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In this report, the details of an investigation into the eect of the low induction wind turbines on the Levelised Cost of Electricity (LCoE) in a 1GW oshore wind farm is outlined. The 10 MW INNWIND.EU conventional wind turbine and its low induction variant, the 10 MW AVATAR wind turbine, are considered in a variety of 10x10 layout configurations. The Annual Energy Production (AEP) and cost of electrical infrastructure were determined using two in-house ECN software tools, namely FarmFlow and EEFarm II. Combining this information with a generalised cost model, the LCoE from these layouts were determined. The optimum LCoE for the AVATAR wind farm was determined to be 92.15 e/MWh while for the INNWIND.EU wind farm it was 93.85 e/MWh. Although the low induction wind farm oered a marginally lower LCoE, it should not be considered as definitive due to simple nature of the cost model used. The results do indicate that the AVATAR wind farms require less space to achieve this similar cost performace, with a higher optimal wind farm power density (WFPD) of 3.7 MW/km2 compared to 3 MW/km2 for the INNWIND.EU based wind farm.
This paper presents a report of some of the activities of the International Energy Agency's (IEA) Wind TCP Task 39. By identifying best practices in an international collaboration, Task 39 hopes to provide the scientific evidence to inform improved regulations and standards, increasing the effectiveness of quiet wind turbine technology. Task 39 is divided into five separate work packages, which address the broad wind turbine noise topic in successive steps; from wind turbine noise generation (WP2), to airborne noise propagation over large distances (WP3). The assessment of wind turbine noise and its impact on humans is addressed in WP4, while WP5 is dealing with other aspects of perception and acceptance, which may be related to noise. All WPs contribute to a dedicated Work Package on dissemination (WP1). This paper provides an update of activities primarily associated with the socio-psychological aspects of wind turbine noise (WP4 and WP5). Through the consideration of a wide variety of factors, including measurement technologies, auralisation and psychology, the effects on noise perception, annoyance and its impact on wellbeing and health is being further investigated. This paper presents a discussion of the activities of each member country and highlights some of the key research questions that need to be further considered.
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Wind turbines are usually clustered in wind farms which causes the downstream turbines to operate in the turbulent wakes of upstream turbines. As turbulence is directly related to increased fatigue loads, knowledge of the turbulence in the wake and its evolution are important. Therefore, the main objective of this study is a comprehensive exploration of the turbulence evolution in the wind turbine’s wake to identify characteristic turbulence regions. For this, we present an experimental study of three model wind turbine wake scenarios that were scanned with hot-wire anemometry with a very high downstream resolution. The model wind turbine was exposed to three inflows: laminar inflow as a reference case, a central wind turbine wake, and half of the wake of an upstream turbine. A detailed turbulence analysis reveals four downstream turbulence regions by means of the mean velocity, variance, turbulence intensity, energy spectra, integral and Taylor length scales, and the Castaing parameter that indicates the intermittency, or gustiness, of turbulence. In addition, a wake core with features of homogeneous isotropic turbulence and a ring of high intermittency surrounding the wake can be identified. The results are important for turbulence modeling in wakes and optimization of wind farm wake control
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