Optimizing renewable energy site selection in rural Australia: Clustering algorithms and energy potential analysis
Summary. This study uses clustering algorithms and genetic optimization to identify the best locations for renewable energy plants across rural Australia. Researchers analyzed solar irradiance and wind speed data to find optimal sites, then simulated energy outputs using HOMER Pro software. Solar panels consistently outperformed wind turbines. While genetic K-Medoids produced the highest energy output, it came with the highest costs, revealing a trade-off between energy production and financial feasibility.
Cite this article
Rahimi, I., Li, M., Choon, J., Pamuspusan, D., Huang, Y., He, B., Cai, A., Nikoo, M. R., & Gandomi, A. H.. (2025). Optimizing renewable energy site selection in rural Australia: Clustering algorithms and energy potential analysis. Energy Conversion and Management X. https://doi.org/10.1016/j.ecmx.2024.100855
Rahimi, Iman, et al. “Optimizing renewable energy site selection in rural Australia: Clustering algorithms and energy potential analysis.” Energy Conversion and Management X, 2025. https://doi.org/10.1016/j.ecmx.2024.100855.
Rahimi, Iman, Mufei Li, James Choon, Dane Pamuspusan, Yinpeng Huang, Binzhen He, Alan Cai, Mohammad Reza Nikoo, and Amir H. Gandomi. 2025. “Optimizing renewable energy site selection in rural Australia: Clustering algorithms and energy potential analysis.” Energy Conversion and Management X. https://doi.org/10.1016/j.ecmx.2024.100855.
@article{rahimi-2025-optimizing-renewable-energy-site-selection,
title = {Optimizing renewable energy site selection in rural Australia: Clustering algorithms and energy potential analysis},
author = {Iman Rahimi and Mufei Li and James Choon and Dane Pamuspusan and Yinpeng Huang and Binzhen He and Alan Cai and Mohammad Reza Nikoo and Amir H. Gandomi},
journal = {Energy Conversion and Management X},
year = {2025},
doi = {10.1016/j.ecmx.2024.100855},
url = {https://doi.org/10.1016/j.ecmx.2024.100855}
}
TY - JOUR TI - Optimizing renewable energy site selection in rural Australia: Clustering algorithms and energy potential analysis AU - Iman Rahimi AU - Mufei Li AU - James Choon AU - Dane Pamuspusan AU - Yinpeng Huang AU - Binzhen He AU - Alan Cai AU - Mohammad Reza Nikoo AU - Amir H. Gandomi JO - Energy Conversion and Management X PY - 2025 DO - 10.1016/j.ecmx.2024.100855 UR - https://doi.org/10.1016/j.ecmx.2024.100855 ER -
Details
- DOI
- 10.1016/j.ecmx.2024.100855
- Countries
- Australia
- Regions
- Oceania
- Categories
- energy, regional-innovation-systems
- Added
- 2026-04-28