Calculation Method of the Line Loss Rate in Transformer District Based on Neural Network with Optimized Input Variables

2020 ◽  
Author(s):  
Yijing Ren ◽  
Li Zhang ◽  
Haibo Wang ◽  
Mengwei Li
Keyword(s):  
Neural Network ◽  
Calculation Method ◽  
Loss Rate ◽  
Line Loss ◽  
Input Variables

Line Loss Rate Forecasting Based on Grey Model and Combination of Neural Network

2012 ◽  
Vol 621 ◽  
pp. 340-343 ◽  
Author(s):  
Fei Xie ◽  
Bu Xiang Zhou ◽  
Qin Zhang ◽  
Long Jiang
Keyword(s):  
Neural Network ◽  
Loss Rate ◽  
Grey Model ◽  
Combined Model ◽  
Related Factors ◽  
The Neural Network ◽  
Line Loss ◽  
Input Variables ◽  
Relationship Of ◽  
Bp Model

This thesis is mainly focusing on the research of the method for line loss rate forecast by adopting grey model combined with neural network. Firstly, GM(1,1) model can be used to analyze and calculate line loss rate change trend. The input variables of the neural network could be determined by grey relationship of related factors. Three-Layer BP model for line loss rate forecast is constructed, and then the eventual result can be obtained by using the combined model of GM(1,1) and neural network method. An example is taken to prove the precision improved for line loss rate forecast by the proposed method studied in the thesis.

Study on the Prediction of Line Loss Rate Based on the Improved RBF Neural Network

2014 ◽  
Vol 915-916 ◽  
pp. 1292-1295 ◽  
Author(s):  
Ye Ren ◽  
Xiu Ge Zhang ◽  
Xun Cheng Huang
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Loss Rate ◽  
Rbf Neural Network ◽  
Distribution Network ◽  
Voltage Distribution ◽  
Medium Voltage ◽  
Radial Basis ◽  
Line Loss

According to characteristics of medium voltage distribution network, use raw data that are easily collected to study an accurate fast and simple line loss calculation method of the medium voltage distribution network, that is the radial basis function neural network algorithm. In order to improve the power system line loss rate accuracy, the paper puts forward using alternating gradient algorithm to improve the radial basis function (RBF) neural network. The simulation results show that the algorithm is feasible.

scholarly journals Calculation method of line loss rate of photovoltaic station based on PCA-GRNN

2021 ◽  
Vol 1754 (1) ◽  
pp. 012201
Author(s):  
Yuan Li ◽  
Jing Liu ◽  
Huang Tan ◽  
Yajie Li ◽  
Xinping Diao ◽  
...  
Keyword(s):  
Calculation Method ◽  
Loss Rate ◽  
Line Loss
Sign in / Sign up

Export Citation Format

Share Document