WANG Yinsong, LIU Shuang, LI Mudan, et al. Energy consumption characteristics of large axial flow fan based on neural network[J]. Thermal power generation, 2019, 48(2): 65-71.
DOI:
WANG Yinsong, LIU Shuang, LI Mudan, et al. Energy consumption characteristics of large axial flow fan based on neural network[J]. Thermal power generation, 2019, 48(2): 65-71. DOI: 10.19666/j.rlfd.201804077.
Energy consumption characteristics of large axial flow fan based on neural network
To reduce the energy consumption of thermal power units
the domestic electric power industry starts to try single-side operation of auxiliaries of large-scale thermal power units. On the basis of neural network optimization algorithm
the simulation model of large-scale axial fan of thermal power units was established in this paper and the energy consumption was also analyzed. According to the performance curves and related parameters provided by the manufacturer
the mathematical model of static performance of the large-scale axial fan was built up. Combining with the characteristics of the pipeline corresponding to the actual operation of the wind turbine
the adjustment command-air volume relationship model of the fan under adjustable regulating mode of dynamic blades was established. Moreover
the energy consumption analysis model and efficiency analysis model of the fan were also build up by using the actual operation data of the power plant. On the basis of all the above models
the energy consumption characteristics of the unit with single forced draft fan running and double-fan running were analyzed at low load. The results show that
at low load
when the air volume is lower than a certain critical value
the single-blower operation is more efficient and has lower energy consumption.