Dynamic rating of overhead transmission lines over complex terrain using a large-eddy simulation paradigm


Large-eddy simulation technique with an immersed boundary approach is applied to simulate wind over a complex terrain region.

The wind solver is accelerated using multiple graphics processing units for parallel processing.

Transient calculation of the conductor temperature with high-order time stepping schemes is advantageous.

Simulation results compare favorably with weather station data.

Dynamic line rating has the potential to address congestion problems that hinders the integration of renewable energy sources.


Dynamic Line Rating (DLR) enables rating of power line conductors using real-time weather conditions. Conductors are typically operated based on a conservative static rating that assumes worst case weather conditions to avoid line sagging to unsafe levels. Static ratings can cause unnecessary congestion on transmission lines. To address this potential issue, a simulation-based dynamic line rating approach is applied to an area with moderately complex terrain. A micro-scale wind solver — accelerated on multiple graphics processing units (GPUs) — is deployed to compute wind speed and direction in the vicinity of powerlines. The wind solver adopts the large-eddy simulation technique and the immersed boundary method with fine spatial resolutions to improve the accuracy of wind field predictions. Statistical analysis of simulated winds compare favorably against wind data collected at multiple weather stations across the testbed area. The simulation data is then used to compute excess transmission capacity that may not be utilized because of a static rating practice. Our results show that the present multi-GPU accelerated simulation-based approach — supported with transient calculation of conductor temperature with high-order schemes — could be used as a non-intrusive smart-grid technology to increase transmission capacity on existing lines.


  • Computational fluid dynamics;
  • Dynamic line rating;
  • Wind power

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