Abstract
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.
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