Bi-objective Layout Optimization for Multiple Wind Farms Considering Sequential Fluctuation of Wind Power Using Uniform Design

Yinghao Ma; Kaigui Xie; Yanan Zhao; Hejun Yang; Dabo Zhang

doi:10.17775/CSEEJPES.2020.03350

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Bi-objective Layout Optimization for Multiple Wind Farms Considering Sequential Fluctuation of Wind Power Using Uniform Design

Regular Papers | 更新时间：2026-10-15

- Bi-objective Layout Optimization for Multiple Wind Farms Considering Sequential Fluctuation of Wind Power Using Uniform Design
- CSEE Journal of Power and Energy Systems Vol. 8, Issue 6, Pages: 1623-1635(2022)
- 作者机构：
  
  1. Anhui Province Key Laboratory of Renewable Energy Utilization and Energy Saving, Hefei University of Technology,Hefei,China
  2. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University,Chongqing,China
  3. School of Computer Science and Technology at University of Science and Technology of China,Hefei,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2020.03350
  CLC：
- Published：01 November 2022
- 稿件说明：
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Yinghao Ma, Kaigui Xie, Yanan Zhao, et al. Bi-objective Layout Optimization for Multiple Wind Farms Considering Sequential Fluctuation of Wind Power Using Uniform Design[J]. CSEE Journal of Power and Energy Systems, 2022, 8(6): 1623-1635.
DOI：

Yinghao Ma, Kaigui Xie, Yanan Zhao, et al. Bi-objective Layout Optimization for Multiple Wind Farms Considering Sequential Fluctuation of Wind Power Using Uniform Design[J]. CSEE Journal of Power and Energy Systems, 2022, 8(6): 1623-1635. DOI： 10.17775/CSEEJPES.2020.03350.

摘要

Abstract

The fluctuation of wind power brings great challenges to the secure

stable

and cost-efficient operation of the power system. Because of the time-correlation of wind speed and the wake effect of wind turbines

the layout of wind farm has a significant impact on the wind power sequential fluctuation. In order to reduce the fluctuation of wind power and improve the operation security with lower operating cost

a bi-objective layout optimization model for multiple wind farms considering the sequential fluctuation of wind power is proposed in this paper. The goal is to determine the optimal installed capacity of wind farms and the location of wind turbines. The proposed model maximizes the energy production and minimizes the fluctuation of wind power simultaneously. To improve the accuracy of wind speed estimation and hence the power calculation

the time-shifting of wind speed between the wind tower and turbines' locations is also considered. A uniform design based two-stage genetic algorithm is developed for the solution of the proposed model. Case studies demonstrate the effectiveness of this proposed model.

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