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<p>Energy access is vital for poverty alleviation in developing countries, yet rural electrification and off-grid systems often face sustainability challenges due to conflicting criteria in project selection. This study presents a G-PESTLE-based framework for identifying the most sustainable Hybrid Renewable Energy Systems (HRES) using the Philippines’ off-grid islands as case study. The framework incorporates geographical, legal, and political dimensions alongside the triple-bottom-line approach, offering a holistic selection process. Using techno-economic simulations, attribute scores for various indicators were calculated, with Fuzzy Analytical Hierarchy Process (FAHP) determining local weights and Grey Relational Analysis (GRA) ranking islands. Key findings show larger islands favor wind turbines and biomass gasifiers, while smaller islands rely on solar PV and biomass, emphasizing the importance of resource planning and economies of scale. Cluster analysis identified patterns among viable islands, aiding strategy replication. The framework highlights HRES’s role in reducing diesel dependency, enabling sustainable electrification, and guiding policy for equitable energy transition.</p> Graphical Abstract <p></p>

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Optimal Site Selection and Clustering for Off-Grid Island Renewable Electrification Based on the G-PESTLE Framework

  • 期刊论文

  • 发表日期：

    2025年12月13日

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  • Arizeo C. Salac,
  • Michael T. Castro,
  • Michael Angelo B. Promentilla,
  • Paul Bertheau,
  • Jhud Mikhail O. Aberilla,
  • Joey D. Ocon

摘要

Energy access is vital for poverty alleviation in developing countries, yet rural electrification and off-grid systems often face sustainability challenges due to conflicting criteria in project selection. This study presents a G-PESTLE-based framework for identifying the most sustainable Hybrid Renewable Energy Systems (HRES) using the Philippines’ off-grid islands as case study. The framework incorporates geographical, legal, and political dimensions alongside the triple-bottom-line approach, offering a holistic selection process. Using techno-economic simulations, attribute scores for various indicators were calculated, with Fuzzy Analytical Hierarchy Process (FAHP) determining local weights and Grey Relational Analysis (GRA) ranking islands. Key findings show larger islands favor wind turbines and biomass gasifiers, while smaller islands rely on solar PV and biomass, emphasizing the importance of resource planning and economies of scale. Cluster analysis identified patterns among viable islands, aiding strategy replication. The framework highlights HRES’s role in reducing diesel dependency, enabling sustainable electrification, and guiding policy for equitable energy transition.

Graphical Abstract