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European wholesale electricity prices have dropped by early two thirds since their all-time high around 2008. Different factors have been blamed, or praised, for having caused the price slump: the expansion of renewable energy; the near-collapse of the European emissions trading scheme; over-optimistic power plant investments; a decline in final electricity consumption; and cheap coal and natural gas. This ex-post study of European electricity markets from 2008 to 2015 uses a fundamental power market model to quantify their individual contributions on day-ahead prices. The two countries we study in detail, Germany and Sweden,differ significantly: fuel and CO2 prices were important price drivers in Germany, but in Sweden it was electricity demand. This difference is explained by the nature of the hydro-dominate Nordic electricity system. In both countries, however, the single largest factor depressing prices was the expansion of renewable energy. At the same time, Germany’s nuclear phase-out had an upward effect on prices. If one defines the Energiewende as the combination of these two policies, its net effect on power prices was negligible.
Applied power system research is data intensive, often requiring hour-by-hour data on electricity consumption and generation as well as detailed information about technical and cost parameters of power stations. The European Union obliges firms to publish much of this information on a common website, the “ENTSO-E Transparency Platform” operated by the association of transmission system operators. It is possibly the most ambitious platform for power system data globally. However, anecdotal evidence from users indicates significant shortcomings regarding data quality and usability. This paper provides an introduction to and an assessment of the Transparency Platform, helping researchers to use it more efficiently and to judge data quality more rigorously.
The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research.