Adaptive Modeling and Operation Optimization for the Cold End System of Thermal Power Units based on Mechanism and Statistical Analysis

Abstract

The operation optimization for the cold end system is an efficient means to improve the economy of steam turbine units. To compensate for the inadequacy of the traditional mechanism analysis utilized in obtaining actual operating characteristics of the cold end system, the prediction model of the exhaust pressure was established on the basis of mechanism analysis combined with data from the operation process. An online adaptive updating strategy was introduced to guarantee the modeling accuracy. A discrete model of the cooling tower outlet water temperature (CTOWT) was constructed based on the operation data partitioned into different groups according to the pump operating mode change (POMC). Combining the above two models, the coupled model of the cold end system was therefore obtained. A model-based operation optimization system was then implemented for the cold end system in a coal-fired power plant. Experimental trials authenticate that the optimization suggestions provided by the system can effectively enhance the benefit of power generation.