CAREER: Process Systems Framework for the Efficient Design, Intensification and Control of Modular Energy Systems

West Virginia University Research Corporation, Morgantown WV

Investigators

Abstract

PI: Lima, Fernando Proposal Number: 1653098 Institution: West Virginia University Research Corporation Title: CAREER: Process Systems Framework for the Efficient Design, Intensification and Control of Modular Energy Systems This project aims to develop an optimization-based framework for the design and control of modular energy systems. The work is inspired by the current abundance of shale gas and its potential for use as a low-cost feedstock for producing energy and chemicals. To demonstrate the effectiveness of the developed approaches, two natural gas utilization case studies will be addressed: (i) a membrane reactor for direct conversion of methane to fuels and chemicals; and (ii) a natural gas combined cycle system for combined heat and power generation. The successful completion of the proposed research will provide a framework to facilitate the penetration of modular systems into the economy. The main educational and outreach goal of the proposal is to enable experiential learning by employing an interactive gaming environment of 3-D process simulators. To achieve this goal, the following activities are proposed: (i) incorporation of interactive simulator learning tools into undergraduate and graduate chemical engineering courses that include process systems concepts; and (ii) implementation of simulator-based gaming activities for outreach events focused on learning, exploration and recruitment. These activities will be designed to engage high-school and undergraduate students, including underrepresented groups, the lay public, and process systems researchers. The proposed research will provide theoretical advances in process design, control and estimation. Two research directions are proposed: (i) a nonlinear optimization-based approach for process design and intensification that employs computational geometry, optimization and statistical tools; and (ii) an integrated control-estimation framework for modular systems that incorporates moving horizon estimation into stochastic model predictive control. This potentially transformative research will lead to a deeper understanding of the feasible operating regions for modular energy systems to achieve process intensification and to overcome the control challenges of meeting product quality specifications under the presence of uncertainties and with reduced environmental footprint. By employing the developed methods, the proposed research is expected to accelerate the deployment of the concept of modular manufacturing for energy systems that produce value-added products from low cost methane gas resources with reduced footprint and maximized efficiency. The proposed framework is also flexible and could be adapted to tackle other complex chemical and energy processes.