A model of plate heat exchanger(PHE) for predicting the outlet temperature of cooling water is developed in this *** model combines the mechanistic model with a compensating model in parallel way to reduce the errors ...
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A model of plate heat exchanger(PHE) for predicting the outlet temperature of cooling water is developed in this *** model combines the mechanistic model with a compensating model in parallel way to reduce the errors caused by assumptions and unknown *** mechanistic model is established based on the thermal balance equation and the thermal transfer equation,furthermore,the parameters in the mechanistic model is identified by forming an optimization problem which is solved by the Differential Evolution(DE) *** compensating model is a data-driven model consisting of kernelpartialleastsquares(KPLS) algorithm,which can compensate the deviation of outputs of mechanistic model from the real *** simulation results show that the proposed model demonstrate better performance compared with the pure mechanistic model,which lays an important foundation for energy-saving optimization of PHE.
As to the nonlinear and time-varying problems of the energy consumption model, this paper proposes an adaptive hybrid modeling method. Firstly, the recursive leastsquaresalgorithm with adaptive forgetting factor bas...
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As to the nonlinear and time-varying problems of the energy consumption model, this paper proposes an adaptive hybrid modeling method. Firstly, the recursive leastsquaresalgorithm with adaptive forgetting factor based on fuzzy algorithm and recursive leastsquaresalgorithm is used to identify the simplified mechanism energy consumption model, which solves the data saturation phenomenon and the weights of the "old and new" data during the online identification process and guarantees the adaptability of the mechanism model. Secondly, because there is a deviation between the identified model and the simplified mechanism energy consumption model, the deviation compensation model of mechanism model is established through kernel partial least squares algorithm and the model updating strategy with sliding window, which is used to update the deviation compensation model, and then the adaptive hybrid model is established by combining with the mechanism model identified online and updated deviation compensation model. Finally, the effectiveness, generalization and adaptability of the model are verified by the actual operating data of a single working condition and variable working conditions. And comparing with the mechanism model and the data model, The comparison results show that the adaptive hybrid model has higher calculation accuracy with adaptation.
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