Identifying key elements for adequate simplifications of investment choices - The case of wind energy expansion

The analysis of future energy systems with increasing shares of renewable energy production poses various challenges to models used in the field of energy system analysis. Aggregation is one solution to reduce the computation time of large optimization problems, especially for optimization models with endogenous capacity expansion. Since the economic viability of renewable investments is not directly driven by physical and technical characteristics but rather by the corresponding revenue and cost streams, we propose a novel aggregation method. The aggregation covers both the spatial and the technological dimension of wind investment choices, i.e. the siting as well as the turbine choice. Four value components are defined, related e.g. to the total yield or the site-specific infeed profile of investment choices. A clustering approach is applied to these value components to identify groups of investment choices that can be aggregated without excessive loss of accuracy. The approach is applied in a case study for the German electricity system and the influence of the different value components on the combined technological and spatial aggregation is analyzed.