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The limited resources of land and wind have increased the requirement for better designing of wind farm layouts in the wind industry. A three-dimensional layout of wind turbines (WTs) is proposed in this paper to optimize the horizontal and vertical layouts of wind farms. The issue of optimization is a highly challenging task as it involves many variables and requires handling conflicting criteria. Classical optimization algorithms cannot handle this problem due to discontinuity and nonlinear behavior. Considering this, a metaheuristic algorithm called improved electric charged particle optimization (ECPO) is developed and implemented in four different shapes and cases studies. All the scenarios implemented have the same wind distribution and obstacles. The result shows that ECPO achieves better performance in the case study when the maximum number of a wind turbine is the same as the number of grids when compared to three well-known metaheuristic algorithms, which are binary particle swarm optimization (BPSO), genetic algorithm (GA), and artificial bee colony (ABC). By implementing the three-dimensional WFLO, the levelized cost of energy (LCOE) will increase by 7&#x0025; in the case of the optimal number of WT and 3&#x0025; in the case of the fixed number of WT.

Design of 3D Wind Farm Layout Using an Improved Electric Charge Particles Optimization With Hub-Height Variety