Applied-Information Technology in Short-Term Wind Speed Forecast Model for Wind Farms Based on Ant Colony Optimization and BP Neural Network

Qi Di Zhao; Yang Yu; Meng Meng Jia

doi:10.4028/www.scientific.net/AMM.662.259

Paper Titles

Research on the Circular Polarization Microstrip Array Antenna
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Research on the Angle Measurement Algorithm for Low-Speed Target of Radar
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The Design and Application of Information and Communication Networking Training Needs Analysis Simulation System
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Applied-Information Technology with Mutil-Agent Cooperation in Education Model Control Engineering
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Applied-Information Technology in Short-Term Wind Speed Forecast Model for Wind Farms Based on Ant Colony Optimization and BP Neural Network
p.259

Study on Content Distribute Mechanism of Cloud Storage
p.263

Self-Cooperative Network Coding in Deep Space Communications
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Applied-Information Technology and Data Processing in Determination of Subjective Weights in Multiple Attribute Decision Making
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Applied Technology with an Improved EGO Algorithm for Incremental Kriging
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 662Applied-Information Technology in Short-Term Wind...

Applied-Information Technology in Short-Term Wind Speed Forecast Model for Wind Farms Based on Ant Colony Optimization and BP Neural Network

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.

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Periodical:

Applied Mechanics and Materials (Volume 662)

Pages:

259-262

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.662.259

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Online since:

October 2014

Authors:

Qi Di Zhao, Yang Yu*, Meng Meng Jia

Keywords:

Ant Colony Optimization, BP Neural Network (BPNN), Short-Term Wind Speed Prediction, Wind Power Generation

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* - Corresponding Author

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