A future energy system that to a large extent depends on variable renewable energy sources, like wind and solar power, involves new challenges for securing a reliable supply of electricity. The economic basis for such an electricity system differs significantly from the one we have today, and one can expect that prices will be more volatile and risk for shortages in supply increases. In the transition towards a renewable energy system, foresight is needed in order to design policies that facilitate changes that are required for the transition. This also includes improved understanding of possible consequences of implemented measures and policies—also the unintended ones, like the increased price volatility in the example above. Another example of undesired consequences that has been discussed as a possible effect of climate policies is the food price peaks we have witnessed the passed ten years. In order to address these issues, we will develop a new set of models that explicitly includes mechanisms for decisions— mechanisms that do not necessarily assume rational agents but may allow for bounded rationality. These models may be formulated on the level of individual agents (citizens, firms, regions, etc), so-called agent-based models, or projections of agents into aggregate variables leading to dynamic simulation models. One major aim with the project is to critically and carefully investigate the difference between the possible modelling approaches.
Professor at Energy and Environment, Physical Resource Theory
Funding years 2016–2018
Chalmers Driving Force