A generator modeling method for optimal control of absorption refrigeration system
The modeling approach of neural network helps to optimize the operation process of dispatching absorption refrigeration system in real time.In this study,a modeling method based on simple particle swarm optimization and wavelet neural network(SPSO-WNN)is proposed.The input and output structure of the model is determined through the analysis of the working principle of the generator,while the single hidden layer WNN neural network is selected as the internal structure of the model according to the complex heat transfer and mass transfer process within the generator.The number of nodes in the hidden layer of the network model is determined by the trial-and-error method of root mean square error and the determination coefficient.The Morlet wavelet function and the simple particle swarm optimization algorithm are used to improve the activation function of the hidden layer of the traditional neural network and the method of determining the parameters such as the weights,stretch factors,translation factors of the neural network.The results indicate that the proposed generator model,SPSO-WNN,compared with the traditional WNN model,the root mean square error of the two outputs is reduced by 1.36%and 1.06%respectively.The proposed model is simple and efficient,and can be used as the equality constraint in the optimal operation control strategy of the absorption refrigeration system.
万方数据
维普
