Trends of offshore wind projects

Rodrigues, Sílvio; Restrepo, Carlos; Kontos, E.; Pinto, R. Teixeira; Bauer, Pavol

doi:10.1016/j.rser.2015.04.092

Cited by 198 publications

(119 citation statements)

References 33 publications

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“…In fact, circa 4% of the total capital expenditure (CAPEX) of an OWF are allocated to the development phase (see Figure 1b), in which all the components and technologies that lead to an optimized and feasible system must be assessed [13,21]. Recent OWFs occupy larger areas, which often have variable water depth and seabed conditions [22] and are situated further from shore [22], leading to more complex constraints and design challenges on the grid connection. Finally, the large number of wind turbines leads to complex collection systems, which need to be carefully assessed to achieve wind farm layouts with higher efficiencies [2].…”

Section: Figurementioning

confidence: 99%

“…Therefore, the macro siting optimization of the wind farm is out of scope. It is considered that the project location resulted from several factors that minimized environmental impacts such as bird and marine life, military activity, nature conservation, shipping and navigation, sub-sea cabling and pipelines, existing offshore industries and aviation [22].…”

Section: Optimization Goalsmentioning

confidence: 99%

“…Initial OWFs exported their energy production via medium-voltage ac (MVac) transmission systems since the transmission losses were low due to their low installed capacities (up to 100 MW) and close proximity to shore (shorter than 15 km) [22]. The need for an offshore transformer came from the high installed capacities and higher distances to shore [22].…”

Section: Transmission Cablesmentioning

confidence: 99%

“…The need for an offshore transformer came from the high installed capacities and higher distances to shore [22]. In 2002, the Danish Horns Rev 1 became the first project to make use of an offshore transformer station [10].…”

Section: Transmission Cablesmentioning

confidence: 99%

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A Multi-Objective Optimization Framework for Offshore Wind Farm Layouts and Electric Infrastructures

et al. 2016

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Current offshore wind farms (OWFs) design processes are based on a sequential approach which does not guarantee system optimality because it oversimplifies the problem by discarding important interdependencies between design aspects. This article presents a framework to integrate, automate and optimize the design of OWF layouts and the respective electrical infrastructures. The proposed framework optimizes simultaneously different goals (e.g., annual energy delivered and investment cost) which leads to efficient trade-offs during the design phase, e.g., reduction of wake losses vs collection system length. Furthermore, the proposed framework is independent of economic assumptions, meaning that no a priori values such as the interest rate or energy price, are needed. The proposed framework was applied to the Dutch Borssele areas I and II. A wide range of OWF layouts were obtained through the optimization framework. OWFs with similar energy production and investment cost as layouts designed with standard sequential strategies were obtained through the framework, meaning that the proposed framework has the capability to create different OWF layouts that would have been missed by the designers. In conclusion, the proposed multi-objective optimization framework represents a mind shift in design tools for OWFs which allows cost savings in the design and operation phases.

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Section: Figurementioning

confidence: 99%

Section: Optimization Goalsmentioning

confidence: 99%

Section: Transmission Cablesmentioning

confidence: 99%

Section: Transmission Cablesmentioning

confidence: 99%

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A Multi-Objective Optimization Framework for Offshore Wind Farm Layouts and Electric Infrastructures

et al. 2016

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“…The spacing between wind turbines commonly range from 7 RD to 11 RD, where RD represents the rotor diameter of the wind turbine [1,2]. Considering the fact that the rotor diameters of modern wind turbines commonly reach 100 m, the spacing between wind turbines seems large but it is still necessary to reduce the wake effects from upstream wind turbines on downstream ones which result in lower power and higher load [3].…”

Section: Introductionmentioning

confidence: 99%

Model Based Open-Loop Wind Farm Control Using Active Power for Power Increase and Load Reduction

Kim

Paek

2017

Applied Sciences

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Abstract:A new wind farm control algorithm that adjusts the power output of the most upstream wind turbine in a wind farm for power increase and load reduction was developed in this study. The algorithm finds power commands to individual wind turbines to maximize the total power output from the wind farm when the power command from the transmission system operator is larger than the total available power from the wind farm. To validate this wind farm control algorithm, a relatively high fidelity wind farm simulation tool developed in the previous study was modified to include a wind farm controller which consists of a wind speed estimator, a power command calculator and a simplified wind farm model. In addition, the wind turbine controller in the simulation tool was modified to include a demanded power tracking algorithm. For a virtual wind farm with three 5 MW wind turbines aligned with the wind, simulations were performed with various ambient turbulent intensities, turbine spacing, and control frequencies. It was found from the dynamic simulation using turbulent winds that the proposed wind farm control algorithm can increase the power output and decrease the tower load of the most upstream wind turbine compared with the results with the conventional wind farm control.

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