Paper
6 February 2024 Prediction of wind farm cost based on genetic optimization algorithm
Qi Dang, Yuechao Zhang, Wei Yang, Yongli Wang, Zhonghua Zhao, Jing Qiao
Author Affiliations +
Proceedings Volume 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023); 129795F (2024) https://doi.org/10.1117/12.3015858
Event: 9th International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 2023, Guilin, China
Abstract
With the improvement of new energy utilization, wind farm development has been paid more and more attention. Based on the genetic optimization algorithm, this paper constructs the economic cost prediction model of wind farm with the goal of economic cost and power generation of wind farm and realizes the optimization of wind farm layout platform. Finally, based on the genetic optimization algorithm, the wind farm layout platform is optimized to obtain better economic cost and wind farm layout, and the distribution law of wind farm construction and operation and maintenance cost under better economic cost is summarized.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Qi Dang, Yuechao Zhang, Wei Yang, Yongli Wang, Zhonghua Zhao, and Jing Qiao "Prediction of wind farm cost based on genetic optimization algorithm", Proc. SPIE 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 129795F (6 February 2024); https://doi.org/10.1117/12.3015858
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KEYWORDS
Wind turbine technology

Mathematical optimization

Wind speed

Genetic algorithms

Genetics

Turbines

Wind energy

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