Search

As energy systems grow more complex, modeling efforts spanning multiple scales, disciplines and perspectives are essential. Improved methods are needed to guide the development of not just individual models, but also multi-model ecologies - systems of interacting models. Currently there is a lack of knowledge concerning how multi-model ecologies can and should be designed to facilitate adequate understanding of energy system complexity and its consequences. Via an analysis of twelve multi-model initiatives both within and outside the energy domain, this paper elucidates possible design patterns and development paths for multi-model ecologies.The results highlight two broad paths to developing energy system multi-model ecologies, one prioritizing interoperability and the other prioritizing diversity. The former path facilitates the efficient development of models spanning multiple scales and (to a degree) disciplines, and can ease systematic testing of assumptions. The latter is suited to bridging traditional disciplines and perspectives and advancing knowledge within the interstices of different knowledge communities. It is furthermore suggested that a combination of diversity, connectivity and hierarchy in multi-model ecology composition is central to enabling the development of complex webs of models capable of addressing the complexity of real-world energy systems.

This paper focuses on standards battles for photovoltaic technological systems. Five photovoltaic technologies are currently commercially available and it is still unclear which of these technologies will emerge as the dominant design. Based on the literature and on expert interviews, we develop and analyze categories and factors for technology dominance for these systems. By applying the analytic hierarchy process, we determine the importance of these factors and the chances of one of these five technologies becoming the dominant photovoltaic technology. The crisp and fuzzy (logarithmic fuzzy preference programming) analytic hierarchy process method is used to analyze the data. The results show that the standard support strategy is the most important category, and that pricing strategy and technological superiority are the most influential factors in the dominance process. Furthermore, the first generation technology mono-crystalline silicon photovoltaic has the best chance of achieving dominance (30% chance). The results of this study are useful for multiple stakeholders (e.g. energy policy makers and photovoltaic module companies) who have to make the decision as to which standard should be supported for photovoltaic technology.