Optimization of hydrogen supply from renewable electricity including cavern storage

The present study introduces a methodology to model electricity based hydrogen supply systems as a Mixed Integer Linear Programming (MILP) problem. The novelty of the presented approach lies especially in the linear formulations of the models for electrolysis and salt cavern storage. The proposed linear electrolysis model allows for an accurate consideration of operating limits and operating point-specific efficiencies, while the two-dimensional cavern model treats the cavern volume as a decision variable. The developed formulations are implemented in the open energy modeling framework (oemof) and applied to representative case studies with 2020 marginal conditions. Thereby, it has been confirmed that the individual consideration of power supply and hydrogen demand is crucial for optimal system design and operation. If electricity is drawn exclusively from the German grid, hydrogen costs of 2.67 (sic) kg(H2)(-1) are identified along with an increased CO2 footprint compared to natural gas based hydrogen. By contrast, a significantly reduced CO2 footprint results from autarkic wind power supply at costs of at least 4.28 (sic) kg(H2)(-1). Further findings on autarkic operation include optimal ratios of electrolyzer and wind farm nominal power, as well as power curtailment strategies. Evidence is provided that salt cavern interim storage is beneficial. With grid connection, it serves to exploit electricity price fluctuations, while with renewable autarkic operation, it is essential to compensate for seasonal fluctuations in generation.

Automated summary

This study introduces a new methodology for modeling electricity-based hydrogen supply systems, emphasizing the linear formulations of electrolysis and salt cavern storage models, as well as the crucial individual consideration of power supply and hydrogen demand for optimal system design and operation.