A new approach to optimize the performance of a hydrogen reservoir using activated carbon as the storing material

We have developed a new approach in order to compute the optimal way of filling as efficiently as possible an hydrogen reservoir using activated carbon as the storing material. Our approach combines finite element computation with multi objective optimization techniques based on the Fast Pareto Genetic Algorithm (FPGA) to find an ensemble of optimal solutions known as the Pareto front. We have illustrated our method by studying a small cylindrical reservoir. We were able to find a 7-point filling function (i.e. the input flow as a function of time) giving the shortest filling time to reach a stored hydrogen mass for a given heat transfer coefficient while keeping the reservoir internal temperature and pressure under their maximal safe values.