  The rapid expansion of renewable energy sources has introduced significant
volatility and unpredictability in the energy supply chain, necessitating
advanced control strategies to ensure grid stability and reliability. Green
hydrogen production via electrolysis offers a viable solution for converting
and storing this volatile renewable energy. However, the inherent fluctuations
of renewable energy sources present challenges for consistent utilization and
integration of green hydrogen. This work proposes a two-stage optimization
approach, combining site-wide optimization and real-time optimization for
managing systems of electrolyzers. By adapting an existing static optimization
model, dual use is achieved in both site-wide optimization and real-time
optimization. The hierarchical optimization structure, characterized by
distinct temporal resolutions, enables effective responses to both dynamic
changes and long-term trends. The side-wide optimization layer generates
long-term plans based on forecast data, while the real-time optimization layer
refines these plans in real-time, accommodating immediate fluctuations and
ensuring efficient operation. The results from the case study on a system of
electrolyzers demonstrate the method's effectiveness in aligning electrolyzer
operation with actual availability of renewable energy. This approach offers a
robust framework for optimizing the operation of electrolyzers but also other
types of flexible energy resources, contributing to sustainable and
economically viable energy management.
