Overall Optimization for Offshore Wind Farm Electrical System

Hou, Peng; Hu, Weihao; Chen, Cong; Chen, Zhe

doi:10.1002/we.2077

Cited by 32 publications

(31 citation statements)

References 29 publications

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“…2. The amount of wake effect is minimized, if: À the WT 12 is placed with an angle h 1 with respect to WT 11 ; the WT 13 is placed with an angle h 2 and greater than that with respect to WT 11 . This pattern continues for next columns and it is indicated in Fig.…”

Section: Case 2: With Wake Effectmentioning

confidence: 99%

“…The particle swarm optimization (PSO) [11,12] and mixed integer PSO [13] techniques are adopted to optimize the wind farm layout in terms of optimal placement allocation of WTs. Clarke and Wright savings heuristic method with vehicle routing [14], ant colony optimization (ACO) with GA [15] and capacitated MST [16] were implemented for the optimization of inter-array cable routing between WTs in OSWFs.…”

Section: Introductionmentioning

confidence: 99%

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Optimized design of collector topology for offshore wind farm based on ant colony optimization with multiple travelling salesman problem

Srikakulapu

Vinatha

2018

J. Mod. Power Syst. Clean Energy

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A layout of the offshore wind farm (OSWF) plays a vital role in its capital cost of installation. One of the major contributions in the installation cost is electrical collector system (ECS). ECS includes: submarine cables, number of wind turbines (WTs), offshore platforms etc. By considering the above mentioned problem having an optimized design of OSWF provides the better feasibility in terms of economic considerations. This paper explains the methodology for optimized designing of ECS. The proposed methodology is based on combined elitist ant colony optimization and multiple travelling salesman problem. The objective is to minimize the length of submarine cable connected between WTs and to minimize the wake loss in the wind farm in order to reduce the cost of cable and cable power loss. The methodology is applied on North Hoyle and Horns Rev OSWFs connected with 30 and 80 WTs respectively and the results are presented.

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Section: Case 2: With Wake Effectmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimized design of collector topology for offshore wind farm based on ant colony optimization with multiple travelling salesman problem

Srikakulapu

Vinatha

2018

J. Mod. Power Syst. Clean Energy

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“…Moreover, they do not capture the response of the atmospheric boundary layer as a whole, which, if the farm is large, must be considered to take place within the farm rather than downwind. However, Katic's model was widely used in wake losses estimation for wind farm optimization research as due to its simplicity and accuracy . In, a binary matrix method of wake losses calculation was proposed base on Katic's model to simplify the calculation, and the results were compared with the results obtained by WAsP (Wind Atlas Analysis and Application software); this model was also adopted for wind farm layout optimization in, and .…”

Section: Cable Losses and Wind Farm Energy Yieldmentioning

confidence: 99%

Baseline layout and design of a 0.8 GW reference wind farm in the North Sea

et al. 2017

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The paper presents a model of a reference wind farm. The model considers the wind and wave climatologies for a specific site from which two different wind farm layouts are derived. These layouts are examined through the effective wakeenhanced turbulence intensity at the hub height for a given climatology, and a simple model for the influence on capital expenditures is proposed. An electrical design is presented, the cable losses are calculated and the energy yield is determined. An operation and maintenance model is established, and the associated operating expenditure is obtained. All of the models are then summarized in terms of a levelized cost of energy using a numerical simulation tool, which allows the layouts to be compared. The data and models are freely available online for others to use and may serve as a baseline for benchmarking and allow researchers to compare and discuss their results.Throughout Europe, 74 offshore wind farms are now installed with a cumulative total installed capacity of 8 GW. 1 The most active development area in Europe is the North Sea, representing 63% of the offshore capacity. The installed offshore capacity is expected to reach 23.5 GW by 2020. 2 Reducing the cost of energy requires that new technological concepts or solutions be investigated. A common reference wind farm (RWF) is useful for quantifying the benefits of one solution over another; that is, a system-level model of a large-scale offshore installation with multi-megawatt turbines containing the relevant data and models is required to represent a wind farm and determine the associated energy costs.Offshore wind farms are complex systems affected by both the environment (e.g. wind, waves, current and seabed) and the design characteristics of the installed equipment (e.g. the turbine type, cabling and distance to shore). These aspects govern the capital and operating expenditures, which, along with the energy produced, determine the energy costs. The components of a RWF model can largely be found in the literature, and thus, the RWF can be based on well-established knowledge. The aerodynamic part includes static wakes, as discussed in, 3,4 and. 5 Added turbulence is modelled in, for instance, 6,7 and, 8 and the last reference established the draft norm in. 9 The power yield for wind farms was investigated in, 10 and commercial software tools are available for this task such as WASP. Operation and maintenance (O&M) aspects for wind farms comprise a substantial part of the costs. 11 In general, the literature has focused on the physical/technical aspects of wind farms, not on the costs involved. For example, the added turbulence in farms is modelled in, 9 but the results regarding the effects of added turbulence on cost are not readily available. 12 Considering this gap in the literature, The Norwegian Centre for Offshore Wind Energy (NORCOWE) has designed an offshore RWF, which is intended to represent the next generation of wind farms to be constructed in the North Sea. The RWF is a baseline for benchmarking and will ...

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“…Compared to land, offshore wind energy resources have many advantages, including richer reserves, higher wind energy density, smaller turbulence intensity, and more stable wind direction, which have great development potential [1]. At present, the development cost of the offshore wind farms is more than twice that of the onshore wind farms, and the expenditure for the power collection systems accounts for 15%-30% of the total investment of the project [2]. Therefore, the current research focuses on establishing more cost-effective power collection systems.…”

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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Overall Optimization for Offshore Wind Farm Electrical System

Cited by 32 publications

References 29 publications

Optimized design of collector topology for offshore wind farm based on ant colony optimization with multiple travelling salesman problem

Optimized design of collector topology for offshore wind farm based on ant colony optimization with multiple travelling salesman problem

Baseline layout and design of a 0.8 GW reference wind farm in the North Sea

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

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