Assessment of control techniques for the dynamic optimization of (semi-)batch reactors

YesThis work investigates how batch reactors can be optimized to increase the yield of a desired product coupling two appealing techniques for process control and optimization: the nonlinear model predictive control (NMPC) and the dynamic real-time optimization (D-RTO). The overall optimization problem is formulated and applied to calculate the optimal operating parameters of a selected case study and the numerical results are compared to the traditional control/optimization techniques. It has been demonstrated in our previous work (Pahija et al, Selecting the best control methodology to improve the efficiency of discontinuous reactors, Computer Aided Chemical Engineering, 32, 805-810, 2013) that the control strategy can significantly affect optimization results and that the appropriate selection of the control methodology is crucial to obtain the real operational optimum (with some percent of improved yield). In this context, coupling NMPC and D-RTO seems to be the ideal way to improve the process yield. The results presented in this work have been obtained by using gPROMS® and MS C++ with algorithms of BzzMath library

A robust sustainable optimization & control strategy (RSOCS) for (fed-)batch processes towards the low-cost reduction of utilities consumption

YesThe need for the development of clean but still profitable processes and the study of low environmental impact and economically convenient management policies for them are two challenges for the years to come. This paper tries to give a first answer to the second of these needs, limited to the area of discontinuous productions. It deals with the development of a robust methodology for the profitable and clean management of (fed-)batch units under uncertainty, which can be referred to as a robust sustainability-oriented model-based optimization & control strategy. This procedure is specifically designed to ensure elevated process performances along with low-cost utilities usage reduction in real-time, simultaneously allowing for the effect of any external perturbation. In this way, conventional offline methods for process sustainable optimization can be easily overcome since the most suitable management policy, aimed at process sustainability, can be dynamically determined and applied in any operating condition. This leads to a significant step forward with respect to the nowadays options in terms of sustainable process management, that drives towards a cleaner and more energy-efficient future. The proposed theoretical framework is validated and tested on a case study based on the well-known fed-batch version of the Williams-Otto process to demonstrate its tangible benefits. The results achieved in this case study are promising and show that the framework is very effective in case of typical process operation while it is partially effective in case of unusual/unlikely critical process disturbances. Future works will go towards the removal of this weakness and further improvement in the algorithm robustness

From CO₂ to formic acid fuel cells

ABSTRACT: Formic acid is a liquid, safe, and energy-dense carrier for fuel cells. Above all, it can be sustainably produced from the electroreduction of CO₂. The formic acid market is currently saturated, and it requires alternative applications to justify additional production capacity. Fuel cell technologies offer a chance to expand it, while creating an opportunity for sustainability in the energy sector. Formic acid-based fuel cells represent a promising energy supply system in terms of high theoretical open-circuit voltage (1.48 V). Compared to common fuel cells running on H2 (e.g., proton-exchange membrane fuel cells), formic acid has a lower storage cost and is safer. This review focuses on the sustainable production of formic acid from CO₂ and on the detailed analysis of commercial examples of formic acid-based fuel cells, in particular direct formic acid fuel cell stacks. Designs described in the literature are mostly at the laboratory scale, still, with 301 W as the maximum power output achieved. These case studies are fundamental for the scale-up; however, additional efforts are required to solve crossover and increase performance

A novel real-time methodology for the simultaneous dynamic optimization and optimal control of batch processes

NoA novel threefold optimization algorithm is proposed to simultaneously solve the nonlinear model predictive control and dynamic real-time optimization for batch processes while optimizing the batch operation time. Object-oriented programming and parallel computing are exploited to make the algorithm effective to handle industrial cases. A well-known literature case is selected to validate the algorithm