Forecasting of Solar and Wind Resources for Power Generation

Author:

Islam M. K.1,Hassan N. M. S.1,Rasul M. G.2,Emami Kianoush1,Chowdhury Ashfaque Ahmed3ORCID

Affiliation:

1. School of Engineering and Technology, Central Queensland University, Abbott Street, Cairns, QLD 4870, Australia

2. School of Engineering and Technology, Central Queensland University, Yaamba Rd., Rockhampton, QLD 4701, Australia

3. School of Engineering and Technology, Central Queensland University, Bryan Jordan Dr., Gladstone, QLD 4680, Australia

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.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference65 articles.

1. Bureau of Meteorology (2021, December 20). Monthly Mean Daily Global Solar Irradiation, Available online: http://www.bom.gov.au/climate/maps/averages/solar-exposure/.

2. Bureau of Meteorology (2021, June 08). Average Daily Sunshine Hours, Available online: http://www.bom.gov.au/watl/sunshine/.

3. Bureau of Meteorology (2021, February 15). Renewable Energy Atlas of Australia, Mean Wind Speed at 80 m above Ground Level, Available online: www.environment.gov.au/renewable/atlas.

4. Assessment of solar power potential in a hill state of india using remote sensing and geographic information system;Mishra;Remote Sens. Appl. Soc. Environ.,2020

5. Gis based site suitability assessment for wind and solar farms in Songkhla, Thailand;Ali;Renew. Energy,2019

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