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A high-resolution suitability index for solar farm location in complex landscapes

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  • Finn, Thomas
  • McKenzie, Paul

Abstract

The introduction of renewable energy legislation in the European Union aims to encourage development of utility-scale renewable energy sources. Site location is a key part of strategic planning for renewables such as solar energy and is hampered in complex landscapes due to high spatial heterogeneity. This heterogeneity needs to be accounted for and incorporated into decision-making processes. This study used high-resolution spatial data in a Geographic Information System (GIS) alongside Analytical Hierarchy Process (AHP) and Multi-Criteria Decision Making (MCDM) to determine the potential for large-scale solar developments using Northern Ireland as a case study. Criteria were analysed using a weighted sum overlay, with weights calculated using a pairwise comparison method. The resulting Suitability Index model defined the level of suitability for 10% of the region with 392 km2 identified as very suitable. Two potential site size criteria were then defined, based on manually mapped extents of current solar developments that identified 462 potential sites. A validation exercise identified modelled potential sites had high coincidence with existing and planned solar developments in the study area. The methodology can be applied across regions with complex landscape and settlement patterns with high accuracy and can be utilised by policymakers or renewable energy developers to efficiently target potential utility-scale solar developments.

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  • Finn, Thomas & McKenzie, Paul, 2020. "A high-resolution suitability index for solar farm location in complex landscapes," Renewable Energy, Elsevier, vol. 158(C), pages 520-533.
    • Handle: RePEc:eee:renene:v:158:y:2020:i:c:p:520-533
    DOI: 10.1016/j.renene.2020.05.121
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    5. Islam, Md. Rabiul & Aziz, Md. Tareq & Alauddin, Mohammed & Kader, Zarjes & Islam, Md. Rakibul, 2024. "Site suitability assessment for solar power plants in Bangladesh: A GIS-based analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) approach," Renewable Energy, Elsevier, vol. 220(C).
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