To achieve European climate targets, the decarbonisation of the energy system is essential. This transition is primarily driven by a shift toward electricity generation based on renewable energy sources (RES), which introduces new challenges for electricity balancing. As imbalances are increasingly affected by the variability of RES, while traditional providers of balancing services are gradually being phased out, ensuring the continued efficiency of balancing service procurement becomes a key concern. The Electricity Balancing Guideline addresses this challenge by promoting the international integration of balancing service markets, which have traditionally been organised at the national level. A central challenge in integrating balancing capacity markets for Frequency Restoration Reserves (FRR) lies in the allocation of cross-zonal capacity (CZC) for the exchange of balancing capacity. Given the sequential structure of European electricity market design, where balancing capacity markets typically clear before short-term scheduled energy markets, cross-zonal exchange of balancing capacity creates direct competition between these markets for limited CZC. Efficient allocation is therefore essential to ensure optimal use of CZC across these markets. Two processes for CZC allocation currently under discussion are co-optimised allocation and market-based allocation. While co-optimised allocation enables economically optimal outcomes in theory by clearing markets simultaneously, it requires significant implementation efforts. Market-based allocation, by contrast, is easier to implement within existing structures but relies on forecasts, potentially introducing inefficiencies. Evaluating the impact on market efficiency of both allocation processes is essential to support ongoing discussions. Accordingly, the aim of this thesis is to develop a methodology for assessing CZC allocation processes for balancing capacity exchange. The developed methodology is based on a market simulation model that enables the calculation of electricity generation costs and the extent of balancing capacity exchange under different CZC allocation processes. A reference case without FRR exchange is also considered. For the market-based allocation, the methodology incorporates a synthetic forecasting approach based on historical forecast data. In addition, it includes a representation of the balancing energy market to estimate the costs of balancing energy activation. A key contribution of the methodology is its ability to account for different levels of coordination between the balancing capacity and scheduled energy markets. Specifically, full coordination versus no coordination for both the market-based allocation and the reference case are considered. This distinction is important, as a main difference between co-optimised and market-based allocation lies in the market-clearing sequence, which may influence not only CZC allocation but also dispatch decisions. However, in a portfolio-based market environment, some level of coordination is inherently possible within participants’ portfolios and the effect on dispatch decisions might not be that significant. By enabling the analysis of different intra-portfolio coordination assumptions, the methodology allows for assessing their influence on evaluation outcomes. Evaluating the differences in operational economic efficiency of the allocation processes provides valuable input for weighing the trade-off between implementation complexity and the efficiency of these processes. In this thesis, the methodology is applied to a planning scenario of the European power market. The results show that the exchange of FRR has a limited impact on total electricity generation costs, regardless of the allocation process used. Differences arising from coordination assumptions are more pronounced than those between allocation methods, highlighting the importance of the assumed level of coordination in such evaluations. Although average volumes of exchanged FRR remain low, they are concentrated in specific situations, presenting opportunities for improved cost efficiency. Both allocation approaches capture these benefits, with only minor forecast-related inefficiencies observed under market-based allocation. Overall, the exemplary application confirms the practical applicability and added value of the developed methodology.
Claire Maria Adriana Lambriex (Wed,) studied this question.