When There's No November Rain: Developing a Parametric Insurance for Hydroelectric Energy Generators in Brazil

Hydrological risk is a growing challenge for renewable power systems, as droughts reduce generation, increase costs, and expose gaps in risk-transfer mechanisms. We examine this problem in Brazil, home to the world's sixth-largest electricity system and highly dependent on hydroelectricity, which accounted for 43% of installed generation capacity in 2026. We develop and evaluate a parametric insurance scheme for run-of-river hydroelectric generators indexed to the National System Operator's affluent flow measure. Using monthly energy and climate data from 151 powerplants between 2006 and 2022, we incorporate hydrological network dependence into insurance design. We model generation through a time-varying upstream-downstream spatial network and estimate it using a two-way fixed-effects SAR-IV-GMM-HAC specification. We then use vine copulas to assess the dependence structure among climatic variables, hydrological conditions, and electricity generation, supporting the use of affluent flow as the insurance trigger. Results reveal significant hydrological propagation across connected plants and indicate that parametric insurance can mitigate drought-related losses. However, feasibility depends on plant-specific trigger design, diversification, reinsurance support, and payout magnitude. Water-storage plants exhibit higher basis risk because of their operational flexibility.