The sensitivity of power system expansion models

Summary Optimization models are a widely used tool in academia. In order to build these models, various parameters need to be specified, and often, simplifications are necessary to ensure the tractability of the models; both of which introduce uncertainty about the model results. However, a widely accepted way to quantify how these uncertainties propagate does not exist. Using the example of power system expansion modeling, we show that uncertainty propagation in optimization models can systematically be described by quantifying the sensitivity to different model parameters and model designs. We quantify the sensitivity based on a misallocation measure with clearly defined mathematical properties for two prominent examples: the cost of capital and different model resolutions. When used to disclose sensitivity information in power system studies our approach can contribute to openness and transparency in power system research. It is found that power system models are particularly sensitive to the temporal resolution of the underlying time series.