Abstract

The operation of the modern electric power system is usually associated with various operational planning procedures. The power system needs to meet the specified technical performance standards and economic performance standards so as to meet the power load. A short-term load forecasting model based on adaptive neural fuzzy inference system is established. Based on Sugeno-type fuzzy neural network model, three kinds of output parameters optimization algorithm (Kaczmarz algorithm, Gradient algorithm and Kalman algorithm) are adopted. The simulation experiments results show the adaptive neural fuzzy inference system based on the Kalman method has the optimal forecasting precision on the short-term load for the power system.

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