Dynamic Line Rating (DLR) is a smart grid technology that allows the rating of power line conductor to be based on its real-time temperature. Currently, conductors are generally given a conservative static rating based on near worst case weather conditions. Using historical weather data collected over a test bed area in Idaho, we demonstrate there is often additional transmission capacity not being utilized under the current static rating practice. We investigate a DLR method that employs computational fluid dynamics (CFD) to determine wind conditions along transmission lines in dense intervals. Simulated wind conditions are then used to calculate real-time conductor temperature under changing weather conditions. In calculating the conductor temperature and then inferring the ampacity, we use both a steady-state and transient calculation procedure. Under low wind conditions, the steady-state assumption predicts higher conductor temperatures which could lead to unnecessary curtailments, whereas the transient calculations produce temperatures that can be significantly lower, implying the availability of additional transmission capacity. Equally important, we demonstrate that capturing the wind direction variability in the simulations is critical in estimating conductor temperatures accurately.

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