唤醒
地形
粒子群优化
计算流体力学
反距离权重法
加权
计算机科学
局部最优
风力发电
数学优化
模拟
算法
工程类
数学
航空航天工程
计算机视觉
地理
医学
地图学
电气工程
多元插值
双线性插值
放射科
作者
Weicheng Hu,Qingshan Yang,Ziting Yuan,Fucheng Yang
出处
期刊:Energy
[Elsevier]
日期:2024-02-01
卷期号:288: 129745-129745
被引量:2
标识
DOI:10.1016/j.energy.2023.129745
摘要
A novel hybrid method is proposed for wind farm layout optimization in complex terrain. Firstly, an elliptical modeling method is presented with the Witoszynski-shaped transition curve in the computational fluid dynamics (CFD) simulations. Wind resources in complex terrain are estimated by combining CFD simulations with measured wind data, and an inverse distance weighting method is introduced. Then, an improved genetic algorithm (IGA) is presented to optimize the wind farm layout, which can significantly improve efficiency and avoid falling into local optima. Finally, to overcome the grid limitation of IGA, a particle swarm optimization (PSO) method is introduced for further optimization, i.e., IGA-PSO. The proposed method is used to optimize the wind farm layout in the complex terrain of Qianjiang, China. Various wake models and cost models are considered in the optimization, where wake models include Jensen, Gaussian wake model (GWM), double Gaussian wake model (DGWM) and cost models include annual energy production (AEP) and net annual value (NAV). The results show that the proposed method outperforms other three algorithms in providing a more favorable wind farm layout in complex terrain.
科研通智能强力驱动
Strongly Powered by AbleSci AI