人工神经网络
遗传算法
MATLAB语言
计算机科学
风力发电
期限(时间)
算法
功率(物理)
调度(生产过程)
人工智能
机器学习
工程类
量子力学
操作系统
电气工程
物理
运营管理
作者
Pengfei Guo,Zhiyuan Qi,Wei Huang
标识
DOI:10.1109/ccdc.2016.7531170
摘要
Wind power prediction technology is very important for scheduling of wind power farm. In order to improve the predictive accuracy of wind power, a short-term wind power prediction method based on genetic algorithm to optimize RBF neural network is proposed this paper. Genetic algorithm is used to optimize the weight, centers and widths of the hidden layer in RBF neural network. Relevant historical data is used to train the neural network on MATLAB platform. Simulation results show that the proposed method has higher prediction accuracy and less calculation time than RBF neural network. Therefore, the proposed method can be employed to predict short-term wind power.
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