Open AccessCoal blending optimization for power plants with particle swarm algorithm
Author(s) -
Shuci Gao,
Bin Li
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/569/5/052059
Subject(s) - particle swarm optimization , coal , boiler (water heating) , multi swarm optimization , process engineering , algorithm , swarm behaviour , water content , computer science , mathematical optimization , environmental science , engineering , waste management , mathematics , geotechnical engineering
Optimizing coal blending strategy is important for increasing the running efficiency and lowering down the emissions of utility boilers. A model, considering price, calorific value, ash content, volatile matter content, moisture content and sulfur content of the coal, has been established using quantum-behaved particle swarm optimization algorithm. The calculation result showed that, compared with the particle swarm algorithm, the quantum particle swarm had better global search capability and astringency, the optimal coal blending ratio can be quickly searched at reasonable boiler running cost. The blending mode is in line with the actual requirements, and the algorithm has high stability.