Abstract
Theoretical line loss rate is the basic reference value of the line loss management of low-voltage grids, but it is difficult to calculate accurately because of the incomplete or abnormal line impedance and measurement parameters. The traditional algorithm will greatly reduce the number of samples that can be used for model training by discarding problematic samples, which will restrict the accuracy of model training. Therefore, an improved random forest method is proposed to calculate and analyze the theoretical line loss of low-voltage grids. According to the Influence mechanism and data samples analysis, the electrical characteristic indicator system of the theoretical line loss can be constructed, and the concept of power supply torque was proposed for the first time. Based on this, the attribute division process of decision tree model is optimized, which can improve the limitation of the high requirement of random forest on the integrity of feature data. Finally, the improved effect of the proposed method is verified by 23,754 low-voltage grids, and it has a better accuracy under the condition of missing a large number of samples.
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