Research on neural network modeling of thermal power unit load system

Zhongzhou Dou; Ruicai Si; Xing Cao; Jinfeng Zhao; Yingying Yao; Hang Wang; Hanwen Cao; Chengzhi Su; Chenyu Yang

doi:10.1117/12.2680946

23 May 2023 Research on neural network modeling of thermal power unit load system

Zhongzhou Dou, Ruicai Si, Xing Cao, Jinfeng Zhao, Yingying Yao, Hang Wang, Hanwen Cao, Chengzhi Su, Chenyu Yang

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126452A (2023) https://doi.org/10.1117/12.2680946
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Based on the problem that traditional modeling is difficult to meet the predictive control of high parameters and large capacity units and to achieve the expected control effect, this paper uses BP neural network to establish a dynamic model of 600 MW supercritical once through boiler unit and concludes that neural network can effectively improve the coordination, prediction and optimization of supercritical units, and also can improve the economy and safety of supercritical units.

Citation Download Citation

Zhongzhou Dou, Ruicai Si, Xing Cao, Jinfeng Zhao, Yingying Yao, Hang Wang, Hanwen Cao, Chengzhi Su, and Chenyu Yang "Research on neural network modeling of thermal power unit load system", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126452A (23 May 2023); https://doi.org/10.1117/12.2680946

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