基于模糊神经网络的风速预测研究

Research on wind speed prediction based on fuzzy neural network

针对风速的不确定性给保障风力可靠性发电带来很大困难的问题,采用模糊神经网络的方法对大型风电场的风速进行预测,利用T-S模糊系统和神经网络的知识构建模糊神经网络预测模型,将风电场风电机组附近的气温、气压、空气湿度和风向等环境参数与风速预测模型的输入,对提前4小时和提前一天的风速进行预测,仿真结果表明该方法具有很高的精度。

Aiming at the uncertainty of wind speed makes troubles in ensuring the reliability of wind power generation, the fuzzy neural network methods are adopted to predict the wind speed on large wind farms. To use the knowledge of T-S fuzzy systems and neural network to construct the fuzzy neural network models. To take other parameters such as temperature, atmospheric pressure, air humidity and other environmental aspects as inputs to predict the level of wind in advanced in 4 hours and one day. The simulation results show that this method has a high precision.