Please use this identifier to cite or link to this item:
https://hdl.handle.net/10321/5700
DC Field | Value | Language |
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dc.contributor.author | Adebiyi, Abayomi Aduragba | en_US |
dc.contributor.author | Moloi, Katleho | en_US |
dc.contributor.author | Abbey, Xander | en_US |
dc.date.accessioned | 2024-12-10T14:03:07Z | - |
dc.date.available | 2024-12-10T14:03:07Z | - |
dc.date.issued | 2024-11-28 | - |
dc.identifier.citation | Adebiyi, A.A., Moloi, K. and Abbey, X. 2024. Renewable energy site assessment with multi-criteria decision-making. Presented at: 2024 IEEE PES/IAS PowerAfrica, 1-6. doi:10.1109/PowerAfrica61624.2024.10759388 | en_US |
dc.identifier.uri | https://hdl.handle.net/10321/5700 | - |
dc.description.abstract | With global demand for renewable energy increasing, the search for suitable locations for renewable power plants has intensified. This paper presents a comprehensive site suitability assessment for solar power plants and wind farms using the Analytical Hierarchy Process (AHP) in conjunction with Geographic Information Systems (GIS). The Analytic Hierarchy Process forms the basis for the analysis of criteria while considering their relative importance, making it suitable for multi-criteria decision-making scenarios. Graphical Information Systems provide spatial analysis capabilities that enable the integration of various geographic information layers and facilitate informed decision-making. By combining AHP with GIS, this study offers a systematic approach for decision-makers and stakeholders in renewable energy industries worldwide to identify optimal locations for renewable power plants. The methodology encompasses data collection from reputable sources, extracting useful information from these sources and using them within the AHP framework, all within various Python software libraries. Through the integration of the aforementioned methodologies, this research contributes to the advancement of renewable energy site suitability assessment methodologies and supports the transition towards a more sustainable energy future. | en_US |
dc.format.extent | 6 p | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE Explore | en_US |
dc.relation.ispartof | 2024 IEEE PES/IAS PowerAfrica | en_US |
dc.subject | Renewable energy | en_US |
dc.subject | Solar power plants | en_US |
dc.subject | Wind farms | en_US |
dc.subject | Site suitability assessment | en_US |
dc.subject | Analytical Hierarchy Process | en_US |
dc.subject | Geographic Information Systems | en_US |
dc.subject | Multi-criteria decision-making | en_US |
dc.title | Renewable energy site assessment with multi-criteria decision-making | en_US |
dc.type | Conference | en_US |
dc.date.updated | 2024-12-02T14:27:21Z | - |
dc.identifier.doi | 10.1109/PowerAfrica61624.2024.10759388 | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.languageiso639-1 | en | - |
item.openairetype | Conference | - |
Appears in Collections: | Research Publications (Engineering and Built Environment) |
Files in This Item:
File | Description | Size | Format | |
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IEEE Xplore Copyright Clearance.docx | 137.36 kB | Microsoft Word XML | View/Open | |
Abbey_Adebiyi_Moloi_2024.pdf | 2.83 MB | Adobe PDF | View/Open |
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