Double-sided ring topology for offshore wind fram collector system layout: a multi-cable application

Zuo, Tengjun; Zhang, Yuchen; Meng, Ke

doi:10.1049/cp.2019.0621

Cited by 2 publications

(1 citation statement)

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“…In [30], the ring topology is decomposed into a substation layer, a WT layer, and a submarine cable layer, then the FCM and GA are combined to solve this hierarchical optimization of CST [30]. In [31], the optimal location of each substation can be obtained by PSO, and the optimal connections between different WTs are acquired by a two-phase Clark and wright saving algorithm. In order to improve the solution quality, the Clark and wright saving algorithm is combined with FCM and GA to enhance the ability of clustering and searching, respectively [32].…”

Section: B Optimization Methods For Ring Topologymentioning

confidence: 99%

Grouping-Based Optimal Design of Collector System Topology for a Large-Scale Offshore Wind Farm by Improved Simulated Annealing

Chen,

Zhang,

et al. 2024

Prot. Control Mod. Power Syst.

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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. Index Terms-Offshore wind farm, collector system topology, grouping-based optimal design, meta-heuristic algorithm, graph theory. NOMENCLATURE A. Abbreviations OWFoffshore wind farm CST collector system topology DMST dynamic minimum spanning tree WT wind turbine _____________________________________

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