Sizing of Balance of Plant components for a Multi-Stack Fuel Cell System

The development of fuel cell technology has played a crucial role in advancing effective methodologies for hydrogen utilization, particularly when hydrogen is employed as an energy storage solution. Multi-stack fuel cell systems, in particular, offer the potential to enhance overall system efficiency by interconnecting multiple cells, with the goal of reducing the energy required to power auxiliary systems. SINTEF, one of Europe’s largest independent research organizations, aims to support Norway's ambition to decarbonize the offshore petroleum sector while maintaining international competitiveness through the CleanOFF project. This project explores two main pathways: integrating renewable energy sources with hydrogen as the primary energy storage solution and utilizing compact carbon capture and storage systems. This work focuses specifically on the hydrogen-based model. The objective of this study is to identify a potential optimal configuration, considering fuel supply systems, oxidant supply, and cooling systems. To model a realistic representation of this technology, an initial reference system was developed analytically to validate results obtained through the COFE software. Once validated, two potential architectures were identified and introduced, based on their significance as highlighted in the literature. The most significant results, which were compared to identify the optimal configuration, include system efficiencies. These efficiencies account for the power produced by the fuel cell and the total power required within the system. Both models demonstrate high efficiency, providing a strong foundation for further in-depth research. Additionally, key areas such as fuel cell operation, energy balance, and thermal management are briefly discussed. The performance results will also be examined through complementary analyses focusing on control, redundancy, cost, and regulation. These additional analyses will provide a more comprehensive understanding of the practical viability of the models and guide future developments, which are explored in the final section of this thesis.