Proceedings of the
The Nineteenth International Conference on Computational Intelligence and Security (CIS 2023)
December 1 – 4, 2023, Haikou, China
An Bi-level Optimization Model and Improved Differential Evolutionary for Wind Farm Layout with Different Turbine Types
School of Mathematics and Physics, Qinghai University, Xining, China.
ABSTRACT
It is critical to select the wind turbine type and optimize the layout of the wind farm when the terrain is relatively complex. A hybrid installation strategy can be adapted to obtain higher economic efficiency. But the process is challenging. Therefore, a bi-level constrained optimization model is first established in this paper. Then, according to the characteristics of the model, an improved differential evolution (IDE) is established by designing effective evolutionary strategies. The simulation results show that the proposed algorithm has stronger convergence compared with other algorithms. Keywords: Wind farm, Bi-level optimization, Differential evolutionary, Wind turbines, Hub height.
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School of Mathematics and Physics, Qinghai University, Xining, China.
ABSTRACT
It is critical to select the wind turbine type and optimize the layout of the wind farm when the terrain is relatively complex. A hybrid installation strategy can be adapted to obtain higher economic efficiency. But the process is challenging. Therefore, a bi-level constrained optimization model is first established in this paper. Then, according to the characteristics of the model, an improved differential evolution (IDE) is established by designing effective evolutionary strategies. The simulation results show that the proposed algorithm has stronger convergence compared with other algorithms. Keywords: Wind farm, Bi-level optimization, Differential evolutionary, Wind turbines, Hub height.
Download PDF