The Financial and Operational Impacts of Geomagnetic Disturbances on the Swiss Power System: A Causal Neural Network Approach

Geomagnetic disturbances are an emerging sustainability challenge for modern, low-carbon and highly interconnected power systems, affecting both grid stability and market performance. We develop a deep causal neural network that fuses geomagnetic observatory measurements with national operational indicators and, via counterfactual inference, traces shock and no-shock trajectories to estimate instantaneous and cumulative impacts. Using Switzerland as a case, shocks significantly change national load, canton-level consumption, cross-border flows, and balancing prices. East–west disturbances have stronger effects than north–south, highlighting the role of grid topology. At the regional scale, the canton of Aargau shows pronounced cumulative consumption responses, revealing spatial heterogeneity. In cross-border exchanges, imports rise after shocks while exports contract and transit flows decline; balancing prices increase markedly, suggesting that market mechanisms can amplify physical stress into economic impacts. The approach goes beyond correlation and exposure metrics by providing system-level, decision-relevant effect sizes. The main contributions are as follows: (i) a deep causal framework that identifies and quantifies the causal effects of geomagnetic disturbances on grid operations and prices; (ii) topology-linked empirical evidence of directional and spatial asymmetries across national, canton-level, and cross-border indicators; and (iii) actionable levers for system operation and market design. These findings inform risk-aware reserve procurement, topology-aware dispatch, and cross-border coordination in highly interconnected, low-carbon grids, helping to enhance reliability, maintain affordability, and facilitate clean-energy integration.