Local control of fuel cell systems within hybrid renewable energy generation using model predictive control

Abstract

This paper presents model predictive control (MPC) strategies to tracking local control systems when subjected to supervisory optimal trajectories. The supervisory trajectories are generated using economic receding horizon optimization based on energy management in the energy-intensive industry (e.g., chlor-alkali process) with a hybrid renewable energy system (HRES), including solar, wind, and fuel cell sub-systems. A planer solid oxide fuel cell system is adopted in this study, and its power output is regulated using a constrained MPC controller. The feasibility of MPC control algorithm in regulating energy sub-systems to meet supervisory commands will be studied and evaluated at different parameters and against traditional PI controller. © 2018 The Authors. Published by Elsevier Ltd.