scholarly journals Performance Improvement of Artificial Neural Network Model in Short-term Forecasting of Wind Farm Power Output

2020 ◽  
Vol 8 (3) ◽  
pp. 484-490
Author(s):  
Sergio Velazquez Medina ◽  
Ulises Portero Ajenjo
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Performance Improvement ◽  
Network Model ◽  
Neural Network Model ◽  
Power Output ◽  
Artificial Neural Network Model ◽  
Wind Farm ◽  
Short Term ◽  
Short Term Forecasting

Effects of environmental and turbine parameters on energy gains from wind farm system: Artificial neural network simulations

2019 ◽  
Vol 44 (2) ◽  
pp. 181-195
Author(s):  
Luqman K Abidoye ◽  
Ehab Bani-Hani ◽  
Mamdouh El Haj Assad ◽  
Mohammad AlShabi ◽  
Bassel Soudan ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Wind Farm ◽  
Wind Farms ◽  
Energy Gain ◽  
Artificial Neural ◽  
Energy Gains

Artificial neural network modelling has been employed to investigate the effects of various environmental and machine factors on the energy gain from wind farm systems. Numerical comparison of artificial neural network and nonlinear regression from XLSTAT showed that ANN possessed better numerical accuracy in predicting multivariate data. Several artificial neural network models are developed and tested with several structures to obtain the best prediction performance in energy gain from different wind farms in Jordan. The best performing artificial neural network model was used to predict the energy gain from wind farm based on changes in annual wind speed, turbine rotor diameter and turbine power. As a result of 20% increase in turbine power, 14.4%–31% energy gains were recorded across different wind farms. The proposed artificial neural network model was also a good predictor for energy cost resulting from specific wind farm design.

Sign in / Sign up

Export Citation Format

Share Document