Study on Designing for Inner Grid of Offshore Wind Farm

Shin, Je-Seok; Kim, Wook-Won; Kim, Jin-O.

doi:10.7763/jocet.2015.v3.206

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…In [27], the K-means clustering is used to group the WTs, and then MST can directly generate the topology for each group. Based on the optimization framework of K-means clustering and MST, the firefly algorithm [28] and the local search method [29] are designed to further improve the topology quality and reduce the capital cost of CST.…”

Section: ) Clustering Based Methodsmentioning

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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Section: ) Clustering Based Methodsmentioning

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.

View full text Add to dashboard Cite

show abstract

“…Reference [2] compares different power collecting methodologies in order to find optimal electrical configuration in on-shore wind farms by considering total cable length with minimum spanning tree algorithm. A similar study has been done in [3] for OWFs. However, they have only considered minimization of the total cable length, have worked on optimal interconnection configuration of OWFs by using metaheuristic methods without considering cable dimensions in the optimization problem.…”

Section: Introductionmentioning

confidence: 90%

Optimal Electrical Interconnection Configuration of Off-Shore Wind Farms

Sedighi¹,

Moradzadeh²,

Kükrer³

et al. 2015

JOCET

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Abstract-Development of large-scale Off-shore Wind Farms (OWFs) around the world has created different technical and economic challenges. Optimal configuration of the electrical interconnection of the OWFs is a key factor to minimize the investment and operational costs. This paper proposes an optimization formulation by using a Genetic Algorithm (GA) to find the optimal electrical interconnection configuration for a given OWF topology with different number of turbines. A search algorithm has been incorporated into the objective function that enumerates all feasible power flow directions from all turbines towards the power collecting hub, identifying the power flow path that minimizes the cable dimensions and thus the overall cost. The algorithm has been tested on several OWF topologies. The impact of the location of the hub has also been investigated by way of simulations. Furthermore, a comparison between single-hub and multi-hub solution has been made for multi-OWF system. The results show that multi-hub solution can be a better choice in general, especially when only the interconnection cost is compared. Index Terms-Off-shore Wind Farm (OWF), optimal interconnection configuration, Genetic Algorithm (GA), Transmission line I. INTRODUCTIONOff-shore Wind Farms (OWFs) are nowadays becoming a preferred solution over on-shore wind farms, to reduce the environmental implications in order to meet the high electrical power demand of modern societies [1]. In general, major difference between the cost of OWF and on-shore ones is the foundations cost, the cost of maintenance and electrical interconnection and transmission system to the shore.In the past years, some studies aimed to find optimal interconnection configuration by addressing different power collecting systems for on-shore and off-shore wind farms. Reference [2] compares different power collecting methodologies in order to find optimal electrical configuration in on-shore wind farms by considering total cable length with minimum spanning tree algorithm. A similar study has been done in [3] for OWFs. However, they have only considered minimization of the total cable length, have worked on optimal interconnection configuration of OWFs by using metaheuristic methods without considering cable dimensions in the optimization problem. Furthermore, the impact of the location of the power collecting hub within the farm is not investigated in most literature.Some other studies have only investigated the optimal configuration for the transmission system which brings the OWF power to the mainland, without considering the electrical interconnection of the wind turbines within the farm [7], [8].This paper aims to cover this gap in the literature by optimizing both the interconnecting cable dimensions and the interconnection configuration by using a Genetic Algorithm (GA), as well as illustrating the impact of the location of the hub on the overall cost. Including cable dimension in the fitness function, creates a nonlinear optimization problem (due to existence of a varia...

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“…Thus, these restrictions are driving even major investors in wind farms to design underwater substation pods. Regarding the design of the grid, it can be found from traditional designs such as radial [123], star [124] or ring [125] type, to complex designs based on sophisticated mathematical techniques that use different algorithms to obtain the optimal design as proposed by Shin in [126], who in a first stage uses the algorithm K-clustering algorithm to create k-groups of wind turbines within the internal grid; these, in turn, are interconnected according to different parameters such as the distance to a random center or the radial angle between the turbine and the substation. Once the groups are obtained, the MST (minimum spanning tree algorithm) is used to connect one turbine to another by the shortest path, and in the last step, a local search optimization algorithm is used to obtain the optimal point to connect to the outer grid, to minimizing the cable section [127].…”

Section: Wind Farm Connections To Grid: An Overviewmentioning

confidence: 99%

Wind Turbines Offshore Foundations and Connections to Grid

et al. 2020

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Most offshore wind farms built thus far are based on waters below 30 m deep, either using big diameter steel monopiles or a gravity base. Now, offshore windfarms are starting to be installed in deeper waters and the use of these structures—used for oil and gas like jackets and tripods—is becoming more competitive. Setting aside these calls for direct or fixed foundations, and thinking of water depths beyond 50 m, there is a completely new line of investigation focused on the usage of floating structures; TLP (tension leg platform), Spar (large deep craft cylindrical floating caisson), and semisubmersible are the most studied. We analyze these in detail at the end of this document. Nevertheless, it is foreseen that we must still wait sometime before these solutions, based on floating structures, can become truth from a commercial point of view, due to the higher cost, rather than direct or fixed foundations. In addition, it is more likely that some technical modifications in the wind turbines will have to be implemented to improve their function. Regarding wind farm connections to grid, it can be found from traditional designs such as radial, star or ring. On the other hand, for wind generator modeling, classifications can be established, modeling the wind turbine and modeling the wind farm. Finally, for the wind generator control, the main strategies are: passive stall, active stall, and pitch control; and when it is based on wind generation zone: fixed speed and variable speed. Lastly, the trend is to use strategies based on synchronous machines, as the permanent magnet synchronous generator (PMSG) and the wound rotor synchronous generator (WRSG).

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Study on Designing for Inner Grid of Offshore Wind Farm

Cited by 6 publications

References 4 publications

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

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

Optimal Electrical Interconnection Configuration of Off-Shore Wind Farms

Wind Turbines Offshore Foundations and Connections to Grid

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