Setting a climate target at an early stage

What do you make of the Federal Government’s current climate protection programme in the light of your study results?

Some of the measures in the package are heading in the right direction – including those that promote more efficient use of energy in buildings or in industry. Other measures, such as the proposed distance regulation of wind power plants, are not sufficient to achieve the required expansion of wind power plants, according to our analyses. Finally, there are also elements in the climate protection programme that contradict our findings, for instance regarding the future significance of biomass. This resource plays a crucial role in our models (cf. the results regarding energy sources). According to our calculations, the area under cultivation for biomass needs to be doubled. The climate protection programme, by contrast, does not envisage any expansion of the area to be cultivated for bioenergy.

You have also run an optimisation of the German energy system to achieve a reduction in greenhouse gas emissions of just 80 per cent by 2050. What’s the result?

The total additional cost incurred by 2050 would only be about one third of the cost for a 95 per cent reduction. However, the 80 per cent target will not be enough for Germany to comply with the Paris Agreement, which aims at limiting global warming to well below 2 °C. Regardless, Germany should decide at an early stage which target it is working towards, as the transformation of the energy system varies according to the target. For example, new gas-fired power plants and heating technologies are economically advantageous for the 80 per cent reduction in emissions, but they will not enable the 95 per cent target to be achieved. In the latter case, hydrogen technologies will be among the crucial factors.

Can we actually trust the energy cost predictions of the computer models?

We believe so, yes. Computer models can’t predict the future – a technology may emerge that doesn’t even exist today – but we know the current energy system. Our models can display interactions within it. What’s more, our computer models take technological learning curves into account: the higher the number of units produced, for example of an energy technology system, the lower the price per unit. We also analysed how much a result is affected if the input variables change. For instance, we varied the cost of expanding wind power plants or hydrogen pipelines, and surprisingly, this had little effect on the composition of the ideal energy system.

Frank Frick asked the questions.