Construction of energy scenarios
When specifying assumptions, it is important to represent a wide variety of possible conditions and prerequisites as a way of characterising uncertainties. Scenarios can be constructed in different directions on the time line. Explorative scenarios start with the current status and extrapolate the future based on different assumptions. Normative scenarios look at a certain target (i.e. 450 ppm CO2, 50% renewables) and try to identify a spectrum of consistent paths to reach this target. Backcasting scenarios define a desirable state in the future (for example, reduction of fossil fuels by 80% in 2050) and delineate the requirements for each time period from the present state to the desired end condition in the future.
Computational models are an excellent tool for generating multiple scenarios based on different assumptions. In general, these energy models can be divided into the two categories of bottom-up and top-down models. The top-down approach takes a macroeconomic perspective and seeks to model developments within the entire economy. In many cases, due to the broader perspective, top-down models use aggregated indicators rather than explicit technology options like single power plants. Top-down models are currently focusing on the analysis of GDP or employment impacts due to new energy technologies. Hence, the top-down approach is becoming more attractive even though many current models also include micro data (bottom-up calibration). For instance, the lead market concept can be quantitatively integrated in the models using indicators like registered patents or R&D expenses. Feedback effects might further improve the validity of the models.
Bottom-up approaches seek to model the development of energy systems based on the detailed representation of technology or economic developments. Important groups within the field of conventional bottom-up models include optimisation models and simulation models.
The changed political framework in the energy sector – primarily the liberalisation of the electricity and gas markets – has led to new requirements for modelling approaches. As a result of liberalisation, various markets have evolved where electricity and balancing services are traded. Hence, new models have to be capable of realistically representing multiple markets and the interactions between them. In order to be able to produce realistic market results and analyse the impact of heterogeneous players and different (dynamic) strategies, new models also have to integrate the perspective of single players. This offers new possibilities to develop insightful scenarios with regard to the impact of energy system developments on the overall economy. Besides conventional models, agent-based computational economics (ACE) is a very promising approach. Coupling different models or model techniques is also auspicious for future research.
Increasing shares of renewable sources will change the structure and operation of energy systems as they depend on the site- and time-specific availability of the sources. Energy systems with a high penetration of renewable sources need advanced supply and demand management systems. These management systems and renewable source shares will vary as they depend on regional climate conditions. Scenarios need to take the regional meteorology into account to find suitable renewable energy mixes and management systems able to provide reliable energy systems. The modelling has to be done with high spatial and temporal resolution in order to evaluate the balancing effects of distributed systems with multiple technologies.
Important current research topics in the context of scenario construction also include linking quantitative energy models with empirical social research (especially for the topic of the acceptance of new energy technologies), participative elements and experimental analysis, but also linking state-of-the-art methods like the Delphi method and simulation models with quantitative analysis. With regard to content, the influence of renewable energies on the grid, the increasing number of electric vehicles, alternative transport fuels, nuclear phase-out, energy storage and grid extension as well as the influence of CHP generation will all be important research issues in the next few years.