Energy system modeling studies lag behind policy making

Do researchers need all those optimization models?

I would argue that developing new optimization models specifically geared towards answering specific research questions is justifiable, but research should aim to expand on existing tools rather than developing similar models yet again.

The majority of novel energy system models improve on existing modeling approaches, for example, by developing a method to better approximate the operation of seasonal storage technologies. While adding new modeling tools to the already large database of open source models allows the research community to provide even more tailored answers to critical research questions, the continuous addition of new models has downsides, of which I would like to address two.

First, a significant amount of time and effort has to be put into the development of a new optimization model. In many cases, though, the added value created by the new tool is only incremental as a large portion of the models cover overlapping, if not even identical, functionalities. Second, explanations on the model formulation and data quality of new modeling tools is often intransparent and requires a thorough examination of the code and other related information to obtain an understanding of how the new tool answers the particular research question it was aimed at answering.

To tackle these challenges, modeling initiatives and platforms are developing to help researchers understand the capabilities of the readily available models and to improve access to new modeling additions. One example is the OpenMod Initiative, a community that hosts a database for most open source energy system models available and presents their key functionalities, allowing researchers to search for and compare models more easily. It further offers a multitude of resources on input data and modeling approaches. Other initiatives, such as the Nexus-e project take it upon themselves to combine the models into one large platform. Its aim is to use the synergies between all available models to create a powerful framework that is readily accessible for everyone and more versatile than each of its individual parts.

Those initiatives show that, while we might not necessarily need every single model that is being developed, expanding existing energy system models helps us investigate even more nuanced and complex research questions by pooling together the collective modeling knowledge already available. By combining and expanding existing research, we can make the resulting research more precise and valuable for our target audience – policy and decision makers.

Are modeling studies useful for policy making?

In our review on electricity system modeling studies of Switzerland, Germany, France, and Italy, my co-author Georgios Mavromatidis and I concluded that a majority of study results can be seen as outdated only one or two years after their publication when considering the policies considered in the studies.

To give an example: In the majority of the studies renewable energy targets are not represented or significantly less ambitious than what current governments propose. Often, fully renewable energy generation is omitted as a goal for the future entirely, as Figure 1 shows for studies on the Swiss electricity transition.