Multi-task short-term reactive and active load forecasting method based on attention-LSTM model

2022 ◽  
Vol 135 ◽  
pp. 107517
Author(s):  
Jiaqi Qin ◽  
Yi Zhang ◽  
Shixiong Fan ◽  
Xiaonan Hu ◽  
Yongqiang Huang ◽  
...  
Keyword(s):  
Load Forecasting ◽  
Short Term ◽  
Active Load ◽  
Forecasting Method

A Short-Term Power Load Forecasting Method Based on BP Neural Network

2014 ◽  
Vol 494-495 ◽  
pp. 1647-1650 ◽  
Author(s):  
Ling Juan Li ◽  
Wen Huang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
High Speed ◽  
Load Forecasting ◽  
High Accuracy ◽  
Back Propagation Algorithm ◽  
Short Term ◽  
Power Load ◽  
Forecasting Method ◽  
Power Load Forecasting

Short-term power load forecasting is very important for the electric power market, and the forecasting method should have high accuracy and high speed. A three-layer BP neural network has the ability to approximate any N-dimensional continuous function with arbitrary precision. In this paper, a short-term power load forecasting method based on BP neural network is proposed. This method uses the three-layer neural network with single hidden layer as forecast model. In order to improve the training speed of BP neural network and the forecasting efficiency, this method firstly reduces the factors which affect load forecasting by using rough set theory, then takes the reduced data as input variables of the BP neural network model, and gets the forecast value by using back-propagation algorithm. The forecasting results with real data show that the proposed method has high accuracy and low complexity in short-term power load forecasting.

scholarly journals Short-term nodal load forecasting method considering redundant information

2018 ◽  
Vol 366 ◽  
pp. 012046 ◽  
Author(s):  
Si Yang ◽  
Long Zhao ◽  
Xueshan Han ◽  
Yong Wang ◽  
Wenbo Li ◽  
...  
Keyword(s):  
Load Forecasting ◽  
Redundant Information ◽  
Short Term ◽  
Forecasting Method
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