Seasonal energy storage for zero-emissions multi-energy systems via underground hydrogen storage

Highlights

• Mathematical model describing underground H₂ storage in salt caverns and reservoirs.

• Reduced, linear version of full model that can be implemented in linear programming.

• Improved understanding of design and operation of underground H₂ storage.

• Role of H₂ storage in reducing CO₂ emissions of H₂-based integrated energy systems.

Abstract

The deployment of diverse energy storage technologies, with the combination of daily, weekly and seasonal storage dynamics, allows for the reduction of carbon dioxide (CO₂) emissions per unit energy provided. In particular, the production, storage and re-utilization of hydrogen starting from renewable energy has proven to be one of the most promising solutions for offsetting seasonal mismatch between energy generation and consumption. A realistic possibility for large-scale hydrogen storage, suitable for long-term storage dynamics, is presented by salt caverns. In this contribution, we provide a framework for modeling underground hydrogen storage, with a focus on salt caverns, and we evaluate its potential for reducing the ${\text{CO}}_2$ emissions within an integrated energy systems context. To this end, we develop a first-principle model, which accounts for the transport phenomena within the rock and describes the dynamics of the stored energy when injecting and withdrawing hydrogen. Then, we derive a linear reduced order model that can be used for mixed-integer linear program optimization while retaining an accurate description of the storage dynamics under a variety of operating conditions. Using this new framework, we determine the minimum-emissions design and operation of a multi-energy system with ${\text{H}}_2$ storage. Ultimately, we assess the potential of hydrogen storage for reducing ${\text{CO}}_2$ emissions when different capacities for renewable energy production and energy storage are available, mapping emissions regions on a plane defined by storage capacity and renewable generation. We extend the analysis for solar- and wind-based energy generation and for different energy demands, representing typical profiles of electrical and thermal demands, and different ${\text{CO}}_2$ emissions associated with the electric grid.