Robust Planning of Battery–Hydrogen Hybrid Energy Storage Under Heatwave-Induced Source–Load Uncertainty

Abstract

Extreme heat events can cause sustained load growth, reduced renewable power output, and increased source–load uncertainty, posing challenges to supply–demand balance in power systems with high renewable penetration. To address hourly power fluctuations and cross-day energy deficits under extreme heat conditions, this study proposes a two-stage robust planning method for coordinated battery–hydrogen energy storage. The proposed method constructs a wind–PV–load uncertainty set based on historical heatwave events, where quantile-based boundaries, disturbance budgets, and variation rate constraints are introduced to characterize adverse source–load variations. The storage capacity configuration and worst-case operation scheduling are integrated into a unified framework and solved using the column-and-constraint generation (C&CG) algorithm. Case studies demonstrate that the proposed method reduces the system load shedding rate to 0.01% and the wind and PV curtailment rate to 3.15%. Compared with no-storage and single-storage schemes, the battery–hydrogen hybrid energy storage system effectively improves system resilience and reduces renewable energy curtailment under heatwave scenarios.