[Case Study] Suitable Control of Power Plant Denitrification System 'DTEmpower'
A control method that combines "predictive control," "adaptive control," and "feedback correction" is effective!
Based on the issues in the de-NOx system of power plants, we will introduce solutions using the data analysis and modeling software "DTEmpower," as well as optimal control of the system. The de-NOx system has significant thermal hysteresis effects, making it difficult to construct physical and chemical models. Therefore, a control method that combines "predictive control," "optimal control," and "feedback correction" utilizing machine learning based on datasets is effective. As a result of applying data analysis, we can accurately and quickly predict changes in NOx concentration within the de-NOx system through machine learning, providing a reduction in the impact of the boiler's thermal hysteresis effect and optimizing rational system control. [Issues with the de-NOx System] - Unable to respond quickly to fluctuations in nitrogen oxide (NOx) concentration. - It is necessary to excessively spray ammonia at the flue gas outlet to reduce NOx concentration. - Excessive spraying of ammonia can lead to dust accumulation on the catalyst and clogging of the air preheater, resulting in decreased boiler operating efficiency and increased operational costs. *For more details, please download the PDF or feel free to contact us.
basic information
【Results of Data Analysis Applications】 ■Prediction of Nitrogen Oxide Concentration Changes ■Optimal Control in Finite Time Domains *For more details, please download the PDF or feel free to contact us.
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