摘要
准确预测风电场风速是解决风能对电力系统所造成的安全、稳定运行和电能质量等问题的有效途径之一.风速的难以预测是由于它的高度随机和非线性.基于一种非参数的非线性自回归随机模型来预测风速,模型的自回归系数随模型依赖变量的变化而变化,因而它有灵活的非线性结构.数值实验和比较结果表明了这种函数系数自回归模型在风电场风速预测中的有效性.
Accurate predciton of wind speed is one of the most valuable ways to solve the problems of electricity security, stability and quality which are caused by the wind energy pro- duction for power system. The major difficulties for accurate prediction of wind speed are its high stochastictiy and noninearity. This paper predicts the wind speed using a nonlinear au- toregressive model. The autoregressive coefficients of the model vary with the state-dependent variables. Such kind of model offers a very flexible structure for nonlinear time series modeling. A simulation example and the comparsion results show that the effectiveness of the proposed approach.
出处
《数学的实践与认识》
北大核心
2017年第8期161-166,共6页
Mathematics in Practice and Theory
基金
湖南省自然科学基金(14JJ2134)
国家自然科学基金(61673155)
关键词
函数系数模型
非线性
风速预测
functional coefficient models
nonlinearity
wind speed prediction