Transmission Expansion Planning Under Uncertainty

Abstract

The electricity transmission system, lynchpin of the power system chain, has been recognized to play a significant role in fulfilling policy targets such as high integration levels of renewable energy sources, reduction of CO2 emissions, lower electricity costs and increased security of supply. In the European context, cross-border transmission projects are set in center of such discussions and significant investments have been considered for the near future. The European Network of Transmission System Operators for electricity (ENTSO-e) has been established to explore the development of the European transmission system as a whole. The dynamic character of electricity power systems puts great challenges on the long-term transmission planning. Increased levels of uncertainties due to RES integration, variable load profiles (developments in electrical vehicles and demand response) and regulatory changes are only some of the uncertainties. On top of that, the need for a co-ordinated planning process in Europe raises new questions regarding the modeling types used and processes followed. Main focus of this thesis was to examine which modeling approaches are the most appropriate for planning cross-border investments at a pan-European level by taking into account the large uncertainties inherent to transmission planning. An evaluation framework for assessing the different modeling types in transmission expansion was developed and the different options were thoroughly evaluated. In addition, the several uncertainties in transmission planning and ways to address them were examined using an analytical process. These two analyses revealed that there is still room for improvement in the pan-European transmission planning process both in terms of modeling types and uncertainty analysis. Subsequently, several recommendations for transmission planner and policy makers were presented. The topic this thesis examined gets more and more attention among academic and business cycles. The analysis presented can offers a great starting point for the development of new models and practices for transmission planning under uncertainty.