发电技术2025，Vol.46Issue(2)：326-335,10.DOI:10.12096/j.2096-4528.pgt.23129
低温天气下考虑风机运行状态聚类的短期风电功率预测方法
Short-Term Wind Power Prediction Method Considering Wind Turbine Operation Status Clustering Under Low-Temperature Conditions
摘要
Abstract
[Objectives]Low-temperature weather poses challenges to the operation of power systems with a high proportion of new energy,such as wind power.Improving the accuracy of short-term wind power prediction under low-temperature conditions will provide effective decision-making information for power system scheduling and operation.To address this,a wind power prediction method considering the clustering of unit operation status under low-temperature conditions is proposed.[Methods]The fuzzy C-means(FCM)clustering algorithm is used to cluster wind turbines based on their operation status and protection control information.Then,a prediction method based on support vector machine is proposed to predict whether the wind turbines are in normal operation status.The LightGBM algorithm in ensemble learning is employed to predict the power output of wind turbines under normal operation.Based on the prediction results of both operation status and power values,the overall wind power output of the wind farm is determined.Finally,a case study of a wind farm in northern Hebei is conducted to validate the effectiveness of the proposed method.[Results]By fully utilizing the characteristics of wind turbine protection control behaviors under low temperatures,the proposed method accurately predicts the critical shutdown time of wind turbines and provides the shutdown capacity.It effectively fits the variation patterns of wind power curves,which improves the prediction accuracy of the wind power to more than 90%.[Conclusion]The proposed method can provide reliable prediction information for power scheduling and control.Additionally,it can provide a reference for short-term wind power prediction under other extreme weather conditions,such as strong winds.关键词
新能源/电力系统/风电/功率预测/机组运行/模糊C均值(FCM)聚类/支持向量机/电力调度控制Key words
new energy/power system/wind power/power prediction/unit operation/fuzzy C-means(FCM)clustering/support vector machine/power scheduling and control分类
能源科技引用本文复制引用
张扬帆,李奕霖,叶林,付雪姣,王正宇,王耀函..低温天气下考虑风机运行状态聚类的短期风电功率预测方法[J].发电技术,2025,46(2):326-335,10.基金项目
华北电力科学研究院有限责任公司科技项目(KJZ2022060).Project Supported by the Science and Technology Program of North China Electric Power Research Institute Co.,Ltd.(KJZ2022060). （KJZ2022060）
