Dynamic Rating of Transmission Lines for Improved Wind Energy Integration in Complex Terrain

Transmission congestion is a growing concern that could limit integration on new renewable energy projects to the electricity grid. Because construction of new transmission lines is a long and expensive process, transmission service providers are investigating dynamic line rating (DLR) mehtods that could potentially increase capacity of existing transmission lines. DLR is a smart-grid technology that enables rating of power lines based on real-time conductor temperature that is dependent on local weather conditions. whereas conventional practice relies on a static rating, which is based on conservative local weather assumptions to limit transmission line sag. With todays improved wind and weather models, communication systems, and computing hardware, a computational approach to DLR is a possibility. Current thesis research investigates year-long wind patterns over a large test bed area in southern Idaho, in collaboration with Idaho National Laboratory and Idaho Power Company. To instil further confidence in the DLR approach, as proposed in IEEE Standard 738, the ordinary differential equation model that governs conductor temperature change in time, has been first validated by coupled computational fluid dynamics (CFD) and heat transfer analysis. Both steady-state and transient thermal rating assumptions have been evaluated using field measurements and high order numerical methods. Under low-wind conditions it is found that the steady-state thermal-rating assumption can cause unnecessary curtailments of power. To better model the variation of temperature along the path of a transmission line, a large-eddy simulation (LES) of winds over the moderately complex terrain of the test bed area has been performed using clusters of graphics processing units (GPU). LES results indicate that wind speed as well as direction relative to the transmission line is a critical factor in determining the conductor temperature, which implies that numerical wind models need to provide accurate estimates of wind speed and direction in regions of complex terrain