Publications

Great Britain’s decision to leave the European Union affects the structure of political and economic systems and the future relationship between EU member states and the kingdom remains unclear to this day. The European power market undergoes a continuing process of market integration on regulatory and technical levels. Brexit could have a negative impact on that development. The question arises as to how Brexit will affect the British power system and its stakeholders.

There is a broad perception that the level playing field of the European Union is increasingly impacted by the interests of individual member states. This observation also holds true for the long-run development of electricity markets. In this paper, the author looks into the questions whether reaching a cost-efficient decarbonization path and accounting for fairness at the same time is possible and finds a clear trade-off.

The main drivers of the transformation processes affecting electricity markets stem from climate policies and changing economic environments. In order to analyse the respective developments, modelling approaches regularly rely on multiple structural and parametric simplifications. The distorting effects can significantly affect the accuracy of long-term projections. In this study, we include information on economic discontinuities and evaluate their influences.

Due to the pending structural changes driven by the high decarbonization targets in the electricity sector, bottom-up energy system models will play a major role in the decision making process. Since models will always depict a simplified vision of reality, it is essential to understand the underlying error mechanisms which influence the results. This paper investigates the influence of time resolution and proposes an estimation method for time resolution related errors.

Many existing energy system models rely on input data available at country-level, or at the level of administrative divisions. However, there is usually no correlation between the distribution of data such as solar radiation, wind speed, and electrical load on one hand, and the administrative divisions on the other hand. The goal of the research is to measure the impact of the shape of model regions on the results of system optimization models. A novel clustering methodology for high-resolution data is presented and applied to define new regions for an energy system model which optimizes expansion planning and unit commitment. The new model regions take into account the bottlenecks in the transmission system and their effect on the expansion of renewable energy sources. We compare the obtained energy mixes, new capacities, and curtailment levels against a model using administrative divisions. The results show discrepancies between the models in the case of a high share of variable renewable energy, and quantify the impact of the distribution of load, wind and solar resources on energy system models. Possible applications of the new model regions are discussed to emphasize their utility for modelers and policy-makers.

The ambitious decarbonization of electricity markets requires adjustments on both, the supply and the demand side of electricity markets. In this paper, the authors find that energy efficiency plays a minor role in reaching the long-run emission reduction targets when accounting for a rebound effect.

With tightening climate and energy targets and further market integration of renewable energies, the translation of these targets into actual policy instruments becomes even more challenging. In this paper, the authors identify major characteristics of numerical models used for decision support and identify general features, where these models lag behind.

Traditionally, dispatch-only electricity market models use an hourly time resolution. If investment decisions become part of the cost function, problems with the computation time may occur. Reducing the time resolution may significantly boost computation time, however, the effects have not been fully investigated. This paper not only targets at understanding and estimating the error caused by reduced time resolution, but it also describes a novel method for the usage of variable time step lengths.