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Technical Brief

A Wind Farm Optimal Control Algorithm Based on Wake Fast-Calculation Model

[+] Author and Article Information
Gu Bo

State Key Laboratory of Alternate Electrical Power System
With Renewable Energy Sources,
North China Electric Power University,
Beijing 102206, China;
School of Electric Power,
North China University of Water Resources
and Electric Power,
Zhengzhou 450011, China
e-mail: gb19820915@163.com

Liu Yongqian, Yan Jie, Li Li, Kang Shun

State Key Laboratory of Alternate Electrical Power System
With Renewable Energy Sources,
North China Electric Power University,
Beijing 102206, China

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received June 1, 2015; final manuscript received December 10, 2015; published online January 11, 2016. Assoc. Editor: Yves Gagnon.

J. Sol. Energy Eng 138(2), 024501 (Jan 11, 2016) (5 pages) Paper No: SOL-15-1163; doi: 10.1115/1.4032297 History: Received June 01, 2015; Revised December 10, 2015

A wake fast-calculation model is developed, which can calculate the wind speed distribution of wind farms accurately and efficiently under varying wind speed and wind direction. Based on the wake fast-calculation model, a wind farm optimal controlling model is established to optimize the axial induction factors of wind turbines solving by particle swarm optimization (PSO) algorithm. In this way, the overall wind farm power output can be maximized and the wake losses can be minimized. Horns Rev wind farm in Denmark is selected as the case study, and the calculation results show that the wind farm optimal control algorithm based on the wake fast-calculation model is effective.

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References

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Figures

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Fig. 1

Computational method when wind direction is in 0 ≤ β ≤ 90

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Fig. 2

Horns Rev wind farm layout

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Fig. 3

Wake wind speed distribution of the tenth row

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Fig. 4

Wake wind speed distribution of the fourth row

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Fig. 5

Wind farm optimal control process using PSO algorithm under 8.5 m/s and 222 deg

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Fig. 6

Wind farm optimal control process using PSO algorithm under 8.5 m/s and 270 deg

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Fig. 7

Wind speed comparison under 8.5 m/s and 270 deg

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