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Optimal control to handle variations in moisture content and reactor in-feed rate

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  • Kucuksayacigil, Fikri
  • Roni, Mohammad
  • Eksioglu, Sandra D.
  • Bhuiyan, Tanveer H.
  • Chen, Qiushi

Abstract

The variations in feedstock characteristics, such as moisture and particle size distribution, lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass pre-processing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by up to 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. Additionally, HPC reduces the cost of processing biomass by 0.36%–2.22%, and reduces processing time by 0.35%–2.24%. A biorefinery can adapt HPC to achieve its design capacity.

Suggested Citation

  • Kucuksayacigil, Fikri & Roni, Mohammad & Eksioglu, Sandra D. & Bhuiyan, Tanveer H. & Chen, Qiushi, 2022. "Optimal control to handle variations in moisture content and reactor in-feed rate," Energy, Elsevier, vol. 248(C).
    • Handle: RePEc:eee:energy:v:248:y:2022:i:c:s0360544222005539
    DOI: 10.1016/j.energy.2022.123650
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    References listed on IDEAS

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