Hydrogen is one of the key components in renewable energy systems. Its storage and transport, however, are challenging. The Liquid Organic Hydrogen Carrier (LOHC) technology is a possible solution for this issue. With suitable organic components, hydrogen can be stored in a chemically bound form which is safer and has a higher energy density than other solutions. Furthermore, the storage and transport of the LOHC component with high hydrogen content can be provided under normal environmental conditions. The LOHC process cycle involves a catalytic hydrogenation and dehydrogenation step where the LOHC component can be recovered and recycled. The paper reviews a few relevant studies regarding the possible LOHC compound pairs, the potential catalyst systems, and the necessary equipment. Then, the paper discusses a simulation study of three LOHC systems, determining suitable operating conditions and estimating costs. The toluene-methylcyclohexane system was found to be the most promising for LOHC application. Two energy integration opportunities were also examined. The first case study was based on separate hydrogenation and dehydrogenation sites, while the second was based on one site utilization. The results show a lower energy demand in the case of a toluene system, with a reduction of 70% in heating and 45% in cooling. Graphical Abstract

In this article, the authors focus on the introduction of a hybrid method for risk-based fault detection (FD) using dynamic principal component analysis (DPCA) and failure method and effect analysis (FMEA) based Bayesian networks (BNs). The FD problem has garnered great interest in industrial application, yet methods for integrating process risk into the detection procedure are still scarce. It is, however, critical to assess the risk each possible process fault holds to differentiate between non-safety-critical and safety-critical abnormalities and thus minimize alarm rates. The proposed method utilizes a BN established through FMEA analysis of the supervised process and the results of dynamical principal component analysis to estimate a modified risk priority number (RPN) of different process states. The RPN is used parallel to the FD procedure, incorporating the results of both to differentiate between process abnormalities and highlight critical issues. The method is showcased using an industrial benchmark problem as well as the model of a reactor utilized in the emerging liquid organic hydrogen carrier (LOHC) technology.