The Equivalent Model for PMSG Offshore Wind Farm Based on Clustering Algorithm

A large offshore wind farm usually consists of dozens or even hundreds of wind turbines. Due to the limitation of the simulation scale, it is necessary to develop an equivalent model of offshore wind farms for power system studies. At present, the aggregation method is widely adopted for wind farm equivalent modeling. In this paper, the topology, electrical parameters, operating conditions and individual turbine characteristics of the offshore wind farms are taken into consideration. Firstly, the output power distribution of offshore wind farm, the voltage distribution of the collector system and the fault ride-through characteristics of wind turbines are analyzed. Then, a dynamic equivalent modeling method for offshore wind farms is developed based on the fault characteristics analysis. Finally, the proposed method is validated through time-domain simulation.

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Research on reactive power compensation optimization design based on equivalent model of offshore wind farm

2014 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) ◽

10.1109/appeec.2014.7066146 ◽

2014 ◽

Cited By ~ 1

Author(s):

Li Feng ◽

Yang Ping ◽

Zheng Qunru ◽

Zhou-Shuqian ◽

Wang Qian

Keyword(s):

Optimization Design ◽

Wind Farm ◽

Reactive Power ◽

Reactive Power Compensation ◽

Offshore Wind ◽

Equivalent Model ◽

Offshore Wind Farm

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Wind Turbine Clustering Algorithm of Large Offshore Wind Farms considering Wake Effects

Mathematical Problems in Engineering ◽

10.1155/2019/6874693 ◽

2019 ◽

Vol 2019 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Binbin Zhang ◽

Jun Liu

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Clustering Algorithm ◽

Wind Farms ◽

Offshore Wind ◽

Offshore Wind Farm ◽

Wake Effect ◽

Offshore Wind Farms ◽

Power Simulation ◽

Value Decomposition

This paper proposed the SVD (singular value decomposition) clustering algorithm to cluster wind turbines into some group for a large offshore wind farm, in order to reduce the high-dimensional problem in wind farm power control and numerical simulation. Firstly, wind farm wake relationship matrixes are established considering the wake effect in an offshore wind farm, and the SVD of wake relationship matrixes is used to cluster wind turbines into some groups by the fuzzy clustering algorithm. At last, the Horns Rev offshore wind farm is analyzed to test the clustering algorithm, and the clustering result and the power simulation show the effectiveness and feasibility of the proposed clustering strategy.

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Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

10.5194/wes-2020-96 ◽

2020 ◽

Author(s):

Janna K. Seifert ◽

Martin Kraft ◽

Martin Kühn ◽

Laura J. Lukassen

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Power Output ◽

Wind Farm ◽

Clustering Algorithm ◽

Free Field ◽

Measurement Data ◽

Offshore Wind ◽

Offshore Wind Farm ◽

Output Fluctuations

Abstract. The correlation of power output fluctuations of wind turbines in free field are investigated, taking into account the challenge of varying correlation states due to variable flow and wind turbine conditions within the wind farm. Based on eight months of 1 Hz SCADA data, measured at an offshore wind farm with 80 wind turbines, the influence of different parameters on the correlation of power output fluctuations is analysed. It is found that the correlation of power output fluctuations of wind turbines depends on the location of the wind turbines within the wind farm as well as the inflow conditions (free-stream or wake). Wind direction investigations show that the correlation is highest for streamwise aligned pairs and decreases towards spanwise pairs. Most importantly, the highly variable measurement data in a free-field wind farm has considerable influence on the identification of different correlation states. To account for that, the clustering algorithm k-means is used to group wind turbine pairs with similar correlations. The main outcome is that next to the location of a wind turbine pair in the wind farm the standard deviation in their power output and their power differences are suitable parameters to describe the correlation of power output fluctuations.

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Key Issues on the Design of an Offshore Wind Farm Layout and Its Equivalent Model

Applied Sciences ◽

10.3390/app9091911 ◽

2019 ◽

Vol 9 (9) ◽

pp. 1911

Author(s):

Yuan-Kang Wu ◽

Wen-Chin Wu ◽

Jyun-Jie Zeng

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Wind Farms ◽

Offshore Wind ◽

Equivalent Model ◽

Offshore Wind Farm ◽

Wake Effect ◽

Wind Farm Layout ◽

Farm Model ◽

The Future

Offshore wind farms will have larger capacities in the future than they do today. Thus, the costs that are associated with the installation of wind turbines and the connection of power grids will be much higher, thus the location of wind turbines and the design of internal cable connections will be even more important. A large wind farm comprises of hundreds of wind turbines. Modeling each using a complex model leads to long simulation times—especially in transient response analyses. Therefore, in the future, simulations of power systems with a high wind power penetration must apply the equivalent wind-farm model to reduce the burden of calculation. This investigation examines significant issues around the optimal design of a modern offshore wind farm layout and its equivalent model. According to a review of the literature, the wake effect and its modeling, layout optimization technologies, cable connection design, and wind farm reliability, are significant issues in offshore wind farm design. This investigation will summarize these important issues and present a list of factors that strongly influence the design of an offshore wind farm.

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