Autonomous Decision Control of Start-Stop Timing for Coal Mills

Based on the characteristics of the start-stop timing of coal mills, an economic and flexible return function was designed to evaluate the quality of the start-stop timing. By utilizing intelligent decision-making algorithms, the optimal start-stop timing for coal mills was determined and validated...

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Bibliographic Details
Published in2023 IEEE 3rd International Conference on Digital Twins and Parallel Intelligence (DTPI) pp. 1 - 6
Main Authors Cai, Jiachen, Li, Jun, Gu, Yi, Qi, Yan, Gao, Lin, Chang, Peng, Liu, Haibin, Luo, Huanhuan, Chang, Yiming
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.11.2023
Subjects
Automation
autonomous start-stop control
Decision making
Deep learning
deep reinforcement learning
Economics
intelligent decision-making
Optimal start-stop timing
Power demand
Systems architecture
Training
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Summary:Based on the characteristics of the start-stop timing of coal mills, an economic and flexible return function was designed to evaluate the quality of the start-stop timing. By utilizing intelligent decision-making algorithms, the optimal start-stop timing for coal mills was determined and validated through simulation on a certain ultra-supercritical 1000MW unit. The results demonstrate that by making optimal decisions regarding the start-stop timing, it is possible to save auxiliary power consumption while ensuring the flexibility of the milling system. This approach provides convenience for operators and improves the automation level of the unit.
DOI:10.1109/DTPI59677.2023.10365416