# A Review of Road Design for Wind Farms in China
## 2 Research on Line Selection Method Optimization
### Intelligent Road Routing Model  
[PERSON] et al. [7] established a road centerline planning network model considering the multi-dimensional and complex terrain environment of wind farms in order to meet the demand for intelligent road design for the safe transportation of fan equipment. Based on the traditional GIS routing algorithm, they proposed a method for road optimization design of wind farms with multi-dimensional terrain and fan parameter constraints. The algorithm flow of this method is shown in Figure 4. It breaks through the limitation of traditional road design, mainly relying on CAD-aided mapping technology in the overall expression of multi-dimensional space and realizes the complete expression of three-dimensional real-world information of wind farm roads.  
Figure 3: Path design on a digital topographic map.  
[PERSON] [8] and others utilized the method of road optimization design based on the multiple linear programming (LP) model. The model's algorithm flow is shown in Figure 5, which realizes the rapid construction of planar roads taking into account the construction cost of wind power projects and the road alignment design specifications in the three-dimensional GIS environment, and finally obtains the route design scheme with the best construction cost and standardized revision.  
Figure 4: Algorithm flow.  
[PERSON] [9] and others used GIS to collect, store, manage, and analyze geospatial information. Based on the intelligent route selection model of mountain wind farm road based on the improved A* algorithm (Figure 6), the road route selection was optimized according to the characteristics of mountainous areas. Finally, the intelligent route selection was realized through GIS by Python programming.  
Figure 5: LP model’s algorithm flow.  
Figure 6: Flow chart of an improved A* algorithm.  
[PERSON] et al. [10] proposed an optimal approach road route solution formula based on genetic algorithm (GA) technology for precise and fast planning of the construction process. An illustrative example was implemented in M ATLAB to verify the applicability of this formula and reduce time costs. [PERSON] et al. [11] established the extended network structure of wind power units based on vehicle-mounted GPS data and combined it with wind power operation and maintenance business scenarios using the SOM clustering method, and then used the Dijkstra algorithm to find the optimal path between units, solving the road planning problem between units in operation and maintenance of the wind farm and reducing the operation and maintenance costs. The logic of the algorithm is shown in Figure 7.  
[PERSON] [12] and other wind farm layout optimization problems based on the Jensen wake model are modeled as objective functions and constraints. Considering the influence of the wake superposition area, they are solved by the genetic algorithm and mathematical programming method. A joint automatic optimization method for road position in the wind farm field based on a software algorithm is proposed.  
Aerial surveying equipment and professional software aids improve the design only by improving the accuracy of topographic maps and reducing field operations. However, the establishment of the intelligent road route selection model can consider the local geographical environment, road level, vertical and horizontal combination, design specifications, and other aspects of comprehensive route selection. Therefore, the intelligent road route selection model is more suitable for road route selection than the two methods mentioned above.