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Quarterly published "Inventi Impact: Wind & Waves" publishes high quality unpublished as well as high impact pre-published research and reviews related to all the areas involving wind and waves including power generation, navigation, climate change etc.
In this paper, a stand-alone hybrid microgrid consisting of wind turbines,\nphotovoltaic (PV) arrays and storage battery banks is developed for use in\nQinghai Province, China. With the help of Software Homer and Matlab, different\nvariables such as annual average wind speed, annual average load demand,\nand annual capacity shortage are considered. The net present value is\nthen used during an entire project lifetime for the optimization solution....
This study aims to estimate the wind loads acting on a tower structure by comparing and reviewing design codes and the results of
wind tunnel tests. To this end, the modal properties of the tower were identified through short-term on-site measurements of the
Busan Tower in Korea. -e wind load acting on the tower was calculated using four design codes: KBC2009 (Korea), ASCE7-10
(USA), EUROCODE (Europe), and AIJ2004 (Japan). Additionally, force measurement tests and aeroelastic model tests were
conducted for comparison. -e results obtained indicated that the design wind velocity of each design code differed slightly,
reflecting the individual characteristics of each country. -e base shear force, base moment, and maximum displacement obtained
from each design code were similar to those obtained in the wind tunnel tests.-emagnitudes of the base moments and maximum
displacements calculated by each design code were in the order of KBC > AIJ ≈EUROCODE > ASCE7. -e overall results indicate
that each design code reasonably estimates the wind forces and the responses of the tower and also has an appropriate safety
margin. -e scatter in the predicted wind loads occurs primarily from the variations in the design wind velocity in the respective
Extreme weather events can severely affect the operation and power generation of wind farms and threaten the stability and safety
of grids with high penetration of renewable energy. Therefore, it is crucial to forecast the failure and capacity loss of wind farms
under extreme weather conditions. To this end, considering the disaster-causing mechanism of severe weather and the operational
characteristics of wind farms, this paper first uses the density-based spatial clustering of applications with noise algorithm to cluster
the units in the wind farm based on the operating characteristics affected by the weather, and uses correlation analysis methods to
extract key disaster-causing factors in extreme weather; then proposes a prediction model based on feature-weighted stacking
integration. The model adopts the stacking-integrated learning architecture to support multiple learners and performs feature
weighting according to the prediction accuracy of each learner in the base learner, thereby improving the training effect of the
meta-learner and improving the prediction accuracy of the model. The prediction model is used to predict each wind turbine group
based on the extracted key features and to predict the failure and capacity loss of the wind farm. Finally, an example analysis is
performed based on actual data from a wind farm, and the results show that the proposed prediction method can effectively predict
the operational reliability of wind farms....
This paper describes a new actively controlled multi-fan wind tunnel that generates\nnatural wind as a type of turbulence wind tunnel at a reduced cost.\nThe driving section of the wind tunnel has 100 PC cooling fans that are controlled\nby an original embedded system. The fluctuating velocity wind is successfully\ngenerated with a mean velocity of 7 m/s and two turbulent intensities\nof 2% and 3% based on Karmanâ??s power spectrum density function. The\ncase of 2% has the integral scales of 5 m, 10m and 20 m, and the case of 3%\nhas the integral scales of 3 m, 6 m and 15 m with a turbulence grid. In particular,\nthe wind with the turbulent intensity of 2% satisfies the Kolmogorovâ??s\n-5/3 multiplication rule of inertial subrange with the frequency range from\n0.01 Hz to 2.0 Hz. Consequently, the new wind tunnel can be used for studying\nengineering technology and research regarding conditions with natural\nwind....
