TITLE

Applied-information Technology in Short-term Wind Speed Forecast Model for Wind Farms based on Ant Colony Optimization and BP Neural Network

AUTHOR(S)
Qidi Zhao; Yang Yu; Mengmeng Jia
PUB. DATE
September 2014
SOURCE
Applied Mechanics & Materials;2014, Issue 661-662, p259
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
To improve the short-term wind speed forecasting accuracy of wind farms, a prediction model based on back propagation (BP) neural network combining ant colony algorithm is built to predict short-term wind speed. The input variables of BP neural network predictive model are historical wind speeds, temperature, and air pressure. Ant colony algorithm is used to optimize the weights and bias of BP neural networks. Using the ant colony optimization BP neural network model to predict the future 1h wind speed, the simulation results show that the proposed method offers the advantages of high precision and fast convergence in contrast with BP neural network.
ACCESSION #
98646449

 

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