The complexity dilemma-Insights from security of electricity supply assessments

Complexity in energy systems is increasing. In this context, we investigate if, and if so under which circumstances, more complex models are superior for providing a sound basis for decision making processes. On the one hand, energy system analysts keep increasing model complexity with the growing availability of data. On the other hand, decision makers tend to rely on the results of these ever more complex models. We focus our investigation on assessing the security of electricity supply with two different models associated with different levels of complexity: deterministic capacity balances and probabilistic simulations. We then abstract our findings by introducing a mathematical framework to determine the optimal level of detail for a model. With this, we demonstrate that, under the realistic assumptions made, the optimal model design is not reached by ever increasing model complexity. We summarize our findings as complexity dilemma: the more sophisticated the prevailing research question, the greater the need to depict the details of the underlying system, leading to more complex models. However, the accuracy of complex models highly depends on the quality of input data. Uncertainties of these input data and the costs for conducting sensitivity analyses, in turn, are high for complex models. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This study investigates the impact of increasing complexity in energy systems on decision-making processes and proposes a mathematical framework to determine the optimal level of model detail. The findings suggest that increasing model complexity does not necessarily improve accuracy, and high-complexity models suffer from uncertainties in input data and high costs for sensitivity analysis.