Introduction
Proper lighting and safety equipment on roads are essential for the optimal use of roadside services and the timely, safe transportation of goods. Supplying electricity for road lighting, especially in remote and hard-to-reach areas via the power grid, involves high costs for building power transmission infrastructure. Using renewable energy enables electricity generation directly at the point of use and on a local scale. This approach reduces transmission and distribution costs and significantly lowers the environmental impact associated with fossil fuel-based electricity generation. Kermanshah province plays a key role in road transportation, yet most of its roads lack lighting systems. The province has significant wind energy potential, but wind power has not been utilized to supply electricity for road lighting. This suggests that installing small-scale wind turbines along the roads could be a promising solution. This study aims to assess the wind energy potential for powering road lighting and to prioritize the counties of Kermanshah province for installing small-scale wind turbines to supply electricity to road lighting systems.
Materials and Methods
The main steps of the study include data collection, preparation of the wind atlas, identification of locations with high wind potential, determination of effective factors and indicators for siting wind turbines, weighting of these factors and indicators, scoring counties based on them, and finally ranking the counties for installing wind turbines to supply electricity for the road lighting system using multi-criteria decision-making models. Using the wind atlas, we evaluated wind energy potential within a 3 km buffer zone around roads and identified 46 points with high wind potential. Based on these points, the counties of Kermanshah province were assessed and ranked for installing small-scale turbines to power the road lighting system. The indicators considered to determine suitable turbine locations included wind energy potential, distance from roads, traffic volume, distance from high-voltage power lines, distance from protected areas, distance from rivers and flood-prone zones, distance from faults, distance from residential areas, and land slope. Counties were scored on these indicators based on previous studies and expert opinions. A decision-making matrix was created using these scores, and indicator weights were calculated using Shannon entropy combined with expert evaluation. The SAW, TOPSIS, ELECTRE, and VIKOR methods were then applied to rank and prioritize the counties.
Results and Discussion
The energy potential of wind, with a weight of 0.360, was the most important indicator for selecting locations for wind turbine installation and road lighting systems. Traffic and distance from the road were the next most significant factors, with weights of 0.228 and 0.151, respectively. Kermanshah County had the highest wind energy potential, featuring seven high-potential sites, while Sarpole Zahab and Qasr Shirin counties each had only one suitable site, indicating lower wind potential. The top three counties in terms of wind energy potential were Kermanshah, Ravansar, and Paveh. Kermanshah County also had the highest traffic volume, carrying the greatest weight in that category. For distance from the road, Sanghar and Sahneh ranked first and second, with unscaled weights of 0.094 and 0.070, respectively, and Kermanshah ranked third with 0.047. Kermanshah County scored highest on all indicators except distance from faults and protected areas. Across all decision-making methods, Kermanshah and Sanghar consistently ranked first and second. Overall, Kermanshah, Sanghar, and Ravansar were prioritized as the top three counties for installing wind turbines to supply electricity for road lighting systems.
Conclusion
According to the wind atlas, 46 points with suitable wind potential for the road lighting system were determined. Based on multi-criteria decision-making methods, Kermanshah, Sanghar, and Ravansar counties were prioritized for installing road lighting systems powered by wind turbines.
Acknowledgement 
The authors would like to thank Shahid Chamran University of Ahvaz and its Vice Chancellor for Research and Technology for their financial support in the form of funding (SCU.AA1400.29747).