A Network- and Performance-based Zonal Configuration Algorithm for Electricity Systems

An efficient and non-discriminatory capacity allocation and congestion management is a core task of transmission system operators in any restructured electricity sector. For historic reasons, the allocation of transmission capacity in the European electricity sector of today usually takes place at political borders between countries. While being a pragmatic approach, such an allocation does not reflect very well the structure of the highly meshed European electricity network and its bottlenecks. Driven by the rising cross-border electricity trading and the large-scale integration of volatile renewable energy sources such as wind power, this incoherence between institutions and technology is increasingly limiting the performance and sustainability of the European electricity system as well as endangering the achievement of an integrated European electricity market by 2015, as foreseen by the European target model. A similar challenge has been faced by the European air transport sector in its quest to develop a Single European Sky out of national airspaces. In order to improve its capacity allocation performance, the European air transport sector developed – among other measures – the concept of Functional Airspace Blocks that manage air traffic flows according to functional instead of political borders. Together with Eurocontrol’s Central Flow Management Unit, this approach is expected to significantly reduce delays and emissions by making better use of airspace capacity. In analogy to the air transport sector, the idea of Functional Airspace Blocks is applied to capacity allocation in the European electricity sector by developing a network- and performance- based algorithm to configure functional congestion management zones. The algorithm is based on the identification of critical network elements and a network sensitivity analysis, in order to cluster nodes with the most similar impact on critical network elements into a preferred number of zones, thereby optimizing the utilization of the transmission capacity and minimizing the expected redispatch cost. Hence the algorithm proposed by this thesis fulfils two of the key requirements posed by the ACER framework guideline on congestion management and capacity allocation (CACM) published in 2011. The algorithm is tested on several real snapshots of the European electricity system (peak and off-peak; before and after the 2011 shut-down of eight German nuclear power plants; and on a 2020 network model, including all planned generation and network extensions). The results of the zonal configuration are visualized graphically, reflecting the real structure of the European electricity network. The results of the thesis show that a majority of critical network elements are located not at political borders, but rather inside national transmission systems. In consequence, a functional configuration of congestion management zones usually does not follow political boundaries and it may change substantially within hours, depending on the generation and flow patterns. Regarding the number of congestion management zones, the thesis shows that 5 to 10 functional zones could achieve about the same congestion management performance (in terms of transmission capacity utilization and expected redispatch costs) as today’s 27 political zones. 20 functional zones may improve the congestion management performance by 8 to 12% and 40 functional zones by 11 to 23% compared with today’s political configuration, saving between 400 and 800 million Euro in expected redispatch cost per year. To further improve the congestion management performance and better reflect the increasingly dynamic generation and flow pattern due to variable renewable energy sources, the thesis recommends considering the implementation of a nodal electricity market design at the European scale. Apart from the optimization of congestion management, the sensitivity-based clustering algorithm developed in this thesis could also be a valuable tool for visualizing the network structure and critical network elements as a transparent basis for network investment decisions. Finally, the thesis also analyses the use of transmission rights in the European electricity market. It concludes that the current European approach based on yearly and monthly physical transmission rights may be insufficient to cope with the expected, massive amount of short-term volatility caused by wind and solar power, since they fragment the European electricity market, withdraw much-needed capacity from the day-ahead and intraday-day time-frame relevant for renewable energies, and prevent an optimized capacity allocation at the European level. Beyond the implementation of the day-ahead market coupling, the thesis recommends moving even further by allocating and optimizing all of the physical transmission capacity in efficient intraday and real-time (balancing) markets at the European scale. For managing the forward price risk, it is recommended to issue financial transmission rights (i.e., congestion revenue rights) in monthly and yearly timeframes. Some of the key requirements for the introduction of financial transmission rights are investigated in this study. This development may question the organizational separation of power exchanges and network operators (TSOs) in the long run, and it will require an entity responsible for capacity management at the European level.