Due to greenhouse gas emissions, global warming has severe environmental consequences. To tackle this issue, XINTC produces green hydrogen using alkaline electrolysis to replace fossil fuels. Green hydrogen’s primary challenge is its dependence on intermittent energy sources for electrolysis. Hydrogen storage is necessary for the hydrogen economy to meet production and demand peaks. This work focused on hydrogen storage using double membrane gas holders storing hydrogen at atmospheric pressure, a novel hydrogen storage method. The main goal of the storage is to avoid power cycling the downstream hydrogen compressor. Energy and mass balances are calculated considering molecule permeation through the membranes and water condensation. Weather conditions are also taken into account. To regulate the pressure in the storage, a control system consisting of PID controllers connected to pressure relief valves was designed.
The model shows the behaviour as a response to changing weather conditions. It has been proven that the water in the system will condense and, at certain points, even freeze. A drain is necessary to evacuate the water forming in the system. The control system manages the system accordingly, opening the valves to the desired amounts at the desired moments.
It was also proven that one should not have to worry about forming a combustible hydrogen-oxygen mixture. If the storage is filled at 10% of its maximum value, it takes more than 500 days to reach that value.
The permeation of nitrogen through the membrane is a bigger issue. If the storage is filled to 10% of its maximum value, the maximum concentration of 300 PPM is exceeded within three days at a standstill. Thus, the storage will have to be drained long before safety issues arise.
The model is fully modular, meaning that it can be run for all locations around the world. It can easily compare storage behaviour and performance.
The outcome of this research has led to a better understanding of the behaviour of hydrogen storage in membrane gas holders. The model developed can be used to effectively manage hydrogen storage, reducing any hydrogen losses and maximising storage efficiency