This paper assesses a Hybrid Energy Storage System (HESS) at The Green Village (TGV) of Delft University of Technology (TU Delft), designed and developed as a combination of a lithium-ion battery and hydrogen storage systems to provide a residential energy supply. This paper will evaluate the combination of producing solar-powered green hydrogen through electrolysis, as well as daily and seasonal combinations of battery and hydrogen storage, and electricity generation through a fuel cell. Through an analysis of various sensor data that contained power and hydrogen flow, and control signals, this case study reports on the overall efficiency of the HESS, encourages user energy balancing strategies, and assesses its capability to store sustainable energy over long periods. Based on the same dataset, preliminary machine learning models have been developed and evaluated to predict hydrogen production from weather and PV inverter measurements, supporting future EMS optimization. Therefore, this case study indicates improvements that led to key observations.

This study presents a data-driven offline digital twin model of an operational residential hydrogen hub equipped with more than 100 sensors. The model enables analysis and scaling of hydrogen-based hybrid energy hubs from residential to larger systems. The hub integrates photovoltaic generation, battery storage, hydrogen production via electrolysis, compressed hydrogen storage, and fuel cell electricity generation. Using year-long field data, the model reproduces the current configuration (5.34 kWp PV, 15 kWh battery, ~ 45 kg H₂) and quantifies annual performance: 5,102 kWh PV generation, hydrogen production and consumption efficiencies of 48.0% and 39.6%, 25.3 kg H₂ produced versus 49.3 kg consumed, and net grid exchange of +114 kWh. Multi-scenario sizing shows that an optimized configuration (8.46 kWp PV, 30 kWh battery, 70 kg H₂) reduces grid import to ~ 30 kWh yr^-1 while exporting ~ 380 kWh, with the H₂ buffer ending the year near its initial state under a rule-based energy management strategy. The results demonstrate the capability of a sensor-validated framework for designing integrated PV-battery-hydrogen energy hubs.