Modeling, optimization, and control of microbial electrolysis cells in a fed-batch reactor for production of renewable biohydrogen gas

An integrated modeling, optimization, and control approach for the design of a microbial electrolysis cell (MEC) was studied in this paper. Initially, this study describes the improvement of the mathematical MEC model for hydrogen production from wastewater in a fed-batch reactor. The model, which was modified from an already existing model, is based on material balance with the integration of bioelectrochemical reactions describing the steady-state behavior of biomass growth, consumption of substrates, hydrogen production, and the effect of applied voltage on the performance of the MEC fed-batch reactor. Another goal of this work is to implement a suitable control strategy to optimize the production of biohydrogen gas by selecting the optimal current and applied voltage to the MEC. Various simulation tests involving multiple set-point changes, disturbance rejection, and noise effects were performed to evaluate the performance where the proposed proportional–integral–derivative control system was tuned with an adaptive gain technique and compared with the Ziegler–Nichols method. The simulation results show that optimal tuning can provide better control effect on the MEC system, where optimal H2 gas production for the system was achieved.