Neural Network Load Modeling Synthesis Ability Research

In order to overcome the trouble that mechanism power load models are difficult to describe composite load characteristics of power electronics equipment,this paper put forward a kind of fuzzy neural power load model based on ANFIS(adaptive-network-based fuzzy inference system).Integrating the advantages of fuzzy inference and neural network,the model can accurately represent the output behavior of dynamic power load.Through training and optimizing the neural network with the measured field data,the authors obtained the before-condition parameters and conclusion-parameters of the model.Combining the application instance,the authors elaborated the procedure forming fuzzy subordination parameter and fuzzy rule.To verify the synthesizing ability of the model,the authors applied 4 data samples at power substation field to model dynamic power load.One of them was used to identify the model,and the others were used to test the model.The results show that the fuzzy neural network model has not only excellent self-description ability but also strong synthesizing ability.