Research on the Application of Mechanistic Mathematical Models Smart Control Systems for Wastewater Treatment Plants
Year: 2025
Type: conference-paper
Abstract: With the development of social economy and sewage plant effluent standards become more and more strict, relying on traditional sewage treatment plant management and operation methods is difficult to achieve stable discharge and reduce energy consumption. In order to ensure the efficient operation of wastewater treatment plants and more energy saving, the intelligence of wastewater treatment plants is inevitable. This paper describes the construction of the mechanism mathematical model, performance evaluation and practical application effect, the results show that the mechanism model intelligent control system can make the sewage treatment compliance rate increase by 20%, showing superior control performance. In terms of treatment cost, the electricity consumption and chemical usage are reduced by 18.9%, effectively realizing energy saving and consumption reduction. After more than four years of operation, the model control rate is as high as 98%, and only a small number of technicians are needed for system maintenance, reducing labor costs by about 50%. The intelligent control system based on the mechanism mathematical model has the characteristics of self-learning and self-adaptation, which can be adapted to different operating conditions to meet the current requirements of actual wastewater treatment, and has great potential for application and market prospects. This study analyzes and evaluates the operation and effect of the intelligent control system based on the mathematical model of mechanism, and provides case support and technical guarantee for the engineering application and promotion of the intelligent control system.
Authors: Yuzhen Shi, Chengbo Chang, Chen Zhang, Han Cui, Yanqiong Chen
Institution: Kunming University of Science and Technology
Language: English
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413812440