Price contributions of raw materials to clean energy technologies

Kurzfassung

The energy and transport transition requires a large-scale installation of renewable energy sources (RES), e.g. wind and PV, as well as storage technologies and the electrification of vehicles. These technologies use bulk materials as well as smaller material fractions, some of which are classified as potentially critical. In general terms, “criticality” implies that there is a significant likelihood of short- to mid-term supply bottlenecks and/or a high economic importance of those materials. Supply bottlenecks, in turn, are expected to affect raw material prices and – as a consequence – prices for those technologies in which these raw materials are used. Energy system transformation strategies are often developed using cost-optimizing energy system models. Therefore, cost assumptions for RES technologies play a central role in the development of such scenarios. However, it is usually implicitly assumed that the necessary raw materials for the transformation are available in unlimited quantities, i.e. that there are no bottlenecks in the raw material supply that could result in higher technology costs. In this study, we therefore first examine the share of the costs of a wide range of raw materials in the total costs of central energy and transport technologies. We do this by building, on the one hand, on an extensive database on the specific demand for raw materials in energy and transport technologies. On the other hand, we use the assumptions on investment costs of the technologies in question as they are used in energy system modeling and optimization. In this way, it is possible to show for which technologies price increases on the raw material side can contribute to an increase in technology costs and to what extent. This makes it possible to identify which raw material price developments should be given special attention in the future in order to take potential raw material bottlenecks into account already in the development of (cost-optimal) transformation strategies for the energy system.