Article citationsMore>>

Zhao, J., Guo, Z.-H., Su, Z.-Y., Zhao, Z.-Y., Xiao, X. and Liu, F. (2016) An Improved Multi-Step Forecasting Model Based on WRF Ensembles and Creative Fuzzy Systems for Wind Speed. Applied Energy, 162, 808-826.
https://doi.org/10.1016/j.apenergy.2015.10.145

has been cited by the following article:

• TITLE: Improvement of Coding for Solar Radiation Forecasting in Dili Timor Leste—A WRF Case Study

  AUTHORS: Jose Manuel Soares de Araujo

  KEYWORDS: Shortwave Radiation, Solar Radiation, Timor Leste, WRF Code Improvement

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.9 No.2, February 24, 2021

  ABSTRACT: This paper investigates the accuracy of weather research and forecasting by improving coding for solar radiation forecasting for location in Dili Timor Leste. Weather Research and Forecasting (WRF) model version 3.9.1 is used in this study for improvement purposes. The shortwave coding of WRF is used to improve in order to decrease error simulation. The importance of improving WRF coding at a specific region will reduce the bias and root mean square root when comparing to the observed data. This study uses high resolution based on the WRF modeling to stabilize the performance of forecasting. The decrease in error performance will be expected to enhance the value of renewable energy. The results show the root mean square error of the WRF default is 233 W/m2 higher compared to 205 W/m2 from the WRF improvement model. In addition, the Mean Bias Error (MBE) of the WRF default is obtained value 0.06 higher than 0.03 from the WRF improvement in rainy days. Meanwhile, on sunny days, the performance Root Mean Square Error (RMSE) of WRF default is 327 W/m2 higher than 223 W/m2 from the WRF improvement. The MBE of WRF improvement obtained 0.13 lower compared to 0.21 of WRF default coding. Finally, this study concludes that improving the shortwave code under the WRF model can decrease the error performance of the WRF simulation for local weather forecasting.