Open AccessApplication of statistical process control technology in operation optimization of thermal power units
Author(s) -
Penglu Tian,
Jun Yuan,
Shaonan Zhang,
Zhichao Li,
Qing Wei
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1549/5/052045
Subject(s) - reliability (semiconductor) , statistical process control , thermal power station , process (computing) , reliability engineering , computer science , control (management) , process control , unit operation , power station , power (physics) , manufacturing engineering , process engineering , engineering , artificial intelligence , electrical engineering , quantum mechanics , chemical engineering , physics , operating system
The reliability of power plant data becomes more and more important with the development of smart power plant based on big data and artificial intelligence technology. Statistical process control technology is widely used in product production process management, but it has never been involved in thermal power. In this paper, the statistical process control technology is applied to the thermal power industry. The application results show that the statistical process control technology can not only take the calculation results as the quantitative criteria for the operation conditions of the unit, but also help to select the comprehensive optimal conditions of the unit under the specific conditions, and implement the goal of improving the management level and economic benefits of the power plant.