Application of Chaotic Neural Network Based on Improved Genetic Algorithm in Load Prediction
The analysis is carried out on the chaotic characteristics of the historic load data of power grid of shaanxi province to reconstruct the phase-space of the system and to calculate the largest Lyapunov index. It points out that the time series have chaotic characteristics. Thus the time series can be used on the chaotic neural network in short-term load forecasting. Improved genetic algorithm is used in neural network model to train and study the weights and thresholds,to optimize the weights of neural network,and to maximize the capacity of global optimization of genetic algorithms and the local search performance of the neural network. Then this neural network model is used on load prediction. The predictaion results show that:the method by predictive algorithm is superior than by pure BP network method. It greatly improves the prediction accuracy.