Abstract
Thermal power unit is an energy conversion system consisting of the boiler, the turbine and their auxiliary machines respectively. It is a complicated multivariable system with strong nonlinearity, uncertainty and multivariable coupling. These characters will be more evident with the unit tending to large-capacity and high-parameter. It is expensive to build the model of the unit using conventional method. The paper presents modeling of a 1000MW ultra supercritical once-through boiler unit. Based on these field data, two different neural networks are used to model the thermal power unit. The simulation results validate the efficiency of the neural networks in modelling the ultra supercritical unit.
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