# An Optimization Framework for Wind Farm Design in Complex Terrain
## 6 Conclusions  
Wind farm design in complex terrain is a crucial yet challenging task. In this work, we present an overall design optimization framework for tackling this task. This framework combines results from state-of-the-art wind resource assessment tools, such as WAsP CFD, a fast engineering wake model, and an advanced optimization algorithm, to solve the wind farm design optimization problem in complex terrain under various realistic constraints and requirements. This makes the framework a valuable tool that can be used by designers/developers who need to optimize wind farm designs in complex terrain under a real-life scenario.  
While the framework in its default setting considers maximizing the total net AEP, its modular architecture makes it easy to be extended to consider other objective function(s). More constraints, requirements, and other optimization algorithms can also be easily implemented and added.  
Other contributions of this work include: a terrain ruggedness index (TRI) to characterize the terrain feature and model constraints on the terrain ruggedness; and a fast and simple algorithm called Heuristic Fill to find good initial designs for wind farms in complex terrain, by using a deterministic process based on wind resource considerations and constraints.  
The case study of a real wind farm in complex terrain demonstrates the effectiveness of the framework and the performance of proposed algorithms. An impressive increase of net AEP (up to 2.70%) is achieved by using the framework, while respecting realistic constraints on inclusive and exclusive boundaries, minimal mean wind speed, and maximal TRI, and minimal distance constraints between turbines. In comparison with two widely used algorithms (PSO and real-coded GA) for the same wind farm without any constraints, the Random Search algorithm also shows a much better performance in terms of convergence speed and optimization results. This of course demonstrates the advantages of the developed framework and proves the usefulness for wind farm designers/developers.  
Although the wind farm design considered in the current framework concerns only the turbine layout, other design variables, such as number, hub height(s), and type(s) of turbines, foundations,  
Figure 12: Best optimized design for the wind farm without any constraints (found by Random Search with \(E_{\text{max}}=10,000\) and \(M_{\text{max}}=5000\) m in the random scenario)  
access roads, and electrical systems, also play important roles for an overall design optimization of a wind farm. Our future works will investigate these problems and extend the framework in this direction.  
[PERSON] and [PERSON] conceived and designed the study; [PERSON] wrote the code and performed the computation; [PERSON], [PERSON] and [PERSON] analyzed the results and wrote the paper.  
This research was supported by the Sino-Danish cooperative project \"Wind farm layout optimization in complex terrain\" funded by the Danish Energy Agency (EUDP J.nr. 64013-0405) and the Ministry of Science and Technology of China (No. 2014 DFG62530).  
The authors wish to give special thanks to the Danish and Chinese partners (DTU Wind Energy, EMD International A/S, North West Survey and Design Institute of Hydro China Consultant Corporation, and HoHai University) for their active collaborations.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.