Electricity Gain via Integrated Operation of Turbine Generator and Cooling Tower Using Local Model Network

This paper presents a model-based optimization approach to determine operation mode of a set of fans in the cooling tower (CT) by considering turbine generator and CT as an integrated system. The optimization problem is formulated as to maximize the net power output, which is the result of subtracting power consumption of fans in CT from power generated by turbine generator. The operations of both units are characterized by a data-driven method, local model network, which presents a set of local models in the formats of linear equations. Stepwise variable selection is employed to identify key variables as a way of reducing the number of variables and avoiding overfitting. Satisfactory fuzzy -mean cluster is used to categorize operation data into several groups to build local models. The optimal problem is then solved by linear programming algorithm. A case study conducted in a commercial plant demonstrates that the proposed approach can increase significant net power output.

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