Optimal configuration problem identification of electrical power cable in tidal turbine farm via traveling salesman problem modeling approach

Vartdal, Johanne Tomine; Qassim, Raad Yahya; Mokliev, Børge; Udjus, Guttorm; González-Gorbeña, Eduardo

doi:10.1007/s40565-018-0472-7

Cited by 7 publications

(3 citation statements)

References 20 publications

(30 reference statements)

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“…The impedance, maximum current carrying capacity, etc., of each cable segment is determined after the cross-sectional area thereof is determined. A subset SF i is created for each branch F i to hold the number of all cable segments subordinate to this branch, and then the maximum voltage drop ∆U F,i for this branch is calculated using Equation (4) [36].…”

Section: Branch Voltage Drop Modelmentioning

confidence: 99%

Minimizing Energy Loss by Coupling Optimization of Connection Topology and Cable Cross-Section in Offshore Wind Farm

Wang

Han

et al. 2019

Applied Sciences

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The cable cross section of an offshore wind farm power system is conventionally determined on the basis of the maximum current carrying capacity. However, this criterion cannot be matched and optimized with connection topology, which may lead to a large overall resistance level in the topology, thereby causing severe energy loss. In this pursuit, the present work envisages the establishment of a coupling optimization method of connection topology and cable cross-section planning for the first time. Based on this method, the power system of a small discrete wind farm is optimized and its results are compared with the results of the traditional design methods. The results indicate that an optimal matching of connection topology and cable cross section can be achieved using the proposed method. Besides, the optimal topology obtained uses more branches, and the large cross-section cables are reasonably used on the large-current cable segments, thus dramatically reducing the energy loss and minimizing the total cost of the power system. The proposed method is very versatile and suitable for the optimization of power systems containing any number of wind turbines and substations. Moreover, it can be combined with any evolutionary algorithm.

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Section: Branch Voltage Drop Modelmentioning

confidence: 99%

Minimizing Energy Loss by Coupling Optimization of Connection Topology and Cable Cross-Section in Offshore Wind Farm

Wang

Han

et al. 2019

Applied Sciences

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“…For example, the capitalized MST and the dynamic MST were employed separately to enhance the processing power of a large number of constraints in the optimization of the topology [9,10]. Another applied graph-based model employed in the literature is the travelling salesman problem model [12,13], which obtained the optimal topology by traversing all nodes to form a collection containing multiple different shortest paths. In addition, a hop-indexed integer programming formulation to achieve the optimization of the string topology was introduced by Bauer et al [14], which replaced the graph theory method, by constructing a connection matrix combined with a random algorithm.…”

Section: Introductionmentioning

confidence: 99%

An Integration Optimization Method for Power Collection Systems of Offshore Wind Farms

Wang

Tang

et al. 2019

Energies

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The traditional power collection system design separately optimizes the connection topology and the cable cross sections, which may result in the inherent shortcoming of lacking the most economical solutions. In this pursuit, the present work envisages the development of an integrated design method for general wind farm power collection systems, which integrated the coupling random fork tree coding, union-find set loop identification, current and voltage drop calculation models, and a high performance optimization algorithm. The proposed coupling random fork tree coding, for the first time, realized the coupling code of the substation location, connection topology, and cable cross sections, providing the basis for the integration design of the power collection system. The optimization results for discrete and regular wind farms indicated that the proposed integration method achieved the best match of topology, substation location, and the cable cross sections, thus presenting the most economical scheme of the power collection system. Compared to the traditional two-step methods, the integration method used more branches while acquiring them, to maintain the lower number of wind turbines in each branch. Furthermore, it also employed large cross-section cables to reduce the energy loss caused by the impedance in the topology, thereby resulting in a slight increased cable cost; however, the total cost was minimized. The proposed method is very versatile and suitable for the optimization of power collection systems containing any number of wind turbines and substations, and can be combined with any evolutionary algorithm.

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“…Finally, Section 5 presents the conclusions. Vartdal et al (2019) indicate that the electricity cables in tidal turbine farms generate high capital expenditure. They therefore aimed to find the cheapest configuration for routing the electrical supply cables, which connect the turbines to the collection center.…”

Section: Introductionmentioning

confidence: 99%

Performance measurement of a solution for the travelling salesman problem for routing through the incorporation of service time variability

et al. 2019

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This work assessed the performance of a solution to the problem of assigning service squads, incorporating the variability of service times. The initial problem was modelled as a Travelling Salesman Problem (TSP), whose solution was obtained by the ant colony algorithm, showing the efficient route to be followed by the squad. Assessment of the performance of the solution by discrete event simulation (DES) included the travel time and added the service time. The TSP solution indicated that up to six customer visits could be carried out in an 8hour working day. Validation by DES presented a stable behavior of the variance, regardless of the number of visit sites assigned along the route.

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Optimal configuration problem identification of electrical power cable in tidal turbine farm via traveling salesman problem modeling approach

Cited by 7 publications

References 20 publications

Minimizing Energy Loss by Coupling Optimization of Connection Topology and Cable Cross-Section in Offshore Wind Farm

Minimizing Energy Loss by Coupling Optimization of Connection Topology and Cable Cross-Section in Offshore Wind Farm

An Integration Optimization Method for Power Collection Systems of Offshore Wind Farms

Performance measurement of a solution for the travelling salesman problem for routing through the incorporation of service time variability

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