Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy

Peng Hou, Weihao Hu, Mohsen N. Soltani, Cong Chen, Baohua Zhang, Zhe Chen

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

11 Citationer (Scopus)

Resumé

Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find the solution. In order to increase the probability of finding the global optimal solution, the adaptive parameter control strategy is utilized. Simulation results are given to verify the proposed approach and comparison is made with results obtained using other methods.
OriginalsprogEngelsk
TidsskriftI E E E Transactions on Sustainable Energy
Vol/bind8
Udgave nummer2
Sider (fra-til)638-647
Antal sider9
ISSN1949-3029
DOI
StatusUdgivet - apr. 2017

Fingerprint

Offshore wind farms
Evolutionary algorithms
Wind turbines
Particle swarm optimization (PSO)
Energy dissipation
Costs

Citer dette

@article{09dacc2047824ec09c62c5d3512022c8,
title = "Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy",
abstract = "Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find the solution. In order to increase the probability of finding the global optimal solution, the adaptive parameter control strategy is utilized. Simulation results are given to verify the proposed approach and comparison is made with results obtained using other methods.",
keywords = "Optimized power dispatch control strategy, Wake effect, Optimized placement of wind turbines, Direction of wind farm placement, Non-convex, Particle Swarm Optimization (PSO)",
author = "Peng Hou and Weihao Hu and {N. Soltani}, Mohsen and Cong Chen and Baohua Zhang and Zhe Chen",
year = "2017",
month = "4",
doi = "10.1109/TSTE.2016.2614266",
language = "English",
volume = "8",
pages = "638--647",
journal = "I E E E Transactions on Sustainable Energy",
issn = "1949-3029",
publisher = "IEEE",
number = "2",

}

Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy. / Hou, Peng; Hu, Weihao; N. Soltani, Mohsen; Chen, Cong; Zhang, Baohua; Chen, Zhe.

I: I E E E Transactions on Sustainable Energy, Bind 8, Nr. 2, 04.2017, s. 638-647.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy

AU - Hou, Peng

AU - Hu, Weihao

AU - N. Soltani, Mohsen

AU - Chen, Cong

AU - Zhang, Baohua

AU - Chen, Zhe

PY - 2017/4

Y1 - 2017/4

N2 - Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find the solution. In order to increase the probability of finding the global optimal solution, the adaptive parameter control strategy is utilized. Simulation results are given to verify the proposed approach and comparison is made with results obtained using other methods.

AB - Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find the solution. In order to increase the probability of finding the global optimal solution, the adaptive parameter control strategy is utilized. Simulation results are given to verify the proposed approach and comparison is made with results obtained using other methods.

KW - Optimized power dispatch control strategy

KW - Wake effect

KW - Optimized placement of wind turbines

KW - Direction of wind farm placement

KW - Non-convex

KW - Particle Swarm Optimization (PSO)

U2 - 10.1109/TSTE.2016.2614266

DO - 10.1109/TSTE.2016.2614266

M3 - Journal article

VL - 8

SP - 638

EP - 647

JO - I E E E Transactions on Sustainable Energy

JF - I E E E Transactions on Sustainable Energy

SN - 1949-3029

IS - 2

ER -