Multi-objective optimization and dynamic control of biogas pressurized water scrubbing process

Shida Gao, Cuimei Bo, Jun Li, Chao Niu and Xiaohua Lu

Renewable Energy, 2020, vol. 147, issue P1, 2335-2344

Abstract: For the biogas pressurized water scrubbing process, a plant-level optimizing control system based on the enhanced non-dominated sorting genetic algorithm (NSGA-II) is researched in this paper. According to the technological requirements of the biogas pressurized water scrubbing process, a steady state simulation system is established using Aspen Plus to analyze the constraint domain of the manipulated variables and optimize the operational variables. Under the multi-objective function of the total operating cost and purification effect, the Pareto optimal solutions with the constraints of feasible region of several variables are obtained using the NSGA-II algorithm. A plant-level dynamic control scheme is designed based on the optimal operating variables, and tested using the Aspen Dynamic simulation system. At last a pilot experimental device is developed based on the above optimized operating variables and the control scheme for the biogas pressurized water scrubbing process. The experimental results show that the system has good dynamic response performance, such as the removal rate of CO2 is greater than 99.8% under various disturbances.

Keywords: Biogas pressurized water scrubbing; NSGA-II; Multi-objective optimization; Dynamic control (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:147:y:2020:i:p1:p:2335-2344

DOI: 10.1016/j.renene.2019.10.022

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