This work focuses on the development and implementation of an integrated process design and control framework for a membrane-based hydrogen production system based on low temperature methane steam reforming. Several alternative flowsheet configurations consisted of either integrated membrane reactor modules or successive reactor and membrane separation modules are designed and assessed by considering economic and controller dynamic performance criteria simultaneously. The design problem is expressed as a non-linear dynamic optimization problem incorporating a nonlinear dynamic model for the process system and a linear model predictive controller aiming to maintain the process targets despite the effect of disturbances. The large dimensionality of the disturbance space is effectively addressed by focusing on disturbances along the direction that causes the maximum process variability revealed by the analysis of local sensitivity information for the process system. Design results from a multi-objective optimization study, where only the annualized equipment and operational costs are minimized, are used as reference case in order to evaluate the proposed design framework. Optimization results demonstrate the controller’s ability to track the imposed setpoint changes and alleviate the effects of multiple simultaneous disturbances. Also, significant economic improvements are observed by the implementation of the integrated design and control framework compared to the traditional design methodology, where process and controller design are performed sequentially.

The goal to reduce greenhouse gas emissions necessitates the increase in RES utilization. To accomplish this goal, energy storage solutions are required. This study investigates the performance of an electrothermal energy storage system, the CEEGS, which consists of an above-surface energy storage system and a below-surface geological system. The focus is set initially on the analysis of the above-surface system to gain insight into its operation. Then, steady-state optimization is utilized to identify the operating conditions that maximize the system performance, before investigating the below-surface system integration and the effect that the geological conditions have on system performance. For the above-surface system, efficiency (η_R-T) up to 46.89% is calculated. For systems integrated with CO₂ geological storage, two case studies are examined, presenting higher η_R-T compared to the above-surface system (Case study 1: 50.37%, Case study 2: 67.39%). The optimal η_R-T for Case study 2 is achieved for higher injection/production pressures and temperatures conditions and minimal ΔP and ΔT between injection and production. In conclusion, it is the selection of the geological storage conditions that contribute the most to the optimal η_R-T; thus, the selection of the appropriate geological storage formation is imperative.

The goal to reduce greenhouse gas emissions necessitates the increase of RES utilization. To accomplish this goal, energy storage solutions, are required. This study investigates the performance of an electrothermal energy storage system, the CEEGS system, which consists of an above surface energy storage system and a below surface geological system. The focus is set initially on the analysis of the above surface system to gain insight on its operation. Then steady-state optimization is utilized to identify the operating condition that maximize the system performance, before investigating the bellow surface system integration and the effect that the geological conditions have on system performance. For the above surface system, efficiency (ηR-T) up to 46.89 % is calculated. For system integrated with CO2 geological storage, two case studies are examined, presenting higher ηR-T compared to the above surface system (Case study 1-50.37 %, Case study 2-67.39 %). The optimal ηR-T for Case 2 is achieved for higher injection/production pressures and temperatures conditions and minimal ΔP and ΔT between injection and production. In conclusion, it is the selection of the geological storage conditions that contribute the most to the optimal ηR-T thus the selection of the appropriate geological storage formation is imperative.