中国电力 ›› 2013, Vol. 46 ›› Issue (2): 98-102.DOI: 10.11930/j.issn.1004-9649.2013.2.98.4

• 新能源 • 上一篇    

基于灰色-马尔可夫链的短期风速及风电功率预测

章伟, 邓院昌   

  1. 中山大学 工学院,广东 广州 510006
  • 收稿日期:2012-10-31 出版日期:2013-02-05 发布日期:2015-12-10
  • 作者简介:章伟(1988—),女,江西南昌人,硕士研究生,从事风资源评估与风速、风电功率预测方面的研究。E-mail: zhangweizd@yeah.net

Short-Term Wind Speed and Wind Power Prediction Based on the Grey-Markov Chain

ZHANG Wei, DENG Yuan-chang   

  1. School of Engineering, Sun Yat-Sen University, Guangzhou 510006, China
  • Received:2012-10-31 Online:2013-02-05 Published:2015-12-10

摘要: 风速具有较大的随机波动性,影响风电及其与之相连电网的运行稳定性,良好的风速和风电功率预测是解决风电并网问题的关键。为此,对用于风速预测的灰色模型和马尔可夫链模型进行比较分析。通过对灰色拟合值的误差转移序列进行分析及建立马尔可夫链状态转移概率矩阵,得出灰色-马尔可夫链预测模型,进而求得风速的误差预测值。并用马尔可夫链转移概率矩阵的期望值对传统马尔可夫链进行改进,得出改进型灰色-马尔可夫链模型,以此对风电功率进行直接预测,并与功率曲线模型法进行对比分析。结果表明,改进型灰色-马尔可夫链模型预测精度更高。

关键词: 风速预测, 风电功率预测, 灰色模型, 马尔可夫链模型

Abstract: Wind speed has the characteristics of large stochastic volatility, which affects the wind power and the stability of the grid connected with it. Good predictions of wind speed and wind power are the key to solve the integration problem of wind power with grid. A comparison between grey models and Markov chain models for predicting wind speed is made. The gray-Markov chain prediction model and the wind speed prediction error are obtained by analyzing the error transfer series of the fitted values with grey models and establishing Markov state transition probability matrices. The expected values of the transfer matrices are used to correct the traditional Markov chain, and the improved gray-Markov chain model can thus be obtained to predict the wind power directly. Comparing with the real power curve, the improved grey-Markov model is better in prediction accuracy.

Key words: wind speed forecasting, wind power prediction, grey model, Markov chain

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