AUTHOR=Tan Peng , Zhu Hengyi , He Ziqian , Jin Zhiyuan , Zhang Cheng , Fang Qingyan , Chen Gang 

TITLE=Multi-Step Ahead Prediction of Reheat Steam Temperature of a 660 MW Coal-Fired Utility Boiler Using Long Short-Term Memory

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.845328

DOI=10.3389/fenrg.2022.845328

ISSN=2296-598X

ABSTRACT=With increases in the penetration of renewables in grids, there is an increasing demand for coal-fired power plants to operate flexibly. Regulation of reheat steam temperature is of great importance for the safe and efficient operation of coal-fired power plants. However, the difficulty of reheat steam temperature regulation increases largely during flexible operation due to the large delay and nonlinear properties, especially those units designed to shoulder baseload and with limited regulating strategy. A multi-step prediction model on the reheat steam temperature of a 660 MW coal-fired utility boiler was developed based on long short-term memory. The results show that the multi-step prediction model performs well. The average RMSE and MRE values of the five-step prediction results are below 0.52 ℃ and 0.07%, respectively. The correlation coefficients of the five-step predictions are all over 0.95. With a sample interval of 30 seconds, the model provides an accurate prediction of reheat steam temperature within 2.5 minutes, which could supply an important reference for the reheat steam temperature regulation.