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Optimum Cable Sizing for Offshore Wind Farms Using Binary Integer Programming

delete2023-01-01
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OA
AI
I
In‐Su Bae
E
Eun-Tae Son
S
Sung-Yul Kim *
D
Dong‐Min Kim *
DOI:10.1109/ACCESS.2023.3336163delete
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摘要

摘要

En 中文
This study proposes a method for optimizing the cable sizes in the collection systems of wind turbines on offshore wind farms. Although cable size optimizations for offshore wind farms may require a high initial investment, the power losses are considerably reduced over the system lifespan, thereby justifying the high investment. The proposed method employs a simple binary integer programming model that can determine optimum cable sizes and related cable costs (installation and loss costs) with minimal inputs regarding the topology of the wind-turbine collection system. It can be employed to design the electrical infrastructure of offshore wind farms using heuristic or metaheuristic approaches, as it can automatically calculate the power flows in arcs using bus injection to branch current matrices, even if the system topology changes. Furthermore, we have introduced a method of calculating the power losses by accounting for the diverse capacities and availabilities of WTs to reflect the actual characteristics of WTs. Our method was validated at two offshore wind-farm sites in the Southwestern Sea of Korea, one 60-MW and the other 400-MW, and this study provides some simple examples and the related parameters. Owing to the optimal cable size, the proposed technique (combined with K-clustering based genetic algorithm) demonstrated cost savings in the range of 1.55%-2.21% within the wind-turbine collection system when compared with the conventional metaheuristic methods. Moreover, the cost-based topology modifications achieved cost savings in the range of 0.18%-0.66%.
Keyword:
Binary integer programming (BIP)
cable size optimization
offshore wind farm
power loss cost
wind turbines collection system

期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

K
Kangwon National University
学者数:
1.0W
论文数: 9.4K
被引数: 13
K
Keimyung University
学者数:
3.7K
论文数: 4.0K
被引数: 3.1K
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