基于ARIMA模型的风电场短期风速预测

目前,风力发电的并网规模越来越大,但是鉴于风力发电特有的间歇性和随机性的特点,难免会对电力系统的稳定运行和电能质量造成巨大影响,也就限制了风电的发展速度与规模。对风力发电场的风速进行中、长、短期的预测可以在一定程度上有效的解决该问题,依据风速序列的自相关性以及时序性,本文提出了一种基于时间序列分析的风电场短期风速预测ARIMA模型,重点讨论了建模的过程、模型的识别、模型的定阶和模型参数的估计。最后结合风电场实际,对比于持续法预测给出了相应的预测结果和误差分析,验证了所提出的ARIMA模型用于风电场风速预测的可行性。

Wind Speed Short-term Forecast for Wind Farms Based on ARIMA Model

s: The size of the Wind power network is growing at present. In view of the intermittent and stochastic characteristics of wind power generation, which will inevitably have a tremendous impact on the stable operation of the power system and power quality, also limits the speed and scale of the development of wind power. The long, short-term wind speed forecasts of the wind farm can be effective to solve the problem to some extent. In view of the wind speed sequence with timing and correlation, a wind speed forecast model, ARIMA, based on time series analysis, is presented. This paper focuses on the modeling process, pattern recognition, model order determination and parameter estimation. Finally, the forecast results and error analysis are given with the contrast to the continuous method forecast, the results verify the feasibility of the proposed ARIMA model for wind speed forecasting.