电力系统保护与控制Issue(12)：65-70,6.
短期风电功率预测误差分布研究
Research on error distribution of short-term wind power prediction
摘要
Abstract
Short-term wind power prediction is a popular issue in the research field. This paper proposes t location-scale distribution to describe the errors distribution of wind power prediction. Based on the measured data in wind power plants, autoregressive integrated moving average model and back propagation neural network are adopted to analyze the errors of two forecast models respectively, proving that the t location-scale distribution can describe effectively the frequency distribution of forecast errors, and the specific research data show that the goodness of fit of t location-scale distribution is better than that of normal distribution. Parameters of t location-scale distribution, as the indicators for judging the accuracy degree of the prediction algorithm, make it available to analyze its performance directly.关键词
风电功率预测/误差分布/带位置和尺度参数的 t 分布/差分自回归移动平均模型/BP 神经网络Key words
wind power prediction/error distribution/t location-scale distribution/ARIMA/BP neural network分类
信息技术与安全科学引用本文复制引用
..短期风电功率预测误差分布研究[J].电力系统保护与控制,2013,(12):65-70,6.基金项目
国家电网公司科技项目(2011LY226090423) （2011LY226090423）
