Prediction Model of Main Steam Temperature of Coal-fired Power Plant Based on Phase Space Reconstruction-deep Learning
Power Generation|更新时间:2026-02-06
|
Prediction Model of Main Steam Temperature of Coal-fired Power Plant Based on Phase Space Reconstruction-deep Learning
“Experts have proposed a bidirectional gate controlled cycle unit main steam temperature prediction model based on phase space reconstruction to address the problem of difficult prediction of main steam temperature fluctuations caused by peak shaving demand of thermal power units. The model is established through screening relevant variables, determining weight coefficients, optimizing hyperparameters, and other steps. It is compared and verified with models without relevant mechanisms. The results show that the model has the highest prediction accuracy and good dynamic characteristics, providing an effective solution to the problem of predicting main steam temperature fluctuations.”
Proceedings of the CSEEVol. 45, Issue 10, Pages: 3924-3933(2025)
Xiuzhang JIN, Dayong ZHAO, Shushan ZHAO, et al. Prediction Model of Main Steam Temperature of Coal-fired Power Plant Based on Phase Space Reconstruction-deep Learning[J]. Proceedings of the CSEE, 2025, 45(10): 3924-3933.
DOI:
Xiuzhang JIN, Dayong ZHAO, Shushan ZHAO, et al. Prediction Model of Main Steam Temperature of Coal-fired Power Plant Based on Phase Space Reconstruction-deep Learning[J]. Proceedings of the CSEE, 2025, 45(10): 3924-3933. DOI: 10.13334/j.0258-8013.pcsee.232617.
Prediction Model of Main Steam Temperature of Coal-fired Power Plant Based on Phase Space Reconstruction-deep Learning