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.

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 paper presents a simulation-based case study of a hybrid energy hub located at The Green Village (TGV), a living lab for sustainable innovations in Delft, The Netherlands. The energy hub integrates photovoltaic (PV) generation, battery storage, hydrogen production, seasonal storage, and usage to provide a fully electrified one-person residence, serving as a realistic testbed for the integration of renewable energy. A model of the hub is developed in Simulink/Matlab using historical operational data to simulate system behaviour under various edge case scenarios and system configurations. The model enables the evaluation of system-level interactions, operational strategies, and the impact of design choices on energy efficiency, self-sufficiency, and hydrogen integration. The simulation results show the sensitivity of the system performance to component sizing and EMS settings. This study provides valuable insights into the control and optimisation of The Green Village’s energy hub and its integrated energy systems, contributing to the practical deployment of resilient and sustainable energy hubs in the built environment.