Interval model of a wind turbine power curve - Zhou, Kai; Han, Hao; Li, Junfen; Wang, Yongjie; Tang, Wei; Han, Fei; Li, Yulei; Bi, Ruyu; Zhao, Haitao; Jiao, Lingxiao (Frontiers in Energy Research, 2023)
The wind turbine power curve model is critical to a wind turbine's power prediction and performance analysis. However, the abnormal data in the training set decreases the prediction accuracy of the trained models. This paper proposes a sample average approach-based method to construct an interval model of a wind turbine, which increases the robustness against the abnormal data and further improves the model accuracy. We compare our proposed methods with the traditional neural network-based and Bayesian neural network-based models in experimental data-based validations. Our model shows better performance in both accuracy and computational time.