Hydrogen from water electrolysis associated with renewable energies is one of the most attractivesolutions for the green energy storage. To improve the efficiency and the safety of such stations, sometechnological studies are still under investigation both on methods and materials. As methods, control,monitoring and diagnosis algorithms are relevant tools. These methods are efficient when they use anaccurate mathematical model representing the real behaviour of hydrogen production system. Thiswork focuses on the dynamical modelling and the monitoring of Proton Exchange Membrane (PEM)electrolyser. Our contribution consists in three parts: to develop an analytical dynamical PEMelectrolyser model dedicated to the control and the monitoring; to identify the model parameters and topropose adequate monitoring tools. The proposed model is deduced from physical laws andelectrochemical equations and consists in a steady-state electric model coupled with a dynamicalthermal model. The estimation of the model parameters is achieved using identification and datafitting techniques based on experimental measurements. Taking into account the information given bythe proposed analytical model and the experimentation data (temperature T, voltage U and current I)given by a PEM electrolyser composed of seven cells, the model parameters are identified. Afterestimating the dynamical model, model based diagnosis approach is used in order to monitoring thePEM electrolyser and to ensure its safety. We illustrate how our algorithm can detect and isolate faultson actuators, on sensors or on electrolyser system.