摘要
风速时间序列的预测对风能的可持续发展至关重要,研究出准确的风速预测算法可以提高电网的安全性,改善环境效益。根据卡尔曼滤波和广义回归神经网络(GRNN)的特点,提出一种新的混合风速预测模型以及滤波误差阈值(FET)预测的方法,可以实现长期的风速预测,具有较高的精度和可靠性。
The forecast of wind speed time series is crucial for the sustainable development of wind energy, an accurate wind speed prediction algorithm is developed to improve the security of grid and environmental benefits.The paper proposes a new hybrid wind forecasting models and filtering error threshold (FET) predicted idea based on the Kalman filter and generalized regression neural network (GRNN). The model can predict the long-term wind speed with high precision and reliability.
出处
《科技通报》
北大核心
2015年第9期183-186,共4页
Bulletin of Science and Technology
基金
山东省高等学校科技计划项目(项目编号:J12LN85
J12LN84
J14LN82)
