Bayesian Optimization of Operating Points of a Continuous Perhydro‐Dibenzyltoluene Dehydrogenation Reactor

Abstract

Liquid organic hydrogen carriers (LOHCs) are a promising option for hydrogen storage, but a high efficiency of the LOHC cycle is essential in order to serve as an attractive technology in the context of decarbonization. This paper presents different methods to optimize steady‐state operating points of a LOHC dehydrogenation (DH) reactor. For this purpose, an analytical model of a DH reactor is described, which is extended to a hybrid model (HM) to achieve sufficient model accuracy. The model quality is subsequently validated by measurements. For the optimization of the steady‐state operation point, a Bayesian optimization framework is presented and compared to classical model‐based optimization. The methods are evaluated with the HM as well as with experimental results