An integrated optimization method for distributed wind farm design considering three-dimensional complex terrain

The distributed wind farm is a key electricity source in mountainous and hilly regions due to its clean, low-carbon characteristics and proximity to load centers. However, three-dimensional (3D) complex terrains introduce challenges in wind farm layout design. Existing traditional two-dimensional layout design methods are inadequate for the 3D layout design requirements of wind speed simulation, wake effect calculation and cable network optimization in complex terrain. In addition, the importance users attach to the power stability and investment feasibility makes appropriate battery energy storage system (BESS) capacity an integral part of the design of distributed wind farms. To address these issues, based on the wind speed data in complex terrain obtained by computational fluid dynamics simulations and artificial neural network predictions, this paper proposes an optimization method for the design of distributed wind farm layout and BESS capacity. Using metaheuristic and graph theory algorithms, the approach minimizes the levelized cost of energy (LCOE) and storage (LCOS). Validation on a real-world terrain shows a 5.3 % increase in power generation compared to the traditional layout design method. Moreover, by adopting a suitable combination of power curtailment and external grid supply strategy, the required BESS capacity to achieve demands is reduced, thereby lowering LCOS. The proposed method provides an efficient integrated solution for the future design of distributed wind farms in complex terrain.