Development of Statistical Model to Improve the Efficiency of Cogeneration System

To improve the efficiency of the cogeneration system which integrates turbine generator (TG) and cooling tower (CT), a real-time optimization algorithm based on Approach and multiple linear models of CT to determine operation mode of fans installed in CT is proposed in this paper. Firstly, based on data-driven method, statistical models of TG and CT are developed off-line using local model network. Then, the optimal outlet temperature of cooling water (Tcw, out) can be calculated by solving the optimization problem which maximizes the net power output of cogeneration system. Based on the Tcw, out, a statistical linear model which can characterize Approach of CT and give physical explanation for CT, is employed. Finally, an optimal operation table of fans is established based on the developed Approach model which including factors of different seasons. Using the optimal operation table, a real-time operation mode of fans can be achieved by only researching algorithm. Compared with previous developed optimization based on LMN, the developed method obtains 85% to 95% net power output, but there are a lot of advantages. One is that it can greatly reduce the online computational burdens, the other is that the field engineer can understand the physical meaning of operation. What's more, it can be easily implanted in the existing distributed control system (DCS).