Integrating large quantities of supply-driven renewable electricity generation remains a political and operational challenge. One of the main obstacles in Europe to installing at least 200 GWs of power from variable renewable sources is how to deal with the insufficient network capacity and the congestion that will result from new flow patterns. We model the current methodology for controlling congestion at international borders and compare its results, under varying penetrations of wind power, with a model that simulates an integrated European network that utilises nodal/localised marginal pricing. The nodal pricing simulations illustrate that congestion -and price -patterns vary considerably between wind scenarios and within countries, and that a nodal price regime could make fuller use of existing EU network capacity, introducing substantial operational cost savings and reducing marginal power prices in the majority of European countries.

The quality of electricity system modelling heavily depends on the input data used. Although a lot of data is publicly available, it is often dispersed, tedious to process and partly contains errors. We argue that a central provision of input data for modelling has the character of a public good: it reduces overall societal costs for quantitative energy research as redundant work is avoided, and it improves transparency and reproducibility in electricity system modelling. This paper describes the Open Power System Data platform that aims at realising the efficiency and quality gains of centralised data provision by collecting, checking, processing, aggregating, documenting and publishing data required by most modellers. We conclude that the platform can provide substantial benefits to energy system analysis by raising efficiency of data pre-processing, providing a method for making data pre-processing for energy system modelling traceable, flexible and reproducible and improving the quality of original data published by data providers.

In this paper the German congestion management regime is analyzed and future congestion management costs are assessed given a higher share of intermittent renewable generation. In this context, cost-based re-dispatching of power plants and technical flexibility through topology optimization are considered as market-based and technical congestion management methods. To replicate the current market regime in Germany a two-step procedure is chosen consisting of a transactional spot market model and a congestion management model. This uniform pricing model is compared to a nodal pricing regime. The results show that currently congestion can mainly be managed by re-dispatching power plants and optimizing the network topology. However, congestion management costs tend to increase significantly in future years if the developments of transmission as well as generation infrastructure diverge. It is concluded that there is a need for improving the current congestion management regime to achieve an efficient longterm development of the German electricity system.

Integrating large quantities of supply-driven renewable electricity generation remains a political and operational challenge. One of the main obstacles in Europe to installing at least 200 GWs of power from variable renewable sources is how to deal with the insufficient network capacity and the congestion that will result from new flow patterns. We model the current methodology for controlling congestion at international borders and compare its results, under varying penetrations of wind power, with a model that simulates an integrated European network that utilises nodal/localised marginal pricing. The nodal pricing simulations illustrate that congestion -and price -patterns vary considerably between wind scenarios and within countries, and that a nodal price regime could make fuller use of existing EU network capacity, introducing substantial operational cost savings and reducing marginal power prices in the majority of European countries.