Spatial Battery Siting under Renewable Cost Floors: A PyPSA-Eur Analysis for Europe to 2050

Solar photovoltaic costs have fallen far faster than anticipated since 2010, driving an unforeseen expansion of solar generation; similar cost declines have occurred for wind and are expected to occur for battery storage. Many European planning studies still rely on conservative cost projections that may misrepresent the future role and value of battery storage. This raises a key question for high-renewables power systems: how do faster-than-expected renewable cost reductions and uncertain battery cost trajectories interact to shape the cost-effective deployment and siting of battery storage?

This study addresses this question using the open-source PyPSA-Eur model to represent the European power system with hourly resolution and isolating the arbitrage value under uncertain costs to identify spatially explicit battery capacity. Current battery storage projects often rely on revenue stacking, combining energy arbitrage with frequency services such as fast frequency response and dynamic containment, but these ancillary markets are likely to saturate as the deployment grows, motivating a focus solely on arbitrage value. The analysis draws on recent empirical work that derives national solar and wind cost floors from a comprehensive panel of historical deployment and cost data, showing that global solar costs are likely to continue declining and remain substantially below wind, whose costs approach a moderate floor by mid-century (Baumgärtner & Farmer, 2025). These cost floors are used as boundary conditions for 2030 and 2050 scenarios that explore five discrete cost levels for utility-scale batteries and wind, while treating solar as already very low-cost.

By systematically varying these inputs, the analysis quantifies the spatial patterns of battery capacity location, duration mixes, and use across Europe. The scenario ensemble highlights the temporal complementarity between cheap solar/wind and storage arbitrage, identifying locations where batteries robustly mitigate renewable droughts and where deployment remains highly sensitive to costs. These insights inform resilient spatial planning for high-renewable energy systems under deep technological uncertainty.