Research on Prediction Model of Line Loss Rate in Transformer District Based on LM Numerical Optimization and BP Neural Network

2018 4th International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Zhang, Yingmei^1 ; G., Yang ; X., Hao ; S., Yao

School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin

300222, China^1

关键词: BP neural network model;    BP neural networks;    Electrical equipment;    Low voltage distribution network;    Network structures;    Numerical optimization algorithms;    Numerical optimizations;    Prediction methods;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/3/032095/pdf
DOI  :  10.1088/1755-1315/252/3/032095

来源: IOP

【 摘 要 】

Due to the complex network structure of the low-voltage distribution network, the backwardness of electrical equipment and the large number of nodes, it is difficult to calculate the line loss rate accurately. The author established a simple linear loss rate prediction model with higher accuracy. Firstly, according to the actual power operation data, the typical characteristic parameters with great influence are obtained. Secondly, the K-means clustering algorithm is applied to classify each transformer district according to the different power consumption characteristics. Finally, the BP neural network model based on LM numerical optimization algorithm is designed and applied to predict line loss rate for data class of each transformer district. 1026 transformer district with complete power operation data in a region was selected as an example to verify the accuracy of the proposed prediction method, which provides data and theoretical basis for the loss reduction measures.