Exploratory Projects

Two successful examples of pioneering methodological advancements include:

Financial constraints as a barrier to the energy transformation

Affordable, accessible, and reliable energy supply is essential for economic growth and poverty reduction. Yet, the necessary capital for major infrastructure investments may not always be available at reasonable cost, particularly in developing countries.

A novel modeling approach developed by ENE researchers jointly with collaborators from VTT in Finland and MIT in the United States allows analysis of how financial constraints would affect the transition toward improved energy access and greenhouse gas emission reductions. The methodology, which has been implemented in the MESSAGE model but is transferable to other energy-economic and integrated assessment models, has been applied to energy-climate scenarios for sub-Saharan Africa, a region strongly affected by capital scarcity in the energy sector.

The results portray the effect of capital cost on technology selection in electricity generation, specifically how limited capital supply decreases investments in capital-intensive renewable technologies that are also suitable to supply energy in decentralized settings. As a direct consequence, the incentives for potential investors need to be considerably increased when compared to a case that disregards the financial constraints. The research provides important insights with respect to the barriers of financing clean technologies in low-income countries.

Technology granularity

Granularity – the differences in the unit size of energy conversion and end-use technologies – has recently emerged as an important concept in the technological innovation literature, which was pioneered by TNT researchers. Granular energy technologies, such as wind turbines or solar PV panels, have also seen particularly strong market growth over the past decade, stimulated by a range of policy support measures.

Jointly with the TNT program and the Research Institute for Innovate Technologies for the Earth (RITE) in Japan, ENE researchers have developed an energy model that incorporates both technological learning and unit scaling (i.e., economies of scale due to increasing unit sizes). The new concept has been implemented in a prototype model which shows that granularity matters for the diffusion of electricity generation technologies.

The model reproduces important characteristics of the relative timing of unit size scaling and learning as observed in the past. In case of large economies of scale, the unit size scaling occurs early in the diffusion process, and large units dominate the market. In the case of more humble economies of scale, but with significant learning prospects, small units are deployed in large numbers before a scaling toward larger unit sizes occurs once the technology is mature. In addition, if different unit sizes are explicitly represented in a model – as opposed to an average “scale-free” technology – it was found that diffusion tends to be accelerated, in particular under high learning rates from which granular technologies profit due to their larger numbers.

Last edited: 30 October 2013