基于云理论的风电场群长期出力区间预测

Interval prediction for long-term wind power of wind farm clusters based on cloud theory

风电的不确定性给风电集群式开发和并网带来极大挑战,风电功率的点预测已很难满足电网长期灵活规划的实际需求。针对风电场群的长期风电功率区间预测问题,提出了一种基于云理论的D藤PairCopula-GARCH-t模型,用于预测风电场群的出力区间。GARCH-t模型较为准确地反映了预测误差的尖峰厚尾特性,提高了风电功率预测的精度。D藤Pair Copula模型有效地描述了风电场群之间出力的相关性。以期望、熵和超熵为数字特征的云模型预测出的风电功率区间,不仅能反映风电的随机性和模糊性,也能合理地描述两者之间的关联性,为规划人员作长期风电并网规划提供参考。

The uncertainty of wind power poses great challenges to the cluster development and grid connection of wind power.The point prediction of wind power is difficult to meet the actual need of flexible planning of the power network.Regarding to the problem of interval prediction for long-term wind power of wind farms clusters,the D-vine Pair Copula-GARCH-t model based on cloud theory is proposed to predict the output range of wind farms.The GARCH-t model can accurately reflect the leptokurtic characteristics of prediction errors and thus improve the precision of wind power prediction.Meanwhile,the D-vine Pair Copula model effectively describes the correlation between the wind power of wind farm clusters.Based on such cloud model with the digital characteristics of expectation,entropy and hyper entropy,the interval wind power can not only reflect the randomness and fuzziness,but also describe reasonably the relationship between them.The interval prediction for wind power could provide a reference for planner to do the long-term planning of wind farms.