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ABSTRACT
Determination of optimal location for wind farm is a challenging task influenced by several decision criteria and factors subject to human. This case study done proposes an integrated decision support framework to investigate the spatial wind farm suitability based on F-AHP (Fuzzy-Analytical Hierarchy Process) together with Q-GIS (Quantum-Geographic Information System) tool. Firstly, spatial analysis and integration of nine-exclusion factors were included to identify the unsuitable sites. Next, F-AHP-based MCDM (Multi Criteria Decision Making) analysis was employed to obtain criteria weights of seven evaluation factors. Unlike traditional AHP method, the proposed F-AHP method is much flexible to deal with intermediate linguistic variable. F-AHP results reveal that wind speed is the most important criteria followed by power Tr. lines with weighted value of 33.05% and 20.95% respectively. The thematic suitability map was developed on Q-GIS platform to classify from “least suitable” to “most suitable” classes. The final suitable map indicates 26.09 km2 and 138.42 km2 area are most suitable and highly suitable respectively for wind farm establishment. This study is also supported with ground measurement wind resource data collected through a WMS (Weather Monitoring Station) installed at “most suitable” region of suitability indexed class.
Nomenclature
| Symbol/Short forms | = | Meaning/Units |
| Q-GIS | = | Quantum- Geographic Information System |
| TFN | = | Triangular Fuzzy Number |
| dB | = | Decibel |
| MCDM | = | Multi Criteria Decision Making |
| Tr. | = | Transmission |
| F- AHP | = | Fuzzy- Analytical Hierarchy process |
| WMS | = | Weather Monitoring Station |
| WPD | = | Wind Power Density – W/m2 |
| NIWE | = | National Institute of Wind Energy |
| LULC | = | Land Use Land Cover |
| KML | = | Keyhole Markup Language |
| WGS | = | World Geodetic System |
| GWA | = | Global Wind Atlas |
| ASTER | = | Advance Spaceborne Thermal Emission & Reflection Radiometer |
| GDEM | = | Global Digital Elevation Model |
| SRTM | = | Shuttle Radar Topography Mission |
| USGS | = | United State Geological Survey |
| LSI | = | Land Suitability Index |
| WTGs | = | Wind Turbine Generators |
| COP-26 | = | 26th Conference of Parties |
| OCED | = | Organization for Economic Co- operation and Development |
| SE1 | = | Wind speed (m/s) |
| SE2 | = | Slope (degree) |
| SE3 | = | Elevation (m) |
| SE4 | = | Distance from road networks (m) |
| SE5 | = | Distance from power Tr. Lines (m) |
| SE6 | = | Lightning strike flash rate (fl.km−1yr−2) |
| SE7 | = | Soil texture |
Acknowledgements
Authors thanks to various state government organizations i.e., Forest department (RS & GIS lab), Power Department (Treading cell, HQ & SREDA Bhawan) and Science & Technology (Vigyan Bhawan) for providing relevant data and resource to carry out this research work.
Disclosure statement
The authors declare that they have no financial interest or personal relationship that could have appeared to influence the work reported in this paper.