Energy Technology Perspectives 2016 (ETP 2016) applies a combination of backcasting and forecasting over three scenarios from now to 2050. Backcasting lays out plausible pathways to a desired end state. It makes it easier to identify milestones that need to be reached, or trends that need to change promptly, in order for the end goal to be achieved. The advantage of forecasting, where the end state is a result of the analysis, is that it allows greater considerations of short-term constraints.
The analysis and modelling aim to identify the most economical way for society to reach the desired outcome, but for a variety of reasons the scenario results do not necessarily reflect the least-cost ideal. Many subtleties cannot be captured in a cost-optimisation framework: political preferences, feasible ramp-up rates, capital constraints and public acceptance. For the end-use sectors (buildings, transport and industry), doing a pure least-cost analysis is difficult and not always suitable. Long-term projections inevitably contain significant uncertainties, and many of the assumptions underlying the analysis will likely turn out to be inaccurate. Another important caveat to the analysis is that it does not account for secondary effects resulting from climate change, such as adaptation costs. By combining differing modelling approaches that reflect the realities of the given sectors, together with extensive expert consultation, ETP obtains robust results and in-depth insights.
Sustainable energy outcomes do not demand new technological breakthroughs
Achieving the ETP 2016 2°C Scenario (2DS) does not depend on the appearance of breakthrough technologies. All technology options introduced in ETP 2016 are already commercially available or at a stage of development that makes commercial-scale deployment possible within the scenario period. Costs for many of these technologies are expected to fall over time, making a low-carbon future economically feasible.
The ETP analysis acknowledges those policies that are already implemented or committed. In the short term, this means that deployment pathways may differ from what would be most cost-effective. In the longer term, the analysis emphasises a normative approach, and fewer constraints governed by current political objectives apply in the modelling. The objective of this methodology is to provide a model for a cost-effective transition to a sustainable energy system.
Linking multiple technologies provides robust sustainable energy scenarios
To make the results more robust, the analysis pursues a portfolio of technologies within a framework of cost minimisation. This offers a hedge against the real risks associated with the pathways: if one technology or fuel fails to fulfil its expected potential, it can more easily be compensated by another if its share in the overall energy mix is low. The tendency of the energy system to comprise a portfolio of technologies becomes more pronounced as carbon emissions are reduced, since the technology options for emissions reductions and their potentials typically depend on the local conditions in a country. At the same time, uncertainties may become larger, depending on the technologies’ maturity levels and the risks of not reaching expected technological development targets.
ETP model combines analysis of energy supply and demand
The ETP model, which is the primary analytical tool used in ETP 2016, supports integration and manipulation of data from four soft-linked models:
- energy conversion
- buildings (residential and commercial/services).
It is possible to explore outcomes that reflect variables in energy supply (using the energy conversion model) and in the three sectors that have the largest demand, and hence the largest emissions (using models for industry, transport and buildings). The following schematic illustrates the interplay of these elements in the processes by which primary energy is converted to the final energy that is useful to these demand-side sectors (Figure A.1).
Figure A.1 Structure of the ETP Model
Notes: TIMES = The Integrated MARKAL-EFOM System; MoMo = Mobility Model.
Key point The ETP model enables a technology-rich, bottom-up analysis of the global energy system.