Research of Fuzzy Neural Network Load Modeling of Synthesis Ability

Peiqiang LI

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DOI:                 

Abstract

According to the difficult of electrical electron equipment load modeling, this paper put forward a kind of fuzzy neural network load modeling based on ANFIS (adaptive-network–based fuzzy interference system). The model has superiority of fuzzy inference and nerve network, which can simulate dynamic load model output accurately. Training actual data, the paper analyzed before condition parameter of neural network load model. The conclusion parameter of model has recognized by optimal strategy. The paper elaborated the forming of fuzzy subordination and rule to different constitution four groups of actual transformer substations modeling data, load model is established, fuzzy structure and parameter were obtained by any one groups of data. The model can fit other groups of data in premise of simulation permission errors. The synthesis ability of fuzzy nerve network model is confirmed in the paper, which is the key of load modeling practicality. The example indicated that the model has excellent self-description ability and convergence. Moreover it has formidable synthesis ability.

Keywords

fuzzy interference, neural network, load modeling, synthesis ability

Conflicts of Interest

The authors declare no conflicts of interest.

References