Research on self-optimization of water-coal ratio in thermal  supercritical power units based on VAR model

Yu Zhao; Baochan Zou; Shengdong Du

doi:10.1117/12.2646769

7 September 2022 Research on self-optimization of water-coal ratio in thermal supercritical power units based on VAR model

Yu Zhao, Baochan Zou, Shengdong Du

Author Affiliations +

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123290S (2022) https://doi.org/10.1117/12.2646769
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

To solve the problem of water-coal ratio imbalance under the frequent changes of coal quality in thermal power supercritical units, this paper proposes a vector autoregressive (VAR) model to achieve self-optimization of water-coal ratio of the unit under steady state. This method takes a supercritical 350MW unit as an example. By screening the time series data of key parameters of the unit under steady-state operating conditions, the optimal order of VAR model is determined. Using the VAR model, we can find the optimal value of water-coal ratio under the corresponding operating conditions. And this paper further adopts error analysis, uncertainty analysis, and impulse response analysis to ensure the accuracy and safety of the optimal value of water-coal ratio. In actual operation, the unit can use the VAR model to achieve self-optimization, that is, to find the optimal water-coal ratio under different coal qualities, and to form the water-coal ratio curve under the current coal quality. Practice has proved that this method can effectively solve the problems of large deviation of the main steam temperature and main steam pressure caused by the unsuitable boiler feed water strategy due to frequent changes in coal quality of the unit.

Citation Download Citation

Yu Zhao, Baochan Zou, and Shengdong Du "Research on self-optimization of water-coal ratio in thermal supercritical power units based on VAR model", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123290S (7 September 2022); https://doi.org/10.1117/12.2646769

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