A new ANN model for hourly solar radiation and wind speed prediction: A case study over the north & south of the Arabian Peninsula

2021 ◽  
Vol 46 ◽  
pp. 101248
Author(s):  
Bashar Shboul ◽  
Ismail AL-Arfi ◽  
Stavros Michailos ◽  
Derek Ingham ◽  
Lin Ma ◽  
...  
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Arabian Peninsula ◽  
Ann Model ◽  
Wind Speed Prediction ◽  
The North ◽  
Speed Prediction

scholarly journals Development of ANN Model for Wind Speed Prediction as a Support for Early Warning System

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ivan Marović ◽  
Ivana Sušanj ◽  
Nevenka Ožanić
Keyword(s):  
Wind Speed ◽  
Prediction Model ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Ann Model ◽  
Wind Speed Prediction ◽  
Speed Prediction ◽  
The University ◽  
The Impact

The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS) in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed), an artificial neural network (ANN) prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps Δt=1 h, Δt=3 h, and Δt=8 h. The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”

scholarly journals A Hybrid Forecasting Method for Wind Speed

2018 ◽  
Vol 232 ◽  
pp. 03013
Author(s):  
Jian Jiao
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Power ◽  
Hybrid Method ◽  
Renewable Energy Sources ◽  
Arima Model ◽  
Wind Power Generation ◽  
Ann Model ◽  
Wind Speed Prediction ◽  
Speed Prediction

Wind energy is one of the most widely used renewable energy sources. Wind power generation is uncertain because of the intermittent of wind power. To reduce the influence of wind power generation on the power system, it is necessary to forecast wind speed. This paper presents a hybrid wind speed prediction method based on Autoregressive Integrated Moving Average (ARIMA) model and Artificial Neural Network (ANN) model. In three wind speed prediction tests, the hybrid, ARIMA and ANN models are applied respectively. By analyzing the predicted results, it can be concluded that the hybrid method has better forecasting result. By analyzing the results, we can conclude that the hybrid method has better prediction effect.

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