Overview of the results
In a nutshell
- Energy scenarios describe, usually based on mathematical models, possible development paths for the energy supply. Should, for instance, the number of private vehicles using fossil fuels remain constant in the coming decades, the energy policy targets for the transport sector, i.e. reducing carbon emissions by 40 to 42 percent by 2030, cannot be achieved. They could for example be realised under the double condition of a largely electrified individual transport sector and a power generation system with significantly lower carbon emissions.
- To achieve this goal, we must set the right course today: It is up to the political echelons to create the necessary framework conditions, allowing for the installation of infrastructure such as charging stations for electric vehicles or hydrogen filling stations, the development of innovative drive technologies and the interconnection of modes of transport.
- Scenario studies should underpin and support such energy policy decisions. In order to assess their significance, however, the data used must be accessible, along with the assumptions and uncertainties. In addition, the most important results should be comprehensibly communicated.
- The Academies’ Project “Energy Systems of the Future” therefore recommends binding standards for the commissioning and development of energy scenarios that should be incorporated as an integral part into the according public tenders. Such standards should be jointly agreed by the commissioning institutions and the academic world – represented, for instance, by academic umbrella organisations.
On the basis of mathematical models, energy scenarios describe possible development paths for the energy supply. To this end, they resort to data sets, models and assumptions regarding long-term trends. The scenarios aim at providing guidance for political, social and economic decisions.
Typically, a commissioning organisation – for example a ministry, an association or a company – phrases an energy policy question, which a scientific institute or consulting company is to answer by means of a scenario study. Since the commissioning organisation sets up the (public) tender and the contract, it defines the framework conditions for the study. The implementing institution, on the other hand, is responsible for the choice of methods and the realisation of the study. Thus, both the commissioning and the implementing organisation are responsible for the quality of a scenario study.
The scenarios are indirectly addressed to the public, represented for instance by non-governmental organisations and the media. The public acts as an important control body and should ideally be involved early on in the elaboration of the questions for scenario studies. The requirements the ESYS Working Group has set up for energy scenarios are based on this rationale of a participatory democracy.
Usually, not only one but several scenarios are modelled and evaluated in a study to allow for the consideration of as many determining factors as possible. Scenario studies should be scientifically valid, transparent and unbiased.
- To be scientifically valid, an energy scenario study must use scientifically recognised, state-of-the-art methods, models and data.
- Transparency requires the publication of the entire study. Both the method and results must be documented in a way to be comprehensible to the study’s target group. In order to verify the results, independent experts must be able to recalculate them. Access to the necessary data should bel granted at least to a reviewer panel.
- Unbiasedness implies that measures by which the commissioning institutions or other stakeholders influence the study are openly communicated along with their effects on the results and conclusions.
Precondition for validity is that a scientific quality control is possible. In the field of policy advice by means of energy scenarios, however, such controls have hitherto been rudimentary.
- To ensure the scientific validity of a study, important parts could be reviewed and published in scientific journals (peer-review).
- Alternatively, a scientific advisory board could be appointed to monitor the preparation of scenario studies and review them.
- The existing methods for the systematic analysis of uncertainties should be evolved and incorporated into the preparation process of energy scenarios. For instance, scenarios based on the same assumptions can be computed with different models (model intercomparison studies). Meta- and sensitivity analyses, evaluating and comparing the results of several scenario studies, should likewise be more frequently used.
Transparency is a key requirement. However, many implementing institutions do not disclose the source texts of their models, as they are part of their operating capital.
- Freely available open source models would create the greatest possible transparency. However, many institutes restrict the right to use their energy data. This should be amended by an EU-wide regulation ensuring that published energy data can generally be used for scenario modelling.
- Alternatively, the data and algorithms should be submitted to an external reviewer panel to check the plausibility of the results.
- Were public institutions to provide a consistent set of reference data and assumptions, it would be easier to compare different energy scenarios. This data could be collected and administered by departmental research institutes such as the German Federal Environment Agency (Umweltbundesamt). Alternatively, a platform could be established to allow for the systematic comparison of models for energy scenarios.
- For government-subsidised studies, consistent standards should be formally established as part of the tenders. An institute which is to be commissioned with a scenario study would hence have to agree to submit the data and results for a period of two years for use in meta-studies.
- The conclusions drawn from the model calculations for according energy policy measures should be comprehensibly explained and substantiated. Thus, scenarios can be a legitimate contribution to democratic decision-making processes.
The implementing and commissioning institutions should claim and actively promote unbiasedness. To this end, all specifications that could limit the unbiasedness of an analysis should be disclosed and plausibly justified.
This applies to the role of the involved parties (in particular the commissioning institution) as well as to the assumptions of the scenario and the choice of the calculation model.