Model-based analysis of feedback control strategies in aerobic biotrickling filters for biogas desulfurization

Biotrickling filters are one of the most widely used biological technologies to perform biogas desulfurization. Their industrial application has been hampered due to the difficulty to achieve a robust and reliable operation of this bioreactor. Specifically, biotrickling filters process performance is affected mostly by fluctuations in the hydrogen sulfide (H2S) loading rate due to changes in the gas inlet concentration or in the volumetric gas flowrate. The process can be controlled by means of the regulation of the air flowrate (AFR) to control the oxygen (O-2) gas outlet concentration ([O-2](out)) and the trickling liquid velocity (TLV) to control the H2S gas outlet concentration ([H2S](out)). In this work, efforts were placed towards the understanding and development of control strategies in biological H2S removal in a biotrickling filter under aerobic conditions. Classical proportional and proportional-integral feedback controllers were applied in a model of an aerobic biotrickling filter for biogas desulfurization. Two different control loops were studied: (i) AFR Closed-Loop based on AFR regulation to control the [O-2](out), and (ii) TLV Closed-Loop based on TLV regulation to control the [H2S](out). AFR regulation span was limited to values so that corresponds to biogas dilution factors that would give a biogas mixture with a minimum methane content in air, far from those values required to obtain an explosive mixture. A minimum TLV of 5.9 m h(-1) was applied to provide the nutrients and moisture to the packed bed and a maximum TLV of 28.3 m h(-1) was set to prevent biotrickling filter (BTF) flooding. Control loops were evaluated with a stepwise increase from 2000 ppm(v) until 6000 ppm(v) and with changes in the biogas flowrate using stepwise increments from 61.5 L h(-1) (EBRT = 118 s) to 184.5 L h(-1) (EBRT = 48.4 s). Controller parameters were determined based on time-integral criteria and simple criteria such as stability and oscillatory controller response. Before implementing the control strategies, two different mass transfer correlations were evaluated to study the effect of the manipulable variables. Open-loop behavior was also studied to determine the impact of control strategies on process performance variables such as removal efficiency, sulfate and sulfur selectivity, and oxygen consumption. AFR regulation efficiently controlled [O-2](out); however, the impact on process performance parameters was not as great as when TLV was regulated to control [H2S](out). This model-based analysis provided valuable information about the controllability limits of each strategy and the impact that each strategy can have on the process performance.

Publication year:2021

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