rating increase.

This project focuses on three main contributions. The first contribution investigates the impact of using a predicted hourly dynamic thermal rating for transmission lines on the transient conductor temperature. The second contribution investigates the relationship between dynamic thermal ratings for both transmission lines and transformers considering a wind farm expansion, examining the trade-off between wind generation curtailment, loss-of-life of the transformer and the potential revenue for the wind farm operator. The third contribution investigates the spatial and temporal variations in DTLRs using clustering algorithms to group together weather stations with similar DTLR values.