人工神经网络和模糊技术在风能预测中的应用  

Application of Artificial Neural Network and Fuzzy Logic on Wind Power Forecast

作　　者：李洪涛 

机构地区：[1]龙源(北京)风电工程技术有限公司,北京100034

出　　处：《中国电力》2012年第8期69-73,共5页Electric Power

摘　　要：由于风力发电固有的间歇性和随机性特点,大容量风电机组直接接入高压输电网络,不仅对电网安全运营、电能质量是重大挑战,而且也严重影响了风力发电运营的经济性。在此背景下,设计了基于径向基函数和模糊技术的风能预测模型。该模型利用自组织神经网络模型进行数据分类、径向基函数网络模型进行初始预测以及模糊逻辑函数模型进行预测修正,再以数据预处理模型、数据归一化模型以及数据反归一化模型为辅助,预测目标风电机组未来72 h的发电功率。经过试验验证,证明本模型的预测精度较为理想,可以用于实际生产。Along with the rapid development of wind power industry,the installed capacity of wind turbines has increased steadily year by year.Because of the intermittence and randomness of wind energy,large wind turbines are integrated into high-voltage transmission systems,which is not only a big challenge for grid operation security and electricity quality,but also has great impact on wind power operation economics.A wind power forecast model based on radial basis function and fuzzy logic is proposed.The model uses self-organizing neural network model for data classification,radial basis function network for initial prediction and fuzzy logic for prediction correction.With the assistance of data pre-processing,normalization and anti-normalization models,the proposed model could be used to forecast the wind power generation in 72 hours in advance.Test results show that the accuracy of the proposed model is acceptable,and the model could be used in field production.

关 键 词：风能预测 人工神经网络 模糊逻辑技术 

分 类 号：TM614[电气工程—电力系统及自动化]