Typhoon wind speed prediction is of great significance for it can help prevent wind farms from damages caused by frequent
typhoon disasters in coastal areas. However, most researches on wind forecast are either for meteorological application or for
normal weather. -erefore, this paper proposes a systematic method based on numerical wind field and extreme learning machine
for typhoon wind speed prediction of wind farms. -e proposed method mainly consists of three parts, IGA-YanMeng typhoon
numerical simulation model, typhoon status prediction model, and wind speed simulation model based on an extreme learning
machine. -e IGA-YanMeng typhoon numerical simulation model can greatly enrich typhoon wind speed data according to
historical typhoon parameters. -e typhoon status prediction model can predict the status of typhoons studied in the next few
hours. And wind speed simulation model simulates the average wind speed magnitude/direction at 10m height of each turbine in
the farm according to the predicted status. -e end of this paper presents a case study on a wind farm located in Guangdong
province that suffered from the super typhoon Mangkhut landed in 2018. -e results verified the feasibility and effectiveness of the
Dual-Doppler lidar is a powerful remote sensing technique that can accurately measure\nhorizontal wind speeds and enable the reconstruction of two-dimensional wind fields based on\nmeasurements from two separate lidars. Previous research has provided a framework of dual-Doppler\nalgorithms for processing both radar and lidar measurements, but their application to wake\nmeasurements has not been addressed in detail yet. The objective of this paper is to reconstruct\ntwo-dimensional wind fields of wind turbine wakes and assess the performance of dual-Doppler lidar\nscanning strategies, using the newly developed Multiple-Lidar Wind Field Evaluation Algorithm\n(MuLiWEA). This processes non-synchronous dual-Doppler lidar measurements and solves the\nhorizontal wind field with a set of linear equations, also considering the mass continuity equation.\nMuLiWEA was applied on simulated measurements of a simulated wind turbine wake, with two\ntypical dual-Doppler lidar measurement scenarios. The results showed inaccuracies caused by the\ninhomogeneous spatial distribution of the measurements in all directions, related to the ground-based\nscanning of a wind field at wind turbine hub height. Additionally, MuLiWEA was applied on a\nreal dual-Doppler lidar measurement scenario in the German offshore wind farm Ã¢â?¬Å?alpha ventusÃ¢â?¬Â.\nIt was concluded that the performance of both simulated and real lidar measurement scenarios\nin combination with MuLiWEA is promising. Although the accuracy of the reconstructed wind\nfields is compromised by the practical limitations of an offshore dual-Doppler lidar measurement\nsetup, the performance shows sufficient accuracy to serve as a basis for 10 min average steady wake\nmodel validation....
By the increase of the penetration of power-electronic-based (PE-based) units, such as\nwind turbines and PV systems, many features of those power systems, such as stability, security,\nand protection, have been changed. In this paper, the security of electrical grids with high wind\nturbines penetration is discussed. To do so, first, an overview of the power systemsâ?? security\nassessment is presented. Based on that, stability and security challenges introduced by increasing\nthe penetration of wind turbines in power systems are studied, and a new guideline for the security\nassessment of the PE-based power systems is proposed. Simulation results for the IEEE 39-bus test\nsystem show that the proposed security guideline is necessary for PE-based power systems, as the\nconventional security assessments may not be able to indicate its security status properly....
A novel and robust active disturbance rejection control (ADRC) strategy for variable speed wind turbine systems using a doubly\nfed induction generator (DFIG) is presented in this paper. The DFIG is directly connected to the main utility grid by stator, and its\nrotor is connected through a back-to-back three phase power converter (AC/DC/AC).............................
Wave energy converters (WECs) usually require reactive power for increased levels of
energy conversion, resulting in the need for more complex power take-off (PTO) units, compared to
WECs that do not require reactive power. A WEC without reactive power produces much less energy,
though. The concept of Variable Shape BuoyWave Energy Converters (VSB WECs) is proposed to
allow continuous shape-change aiming at eliminating the need for reactive power, while converting
power at a high level. The proposed concept involves complex and nonlinear interactions between the
device and the waves. This paper presents a Computational Fluid Dynamics (CFD) tool that is set up
to simulate VSB WECs, using the ANSYS 2-way fluid–structure interaction (FSI) tool. The dynamic
behavior of a VSB WEC is simulated in this CFD-based Numerical Wave Tank (CNWT), in open sea
conditions. The simulation results show that the tested device undergoes a significant deformation
in response to the incoming waves, before it reaches a steady-state behavior. This is in agreement
with a low-fidelity dynamic model developed in earlier work. The resulting motion is significantly
different from the motion of a rigid body WEC. The difference in the motion can be leveraged for
better energy capture without the need for reactive power....
Wind energy in Europe is expected to grow at a steady, high pace, but opposition from
residents to local wind farm plans is one of the obstacles to further growth. A large body of evidence
shows that local populations want to be involved and respected for their concerns, but in practice,
this is a complex process that cannot be solved with simple measures, such as financial compensation.
The visual presence and the acoustic impact of a wind farm is an important concern for residents.
Generally, environmental noise management aims to reduce the exposure of the population, usually
based on acoustics and restricted to a limited number of sources (such as transportation or industry)
and sound descriptors (such as Lden). Individual perceptions are taken into account only at an
aggregate, statistical level (such as percentage of exposed, annoyed or sleep-disturbed persons in
the population). Individual perceptions and reactions to sound vary in intensity and over different
dimensions (such as pleasure/fear or distraction). Sound level is a predictor of the perceived health
effects of sound, but explains only part of the reaction. The positive or negative perception of and
attitude to the source of the sound is a better predictor of its effects. This article aims to show how
the two perspectives (based on acoustics and on perception) can lead to a combined approach in the
management of a wind farm aimed to reduce annoyance, not only on a sound level. An important
aspect in this approach is what the sound means to people, leading to the following questions: is
it associated with the experience of having no say in plans, does it lead to anxiety or worry and
is it appropriate? The available knowledge will be applied to wind farm management, including
planning as well as operation....
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