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| Grouping-Based Optimal Design of Collector System Topology for a Large-Scale Offshore Wind Farm by Improved Simulated Annealing |
| Ruilin Chen,Zeyu Zhang,Junxuan Hu,Lei Zhao,Chuangzhi Li,Xiaoshun Zhang,Member, IEEE |
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| Abstract: |
| During the construction of an offshore wind farm (OWF), the capital cost of the collector cable system accounts for a large proportion of the total cost. Consequently, the optimal design of the collector system topology (CST) is one of the most crucial tasks in OWF planning. However, for a large-scale OWF, the optimal design of CST is a complex integer programming problem with high-dimension variables and various constraints. Therefore, it is difficult to acquire a high-quality optimal design scheme. To address this issue, this paper proposes a new grouping-based optimal design of CST for a large-scale OWF. First, all the wind turbines are divided into multiple groups according to their geographical locations and the maximum allowed connected wind turbines by each cable. This not only reduces the optimization dimension and difficulty, but also effectively satisfies the ‘no cross’ constraint by putting the geographically closed wind turbines into the same group. Secondly, the electrical topology among different wind turbines in each group is initially generated by an improved dynamic minimum spanning tree (DMST). The division groups of the OWF are then adjusted to further reduce the capital cost by improved simulated annealing. To verify the proposed technique, comparison case studies are carried out with five algorithms on two different OWF. |
| Key words: Offshore wind farm, collector system
topology, grouping-based optimal design, meta-heuristic
algorithm, graph theory. |
| DOI：10.23919/PCMP.2023.000151 |
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| Fund:This work is jointly supported by the National Key
Research and Development Program of China (No.
2022YFF0606600), and the Fundamental Research
Funds for the Central Universities (No. N2229001). |
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