Identification of Offshore Renewable Energy Sites along the Coastal Areas of Pakistan using Geographic Information Systems and Fuzzy Analytical Hierarchy Process

• Developed a GIS–FAHP model for offshore renewable energy site selection. • Identified colocation zones for wind, solar, and tidal energy in Pakistan. • Evaluated hybrid scenarios using Overlap Efficiency and Resource Density and Efficiency gain. • Found only 7.5% of Pakistan's coast viable for tri-resource deployment. • Validated FAHP weights with consistency ratios below the 0.10 threshold. The need for sustainable energy solutions has driven global interest in offshore renewable energy, particularly in regions with untapped coastal potential. Pakistan's 1,046 km Arabian Sea coastline, with a contiguous zone covering 43,060 km², offers substantial potential for offshore wind, solar, and tidal energy. However, existing studies often overlook spatial frameworks for multi-resource colocation potential and lack spatial-performance aligned approaches. This study presents a geospatial framework integrating GIS and Fuzzy Analytical Hierarchy Process (FAHP) to identify offshore sites for co-located energy development. The model integrates environmental and technical criteria with exclusion constraints, using FAHP-derived weights to generate suitability maps. Key factors include wind speed, solar irradiance, tidal range, seabed elevation, shore distance, while restricted zones; military, ports, and submarine cables are excluded. Within the contiguous zone, high-suitability areas account for 9.5% for wind, 14.5% for solar, and 13.8% for tidal energy, while tri-resource covers 7.5%. Three dual-resource scenarios (wind–solar, wind–tidal, solar–tidal) and tri-resource configuration (wind–solar–tidal) were evaluated using overlap efficiency, efficiency gain, and resource density. Wind–solar–tidal configuration exhibits moderate performance. In contrast, Solar–tidal scenario demonstrates the most favorable outcome. Colocation suitability is concentrated in mid and eastern offshore areas, with western regions limited by weak resources convergence. The consistency ratio for all three energy resources remained well below the maximum threshold (0.10), validating the robustness of FAHP input matrices This framework advances offshore renewable planning by coupling spatial suitability with system-level performance evaluation, offering a replicable, technically validated methodology for multi-resource colocation.

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Journal
Cleaner Energy Systems
Published
2026-05-01
DOI
https://doi.org/10.1016/j.cles.2026.100256
Primary Topic
Social Acceptance of Renewable Energy
Type
article
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article

Identification of Offshore Renewable Energy Sites along the Coastal Areas of Pakistan using Geographic Information Systems and Fuzzy Analytical Hierarchy Process

Cheuk Yin Wai, Zaheer Muhammad Malik, Muhammad Sayyam Asif, Muhammad Atiq Ur Rehman Tariq et al.
Cleaner Energy Systems
Social Acceptance of Renewable Energy
article

Identification of Offshore Renewable Energy Sites along the Coastal Areas of Pakistan using Geographic Information Systems and Fuzzy Analytical Hierarchy Process

Cheuk Yin Wai, Zaheer Muhammad Malik, Muhammad Sayyam Asif, Muhammad Atiq Ur Rehman Tariq, Abdullah Nadeem
article en

Abstract

• Developed a GIS–FAHP model for offshore renewable energy site selection. • Identified colocation zones for wind, solar, and tidal energy in Pakistan. • Evaluated hybrid scenarios using Overlap Efficiency and Resource Density and Efficiency gain. • Found only 7.5% of Pakistan's coast viable for tri-resource deployment. • Validated FAHP weights with consistency ratios below the 0.10 threshold. The need for sustainable energy solutions has driven global interest in offshore renewable energy, particularly in regions with untapped coastal potential. Pakistan's 1,046 km Arabian Sea coastline, with a contiguous zone covering 43,060 km², offers substantial potential for offshore wind, solar, and tidal energy. However, existing studies often overlook spatial frameworks for multi-resource colocation potential and lack spatial-performance aligned approaches. This study presents a geospatial framework integrating GIS and Fuzzy Analytical Hierarchy Process (FAHP) to identify offshore sites for co-located energy development. The model integrates environmental and technical criteria with exclusion constraints, using FAHP-derived weights to generate suitability maps. Key factors include wind speed, solar irradiance, tidal range, seabed elevation, shore distance, while restricted zones; military, ports, and submarine cables are excluded. Within the contiguous zone, high-suitability areas account for 9.5% for wind, 14.5% for solar, and 13.8% for tidal energy, while tri-resource covers 7.5%. Three dual-resource scenarios (wind–solar, wind–tidal, solar–tidal) and tri-resource configuration (wind–solar–tidal) were evaluated using overlap efficiency, efficiency gain, and resource density. Wind–solar–tidal configuration exhibits moderate performance. In contrast, Solar–tidal scenario demonstrates the most favorable outcome. Colocation suitability is concentrated in mid and eastern offshore areas, with western regions limited by weak resources convergence. The consistency ratio for all three energy resources remained well below the maximum threshold (0.10), validating the robustness of FAHP input matrices This framework advances offshore renewable planning by coupling spatial suitability with system-level performance evaluation, offering a replicable, technically validated methodology for multi-resource colocation.

Cleaner Energy Systems
University of Engineering and Technology Lahore (PK), Charles Darwin University (AU), Victoria University (AU)
Affordable and clean energy
Openalex Percentile: Top 4%
Social Acceptance of Renewable Energy
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