Power System Operation Planning Considering Dynamic Line Rating Uncertainty

Abstract

The restructuring of power systems and wider introduction of renewable energy sources in the recent years is placing a greater stress on the transmission system. Yet, transmission system is paramount for the reliable, secure and economic operation of power systems. However, modern transmission systems often have insufficient capacity, leading to bottlenecks, congestions and spillage of renewable energy, while their expansion is generally expensive, complicated and time consuming. As an alternative to the transmission expansion, dynamic line rating technologies allows to utilize latent capacity of transmission lines through the use of measurements or forecasts of weather parameters. However, as the forecasts of the weather parameters are inherently uncertain, the estimates of transmission capacity also become uncertain, and must be addressed accordingly. This thesis investigates the impacts of dynamic line rating forecast uncertainty in power system operational planning problems. Thus, the thesis aims at developing mathematical models for the management of such uncertainty to ensure secure and effective operation of power systems. In order to achieve the above objective, firstly, stochastic models for the dynamic line rating are developed that allow to consider thermal dynamics of the conductor in the presence of uncertain weather forecasts. The models are entirely data-based and provide a risk-averse method of controlling conductor temperature in operational planning problems. Furthermore, the models allow to control both the probability of occurrence and the magnitude of the thermal overloading. Secondly, an analysis of uncertain factors and their interactions in power system operational planning is performed using the coherent risk measure framework. Additionally, a novel modelling approach for the uncertain renewable energy sources in operational planning problems is proposed. Then, coherent reformulations of uncertain constraints are developed and integrated into day-ahead unit commitment problem. Finally, the benefits of managing risk in operational planning problems using coherent risk measures are demonstrated in comprehensive case studies.