Forecasting of Solar and Wind Resources for Power Generation

M. K. Islam, N. M. S. Hassan (), M. G. Rasul, Kianoush Emami and Ashfaque Ahmed Chowdhury
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M. K. Islam: School of Engineering and Technology, Central Queensland University, Abbott Street, Cairns, QLD 4870, Australia
N. M. S. Hassan: School of Engineering and Technology, Central Queensland University, Abbott Street, Cairns, QLD 4870, Australia
M. G. Rasul: School of Engineering and Technology, Central Queensland University, Yaamba Rd., Rockhampton, QLD 4701, Australia
Kianoush Emami: School of Engineering and Technology, Central Queensland University, Abbott Street, Cairns, QLD 4870, Australia
Ashfaque Ahmed Chowdhury: School of Engineering and Technology, Central Queensland University, Bryan Jordan Dr., Gladstone, QLD 4680, Australia

Energies, 2023, vol. 16, issue 17, 1-23

Abstract: Solar and wind are now the fastest-growing power generation resources, being ecologically benign and economical. Solar and wind forecasts are significantly noteworthy for their accurate evaluation of renewable power generation and, eventually, their ability to provide profit to the power generation industry, power grid system and local customers. The present study has proposed a Prophet-model-based method to predict solar and wind resources in the Doomadgee area of Far North Queensland (FNQ), Australia. A SARIMA modelling approach is also implemented and compared with Prophet. The Prophet model produces comparatively less errors than SARIMA such as a root mean squared error (RMSE) of 0.284 and a mean absolute error (MAE) of 0.394 for solar, as well as a MAE of 0.427 and a RMSE of 0.527 for wind. So, it can be concluded that the Prophet model is efficient in terms of its better prediction and better fitting in comparison to SARIMA. In addition, the present study depicts how the selected region can meet energy demands using their local renewable resources, something that can potentially replace the present dirty and costly diesel power generation of the region.

Keywords: solar; wind; forecasting; prophet; SARIMA (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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