Optimal Wind Farm Repowering under Uncertainty with Hydrogen Hybridization

Abstract

This paper addresses the optimal repowering of existing wind farms by integrating battery storage and green hydrogen production systems to enhance profitability and flexibility under market and resource uncertainty. A two-stage stochastic mixed-integer linear programming model is developed to jointly optimize wind turbine selection, battery sizing, and electrolyzer and hydrogen storage capacities. The model considers uncertainty in electricity prices, wind resource availability, and hydrogen prices through a scenario-based approach, and incorporates physical constraints such as turbine spacing and grid capacity. To ensure computational tractability, a chronological time-period clustering technique and an iterative technology-evaluation algorithm are applied. A case study of a wind farm in Spain demonstrates that hybridization with hydrogen increases expected annual profit by approximately 4%, while batteries remain uneconomical at current costs. Sensitivity analyses reveal that higher hydrogen prices significantly increase investments in electrolyzer capacity and hydrogen storage, highlighting the importance of supportive market conditions for the green hydrogen transition.