Title :
FRS-based decision table reduction for the operation optimization of large coal-fired power units
Author :
Ang, Ning-ling W. ; Chen, De-gang ; Yang, Yong-ping ; Zhang, Ting
Author_Institution :
Key Lab. of Condition Monitoring & Control for Power Plant Equip., North China Electr. Power Univ., Beijing, China
Abstract :
Large coal-fired power unit is a complex nonlinear system with more uncertainties to describe, evaluate and optimize. It is essential and difficult to determine the optimal targets in operation optimization of power units, especially considering the boundary constraints, operation conditions and system features. Fuzzy rough set (FRS)-based decision table reduction was introduced to clean the historian operation data efficiently without information losses. The result shows that the derived energy consumption decision rules can be used to determine the optimal targets quickly and dynamically for different boundary and operation conditions. It makes significant reference and promising prospects in energy-consumption diagnosis and operation optimization of power units.
Keywords :
decision tables; fuzzy set theory; optimisation; rough set theory; steam power stations; FRS-based decision table reduction; boundary constraints; complex nonlinear system; energy consumption decision rules; energy-consumption diagnosis; fuzzy rough set-based decision table reduction; historian operation data; information losses; large coal-fired power units; operation optimization; optimal targets; power unit operation optimization; system features; Abstracts; Approximation methods; Training; Decision table reduction; Energy-consumption decision rule; FRS; Large coal-fired power units; Operation optimization; Optimal target;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1484-8
DOI :
10.1109/ICMLC.2012.6359492
