李俊卿, 胡晓东, 马阳硕, 何玉灵. 基于合作博弈和区间划分的风电机组状态评价[J]. 智慧电力, 2022, 50(1): 7-13.
引用本文: 李俊卿, 胡晓东, 马阳硕, 何玉灵. 基于合作博弈和区间划分的风电机组状态评价[J]. 智慧电力, 2022, 50(1): 7-13.
LI Jun-qing, HU Xiao-dong, MA Yang-shuo, HE Yu-ling. State Assessment of Wind Turbines Based on Cooperative Game and Interval Partition[J]. Smart Power, 2022, 50(1): 7-13.
Citation: LI Jun-qing, HU Xiao-dong, MA Yang-shuo, HE Yu-ling. State Assessment of Wind Turbines Based on Cooperative Game and Interval Partition[J]. Smart Power, 2022, 50(1): 7-13.

基于合作博弈和区间划分的风电机组状态评价

State Assessment of Wind Turbines Based on Cooperative Game and Interval Partition

  • 摘要: 风电机组状态评估需要考虑模糊性和随机性的均衡,且不同方法确定的指标权重差异较大。因此,提出了一种基于区间划分的风电机组状态评估合作博弈云模型。首先,针对固定阈值受风速和环境温度的影响较大,采用Bin方法进行区间划分。其次,对于不同方法确定的指标权重,运用合作博弈法进行融合,并采用变权公式进行修正;然后,运用黄金分割法确定评判指标与状态等级间的云映射关系。最后,采用模糊综合评判获得评估结果。通过采集河北某风电场1.5 MW风电机组的监测数据和故障记录,对该方法的有效性进行了验证。结果表明该方法更能反映出风电机组的真实运行状态。

     

    Abstract: Aiming at the problem of strong fuzziness,weak randomness and inconsistent index weights determined by different methods,the paper propose a cooperative game cloud model for the state assessment of wind turbines based on interval partition.Firstly,Bin method is used to divide the interval because the fixed threshold is affected by wind speed and ambient temperature. Then the cooperative game method is used to combine the weights of the indices determined by different methods,and the variable weight formula is used to correct them. After that,the golden section method is used to determine the cloud mapping relationship between the evaluation index and the state level. Finally,the evaluation results are obtained by comprehensive evaluation. The correctness of the method is verified by collecting the monitoring data and fault records of 1.5 MW wind turbine in Hebei wind farm. The results show that the evaluation method can more accurately reflect the true operating state of the wind turbines.

     

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