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| Optimal Control of Dissolved Oxygen for Greenhouse Gas Reduction from Wastewater Treatment Plant in Paper Mill |
| Received:May 11, 2020 |
| DOI：10.11980/j.issn.0254-508X.2020.08.004 |
| Key Words:greenhouse gas wastewater from papermaking mill optimum control dissolved oxygen |
| Fund Project:国家重点研发计划项目（2017YFE0184900）；广东省自然科学基金项目（2019A1515011149）。 |
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| Abstract:Activated sludge process is widely used for wastewater treatment in pulp and paper industry. A mass of greenhouse gas (GHG) generates from the processing, which merely gets a handful of attention and lacks of on-line detection and mitigation. To solve this problem, a layered optimization dissolved oxygen (DO) control strategy based on adaptive kernel regression propagation neural network proportional integral (AKRBP-PI) control was proposed. The object of the study was to reduce the GHG emission in the premise of insuring effluent quality. The optimal control was based on the action mechanism of dissolved oxygen on greenhouse gas emissions and the idea of stratification was adopted. According to the functional constraint relation between pollutant content of effluent and dissolved oxygen, the set value of dissolved oxygen optimization was solved by genetic algorithm, and the neural network tracking control was realized. The simulation results showed that compared with the open-loop control, the effluent pollutant content of AKRBP-PI scheme met the regulation requirement, and the greenhouse gas emission reduced by 8.6%. Wherein, the reduction of greenhouse gases mainly came from the reduction of power consumption of the aerator. |
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