ABSTRACT
To address the problems of unclear assessment standards and incomplete assessment systems in the performance assessment of ultra-supercritical coal-fired power plants. This study utilized the running dataset from a 660 MW ultra-supercritical coal-fired power plant in Xinjiang, China. By combining the analytic hierarchy process and the entropy weight method, a system of assessment indicators was established that used three layers of criteria. A running line graph representing power plant performance and containing 149 moments was obtained, which provided a theoretical basis and optimization direction for improving the power plant. The results show that the 149 running states of the power plant performance are all at level I. The boiler running level had 143 moments (95.97%), the steam-turbine level had 135 moments (90.60%), the power consumption rate level had 148 moments (99.33%), and the environmental performance level had 143 moments (89.94%) of running states at level I.
Acknowledgement
The measurement and collection of the power plant running data in this paper were accomplished with the great support of Zenning Cheng, Zhilong Yang and Yanxun Hou from Xinjiang TBEA Tianchi Energy Co, Ltd. We would like to express our heartfelt thanks to them.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
Aopeng Cao
Aopeng Cao received the B.S. degree in Heating, Ventilation and Air Conditioning from Tianjinchengjian University, Tianjin, China, in 2019. He is currently studying toward the Master degree in Energy & Power Engineering with the School of Electrical Engineering, Xinjiang University, Urumqi 830047, China.
Xiaojing Ma
Xiaojing Ma received the B.S. degree in Energy & Power Engineering from Xi’an Jiaotong University, Xi’an, China, in 2005, the M.S. degree in Energy & Power Engineering from Xi’an Jiaotong University, Xi’an, China, in 2008 and the PH. D in Mechanical Engineering & Automation from the School of Electrical Engineering, Xinjiang University, Urumqi 830047, China, in 2016.
Zening Cheng
Zening Cheng received the B.S. degree in Energy & Power Engineering from Xi’an Jiaotong University, Xi’an, China, in 2012, the M.S. degree in Energy & Power Engineering from Xi’an Jiaotong University, Xi’an, China, in 2015 and the PH. D in Energy & Power Engineering from Xi’an Jiaotong University, Xi’an, China, in 2020.
Jiawang Zhang
Jiawang Zhang received the B.S. degree in Energy and Power Engineering from China University of Petroleum-Beijing, Beijing, China, in 2019. He is currently studying toward the Master degree in Energy and Power Engineering with the School of Electrical Engineering, Xinjiang University, Urumqi 830047, China.
Yanxun Hou
Yanxun Hou received the B.S. degree in Energy and Power Engineering from Inner Mongolia University of Technology University, Hohhot, China, in 2018.