Details

Autor(en) / Beteiligte

• Zhang, Lei
• Si, Feng Qi
• Ye, Ya Lan

Titel

Optimization of Condenser Vacuum Based on Neural Network and SA-BBO

Ist Teil von

• Advanced materials research, 2014, Vol.860-863, p.676-679

Ort / Verlag

Trans Tech Publications Ltd

Erscheinungsjahr

2014

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The optimization of condenser vacuum is significant to improve efficiency and save energy in the power plant. Taking a 600MW unit as the research object, the condenser vacuum optimization model was established synthetically based on neural network, simulated annealing and biogeography optimization hybrid algorithm (SA-BBO). Circulating pumps power, slight increase of turbine power as well as the market value difference between coal and electric were included in the model. The objective function of the model is to maximize the profit of the power plant. The most effective combinations of the condenser vacuum and the circulating water pump were calculated eventually in different operating conditions by using characteristic analysis of variable condenser conditions. In a certain condition, running three circulating pumps for two steam turbines instead of two pumps can make the condenser vacuum reduce 0.49kPa, and increase revenue 110.2 yuan/h.