A review of 10 × 10 and 20 × 20 grid-type wind turbine placement problems solving by metaheuristics

Çınar, Ahmet Cevahir

doi:10.1007/s11356-022-24738-3

Cited by 2 publications

(1 citation statement)

References 51 publications

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“…Due to the high computational cost of these traditional techniques, most articles are reduced to 10x10 or 20x20 meshes. In [6], a collection of 46 articles with these characteristics is shown, many of them using algorithms based on animal behaviour (genetic algorithm, particle swarm, Harris hawk, elephant herding, cuckoo, algae), and mostly showing an artificial solution to the layout problem. All in all, the general trend is the use of meta-heuristic algorithms where the achievement of the optimum (in relation to the mathematical formulation of the problem) is not guaranteed, especially when the solution space is increased.…”

Section: Introductionmentioning

confidence: 99%

Accelerated gradient-based algorithm combined with progressive Big-Bang to optimize the layout in offshore wind farms

Gonzalez-Rodriguez,

Roldan-Fernandez,

Muñoz Díez

2023

Preprint

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A new layout optimization method for offshore wind farms is proposed to minimize power deficits due to wake effect. The main engine of the algorithm is a gradient-descent method, in which an analogy is established between power deficit and repulsive electrostatic potential energy. To achieve a maximum dispersion in the initial solution, throughout the optimization process, new turbines are included in the centre of the concession area, and quickly expand outward looking for areas with less potential, in turn pushing the previous ones. When the optimization process ends, to avoid local maximums, it enters into a process of suppression of the set of locations that cause the greatest potential (power deficit). Then, a potential map of the entire area is created and a greedy algorithm includes new turbines to complete the layout with the final number of turbines. To speed up the search process and the creation of the potential map, two simplifications have been validated and added: the spatial distribution of velocities has been converted into its equivalent with point symmetry; and, for turbines affected by multiple wakes, the power deficit has been calculated by using a linear aggregation of powers, instead of the usual linear (or quadratic) aggregation of speeds. Owing to this type of aggregation, the process is accelerated in a factor of 90.

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Section: Introductionmentioning

confidence: 99%

Accelerated gradient-based algorithm combined with progressive Big-Bang to optimize the layout in offshore wind farms

Gonzalez-Rodriguez,

Roldan-Fernandez,

Muñoz Díez

2023

Preprint

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Gradient Descent Algorithm with Greedy Repositioning Using Power Deficit Aggregation of Wakes to Accelerate the Offshore Wind Farm Layout Optimization Problem in Irregular Concession Areas

Gonzalez-Rodriguez,

Roldan-Fernandez,

Serrano-Gonzalez

et al. 2024

Applied Sciences

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Wind farm layout optimization is essential to maximize the energy production of renewable energy systems. A new layout optimization method for offshore wind farms is proposed to minimize power deficits due to the wake effect without limitation on the number of turbines, the shape, or the extension of the concession area. The main engine of the algorithm is a gradient-descent method in which throughout the optimization process, new turbines are progressively and randomly included within the concession area and quickly expand outward, looking for areas with less perturbation, in turn, pushing the previous ones. When the optimization process ends, to avoid local maxima, it enters into a process of suppression of the set of locations that cause the greatest potential (power deficit). Then, a map of potential for the entire area is created, and a greedy algorithm places new turbines to complete the layout with the final number of turbines. The overall process is completed in 25 s. To drastically speed up the search process and the creation of the potential map, a simplification has been validated and added: for turbines affected by multiple wakes, the resulting power has been calculated by using a linear aggregation of power deficits, instead of the usual linear (or quadratic) aggregation of speed deficits. Owing to this type of aggregation, an analogy is established between power deficit and repulsive non-isotropic electrostatic potential energy, which allows using the properties of conservative fields. Thanks to this, the process is 20 times faster than any other layout optimization algorithm found in the revised literature. Irregular concession areas are easily treated using Stokes’ theorem to detect outer points.

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A review of 10 × 10 and 20 × 20 grid-type wind turbine placement problems solving by metaheuristics

Cited by 2 publications

References 51 publications

Accelerated gradient-based algorithm combined with progressive Big-Bang to optimize the layout in offshore wind farms

Accelerated gradient-based algorithm combined with progressive Big-Bang to optimize the layout in offshore wind farms

Gradient Descent Algorithm with Greedy Repositioning Using Power Deficit Aggregation of Wakes to Accelerate the Offshore Wind Farm Layout Optimization Problem in Irregular Concession Areas

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