Minimisation of Carbon Footprint and Energy Optimization in Green Hydrogen Transport: A Holistic Digital Twin Approach

The global push for decarbonization highlights green hydrogen as a crucial energy carrier for future sustainable economies. My research zeroes in on pipeline transport of this hydrogen, an area vital for efficiency and low carbon impact, yet challenged by high energy use for compression and the risk of leaks affecting environmental balance. This paper presents a new, comprehensive Digital Twin framework designed to model, simulate, and optimize the entire green hydrogen pipeline transport system. Unlike conventional static models, this Digital Twin incorporates real-time data from physical infrastructure, advanced physical models of hydrogen behavior, and sophisticated algorithms for compressor optimization and proactive leak identification. My approach aims for a complete, dynamic representation, enabling continuous, proactive management and sustained performance improvements. Early analyses clearly show the Digital Twin’s ability to significantly quantify and lower both the energy used for hydrogen compression and the resulting carbon emissions from transport. This boosts the system’s operational efficiency, safety, and overall economic and environmental feasibility. This work provides a concrete step toward faster deployment of strong, sustainable hydrogen energy infrastructure.