数据知识融合下的输电线路线损计算及异常分析

Calculation and Anomaly Analysis of Transmission Line Loss Under Data Knowledge Fusion

以数据知识融合为基础,提出了输电线路线损计算方法,并结合GBDT模型进行建模和优化。通过提取EWMA特征、时序曲线特征、线路杆塔特征,多维度地分析影响线损的因素。采用基于数据知识融合的GBDT模型,结合理论计算和实际影响因素,构建了线损计算模型。引入BOA算法优化XGBoost模型参数,提高了电网损耗计算的精度。结果表明,在负载率较小、电流互感器误差较高的状态下,输送电量、电流平均值和功率变化对异常的贡献尤为显著,同时环境因素也会对导线电阻产生影响。

Based on data knowledge fusion,a transmission line loss calculation method is proposed,and combined with GBDT model for modeling and optimization.By extracting EWMA features,time series curve features,and line tower features,analyze the factors that affect line losses from multiple dimensions.A line loss calculation model was constructed using a GBDT model based on data knowledge fusion,combined with theoretical calculations and practical influencing factors.The introduction of BOA algorithm to optimize XGBoost model parameters has improved the accuracy of power grid loss calculation.The results indicate that under low load rates and high current transformer errors,the contribution of transmitted electricity,average current,and power changes to anomalies is particularly significant,and environmental factors can also affect wire resistance.