Temperature-dependent transmission line models for electric power systems and their impacts on system studies

Electric power transmission line models for large scale system studies are characterized by uniformly distributed parameters or a lumped parameter configuration. These models have been historically developed for studies under nominal operating conditions. The following assumptions are often made: uniform current density, constant material characteristics, and constant external conditions, including temperature. However, in recent years, the increased use of renewable energy resources and corresponding enabling technologies has had an impact on the electric power system, and several previous operating assumptions are no longer valid.This thesis focused on electric power lines as a critical network component of the power system, and aimed at developing line models to be used in steady-state system analysis applications. By relaxing historical modeling assumptions and by taking into account parameters not previously considered, more accurate results are expected by the decision-making tools. Specifically, two parameters were considered:1. Environmental conditions – ambient temperature gradients along a line,2. Electrical frequencies – the expected increase in non-fundamental frequencies due to augmented use of power electronic devices.Contributions include formulating an optimization problem to incorporate these parameters into static line models. Then, a focus was put on developing a line modeling approach to take into account ambient temperature variations along the line. The proposed line models are temperature-dependent in terms of both structure and line parameters; therefore, they enable capturing of temperature effects, including more accurate determination of power handling capabilities. The line modeling approach was automated and incorporated into multi-bus system analysis tools. The proposed models’ impacts on large-scale, steady-state system studies, such as power flow analysis, were investigated.Ph.D., Electrical Engineering -- Drexel University, 201