Short-Term Prediction Model for Multi-currency Exchange Using Artificial Neural Network

2020 ◽  
Author(s):  
Isha Zameer Memon ◽  
Shahnawaz Talpur ◽  
Sanam Narejo ◽  
Aisha Zahid Junejo ◽  
Engr. Fawwad Hassan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Prediction Model ◽  
Short Term ◽  
Currency Exchange ◽  
Term Prediction ◽  
Artificial Neural ◽  
Short Term Prediction

Short-Term Prediction Model for a Grid-Connected Photovoltaic System Using EMD and GABPNN

2013 ◽  
Vol 291-294 ◽  
pp. 74-82
Author(s):  
Zeng Wei Zheng ◽  
Yuan Yi Chen ◽  
Xiao Wei Zhou ◽  
Mei Mei Huo ◽  
Bo Zhao ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Prediction Model ◽  
Prediction Method ◽  
Photovoltaic System ◽  
Photovoltaic Systems ◽  
Short Term ◽  
Model Based ◽  
Term Prediction ◽  
Short Term Prediction

The integration between photovoltaic systems and tradition grid have a lot of challenges. To accurately predict is a key to solve these challenges. Due to complex, non-linear and non-stationary characteristics, it is difficult to accurately predict the power of photovoltaic systems. In this paper, a short-term prediction model based on empirical mode decomposition (EMD)and back propagation neural network(BPNN) was constructed, and use genetic algorithm as the learn algorithm of BPNN. The power data after pre-processing is decomposed into several components, then using prediction model based on BPNN and genetic algorithm to predict each component, and all the component prediction values were aggregated to obtain the ultimate predicted result. The simulation shows the purposed prediction model has higher prediction precision compare with traditional neural network prediction method and it is an effective prediction method of photovoltaic systems.

scholarly journals Very Short-Term Power Forecasting of High Concentrator Photovoltaic Power Facility by Implementing Artificial Neural Network

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3493
Author(s):  
Yaser I. Alamin ◽  
Mensah K. Anaty ◽  
José Domingo Álvarez Hervás ◽  
Khalid Bouziane ◽  
Manuel Pérez García ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Real Data ◽  
Short Term ◽  
Prediction Horizon ◽  
Ann Models ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Short Term Prediction ◽  
The University

Concentrator photovoltaic (CPV) is used to obtain cheaper and more stable renewable energy. Methods which predict the energy production of a power system under specific circumstances are highly important to reach the goal of using this system as a part of a bigger one or of making it integrated with the grid. In this paper, the development of a model to predict the energy of a High CPV (HCPV) system using an Artificial Neural Network (ANN) is described. This system is located at the University of Rabat. The performed experiments show a quick prediction with encouraging results for a very short-term prediction horizon, considering the small amount of data available. These conclusions are based on the processes of obtaining the ANN models and detailed discussion of the results, which have been validated using real data.

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