Locating and dispatching flexibility in spatially resolved energy system models: a case study of Austria

The transformation of energy systems driven by the increasing integration of renewable energy sources is leading to a growing flexibility demand. Flexibility options such as battery electric storage systems or power-to-gas can play a key role in addressing this challenge. However, questions remain regarding the optimal siting and deployment of such technologies. This paper presents a novel methodology for optimizing flexibilities in spatially resolved energy system models. Flexibility deployment is based on two different strategies—market-driven and peak-shaving—while flexibility siting is done through a combination of residual load analysis and linear programming. The methodology is applied to a use case representing a climate-neutral Austria in 2040. Based on the Integrated Austrian Network Infrastructure Plan, a model of the very-high-voltage and high-voltage power system in Austria is developed and the siting and deployment of flexibilities is optimized within this framework. The two deployment strategies are then assessed by simulating hourly power flows and thus evaluating their impact on grid utilization. Assuming flexibility expansion according to the Integrated Austrian Network Infrastructure Plan, both strategies lead to a significant decrease in grid utilization. This is especially interesting for the market-driven strategy: While peak-shaving deployment depends on forecasting and covering local flexibility demands, market-driven deployment is based on aggregated spot market price and thus presents a comparatively realizable strategy. This paper shows that, given an optimal siting, even a purely market-driven deployment can contribute to supporting the power grid.