Probabilistic electrical load forecasting for buildings using Bayesian deep neural networks

2021 ◽  
pp. 103853
Author(s):  
Lei Xu ◽  
Maomao Hu ◽  
Cheng Fan
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Load Forecasting ◽  
Electrical Load ◽  
Electrical Load Forecasting

scholarly journals ELECTRICAL LOAD FORECASTING ON HIERARCHICAL LEVELS OF IPS OF UKRAINE USING LSTM NEURAL NETWORK

2021 ◽  
Vol 2021 (59) ◽  
pp. 81-85
Author(s):  
S.S. Loskutov ◽  
◽  
P.V. Shymaniuk ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Power System ◽  
Load Forecasting ◽  
Hierarchical Level ◽  
Electrical Load ◽  
Hierarchical Levels ◽  
Electrical Load Forecasting ◽  
Forecasting Errors ◽  
Integrated Power System

The scientific research presents the results of a study of one-factor forecasting of the total electrical load at three hierarchical levels of the integrated power system (IPS) of Ukraine using artificial neural networks, such as LSTM. Based on research, forecasting errors at each hierarchical level of the power system were analyzed. Methods for improving the quality and stability of forecasts were proposed. The obtained results are the basis for the study of the assessment of the accuracy of forecasting the summary electrical load in the IPS of Ukraine. Ref. 9, fig. 4, table.

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