Load forecasting for smart grid based on continuous-learning neural network

2021 ◽  
Vol 201 ◽  
pp. 107545
Author(s):  
Marcela A. da Silva ◽  
Thays Abreu ◽  
Carlos Roberto Santos-Júnior ◽  
Carlos R. Minussi
2022 ◽  
Vol 2161 (1) ◽  
pp. 012068
Author(s):  
Sthitprajna Mishra ◽  
Bibhu Prasad Ganthia ◽  
Abel Sridharan ◽  
P Rajakumar ◽  
D. Padmapriya ◽  
...  

Abstract The motivation behind the research is the requirement of error-free load prediction for the power industries in India to assist the planners for making important decisions on unit commitments, energy trading, system security & reliability and optimal reserve capacity. The objective is to produce a desktop version of personal computer based complete expert system which can be used to forecast the future load of a smart grid. Using MATLAB, we can provide adequate user interfaces in graphical user interfaces. This paper devotes study of load forecasting in smart grid, detailed study of architecture and configuration of Artificial Neural Network(ANN), Mathematical modeling and implementation of ANN using MATLAB and Detailed study of load forecasting using back propagation algorithm.


2015 ◽  
Vol 5 (4) ◽  
pp. 1756-1772 ◽  
Author(s):  
Ashfaq Ahmad ◽  
Nadeem Javaid ◽  
Nabil Alrajeh ◽  
Zahoor Khan ◽  
Umar Qasim ◽  
...  

2021 ◽  
Author(s):  
Jingyi Zhang ◽  
Wenpeng Jing ◽  
Zhaoming Lu ◽  
Yueting Wang ◽  
Xiangming Wen

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