scholarly journals Some data on the behaviour of kites (Milvus milvus, Milvus migrans) nesting close to two active wind farms in Saxony, Germany

The Ring ◽  
2017 ◽  
Vol 39 (1) ◽  
pp. 121-136
Author(s):  
Przemysław Busse ◽  
Izabella Rząd

Abstract The main aim of this study was to evaluate how local pairs of kites behave in the vicinity of two wind farms located in the same region (Saxony, Germany) and at farms which are to be re-powered. We observed three pairs that had located their nests close to active wind farms (a few hundred to 1500 m from the wind farm). Special attention was focused on variation in the intensity of flights and its dependence on the local landscape and to active avoidance of existing wind turbines. Observations were made at the end of the breeding time, when the young were still in the nest and shortly after fledging. Despite the short observation periods, the results seem to show clearly how differentiated the flight patterns of these birds are in relation to the landscape features around the farm. The distance from the nest to the wind farm cannot be the only measure of the level of potential wind-farm-related danger to the birds nesting close to the farm site. Distribution of flights is not random, but clearly concentrated on defined target hunting areas, while other directions are visited infrequently. In the case of both farms, the farm was rarely crossed by the Black Kites (9.9% of all flights) and very rarely (2.8%) by the Red Kites, and such crossing was observed only while the turbine rotors were not in motion or when the rotors were turning slowly (below 5 turns/min.). It may be advisable to conduct special monitoring of movement patterns at breeding time if kite nests are found close to the planned location of the wind farm.

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 693
Author(s):  
Anna Dóra Sæþórsdóttir ◽  
Margrét Wendt ◽  
Edita Tverijonaite

The interest in harnessing wind energy keeps increasing globally. Iceland is considering building its first wind farms, but its landscape and nature are not only a resource for renewable energy production; they are also the main attraction for tourists. As wind turbines affect how the landscape is perceived and experienced, it is foreseeable that the construction of wind farms in Iceland will create land use conflicts between the energy sector and the tourism industry. This study sheds light on the impacts of wind farms on nature-based tourism as perceived by the tourism industry. Based on 47 semi-structured interviews with tourism service providers, it revealed that the impacts were perceived as mostly negative, since wind farms decrease the quality of the natural landscape. Furthermore, the study identified that the tourism industry considered the following as key factors for selecting suitable wind farm sites: the visibility of wind turbines, the number of tourists and tourist attractions in the area, the area’s degree of naturalness and the local need for energy. The research highlights the importance of analysing the various stakeholders’ opinions with the aim of mitigating land use conflicts and socioeconomic issues related to wind energy development.


2021 ◽  
pp. 0309524X2199245
Author(s):  
Kawtar Lamhour ◽  
Abdeslam Tizliouine

The wind industry is trying to find tools to accurately predict and know the reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique used to determine critical subsystems, causes and consequences of wind turbines. FMECA has been widely used by manufacturers of wind turbine assemblies to analyze, evaluate and prioritize potential/known failure modes. However, its actual implementation in wind farms has some limitations. This paper aims to determine the most critical subsystems, causes and consequences of the wind turbines of the Moroccan wind farm of Amougdoul during the years 2010–2019 by applying the maintenance model (FMECA), which is an analysis of failure modes, effects and criticality based on a history of failure modes occurred by the SCADA system and proposing solutions and recommendations.


SIMULATION ◽  
2021 ◽  
pp. 003754972110286
Author(s):  
Eduardo Pérez

Wind turbines experience stochastic loading due to seasonal variations in wind speed and direction. These harsh operational conditions lead to failures of wind turbines, which are difficult to predict. Consequently, it is challenging to schedule maintenance actions that will avoid failures. In this article, a simulation-driven online maintenance scheduling algorithm for wind farm operational planning is derived. Online scheduling is a suitable framework for this problem since it integrates data that evolve over time into the maintenance scheduling decisions. The computational study presented in this article compares the performance of the simulation-driven online scheduling algorithm against two benchmark algorithms commonly used in practice: scheduled maintenance and condition-based monitoring maintenance. An existing discrete event system specification simulation model was used to test and study the benefits of the proposed algorithm. The computational study demonstrates the importance of avoiding over-simplistic assumptions when making maintenance decisions for wind farms. For instance, most literature assumes maintenance lead times are constant. The computational results show that allowing lead times to be adjusted in an online fashion improves the performance of wind farm operations in terms of the number of turbine failures, availability capacity, and power generation.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4291
Author(s):  
Paxis Marques João Roque ◽  
Shyama Pada Chowdhury ◽  
Zhongjie Huan

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.


2021 ◽  
Vol 6 ◽  
pp. 20-25
Author(s):  
Alexey Bogatyrev

Wind turbines and wind farms can be connected to the major electricity distribution system. This paper presents the research results on synchronization of wind farm power supply into the utility grid depending on parameters of the grid at the moment. Measurement time gets synchronized with the external time signal delivered from a navigating system like GLONASS. This can help eliminate antiphase operation of individual wind turbines. Connection diagrams and the whole methodology presented in this paper aim to make wind farm power supply into the grid more effective and loss-eliminating.


2018 ◽  
Vol 42 (6) ◽  
pp. 547-560 ◽  
Author(s):  
Fa Wang ◽  
Mario Garcia-Sanz

The power generation of a wind farm depends on the efficiency of the individual wind turbines of the farm. In large wind farms, wind turbines usually affect each other aerodynamically at some specific wind directions. Previous studies suggest that a way to maximize the power generation of these wind farms is to reduce the generation of the first rows wind turbines to allow the next rows to generate more power (coordinated case). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its individual maximum power coefficient CPmax (individual case). This article studies this paradigm and proposes a practical method to evaluate when the wind farm needs to be controlled according to the individual or the coordinated case. The discussion is based on basic principles, numerical computations, and wind tunnel experiments.


Author(s):  
Guodong Liang ◽  
Zhiyu Jiang ◽  
Karl O. Merz

Abstract Wind farms with shared mooring lines have the potential to reduce mooring costs. However, such wind farms may encounter complex system dynamics because adjacent wind turbines are coupled. This paper presents an analysis of the shared mooring system with a focus on the system natural periods. We first apply Irvine's method to model both the shared line and the two-segment single lines. The response surface method is proposed to replace iterations of the catenary equations of the single lines, and a realistic single line design is presented for OC3 Hywind. Then, system linearization and eigenvalue analysis are performed for the wind farm consisting of two spar floating wind turbines, one shared line, and four single lines. The obtained natural periods and natural modes are verified by numerical free decay tests. Finally, a sensitivity study is carried out to investigate the influence of mooring properties. It is found that the shared line has a significant influence on the natural periods in the surge and sway modes. The natural periods in the surge and sway modes are also most sensitive to the mooring property variations. Two sway eigenmodes are identified, and the lower sway natural period varies between 23 s and 88 s in the sensitivity study. The present analysis method can be used to identify critical natural periods at the preliminary design stage of shared mooring systems.


Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4246 ◽  
Author(s):  
Guglielmo D’Amico ◽  
Giovanni Masala ◽  
Filippo Petroni ◽  
Robert Adam Sobolewski

Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR).


Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 882 ◽  
Author(s):  
Hongyan Ding ◽  
Zuntao Feng ◽  
Puyang Zhang ◽  
Conghuan Le ◽  
Yaohua Guo

The composite bucket foundation (CBF) for offshore wind turbines is the basis for a one-step integrated transportation and installation technique, which can be adapted to the construction and development needs of offshore wind farms due to its special structural form. To transport and install bucket foundations together with the upper portion of offshore wind turbines, a non-self-propelled integrated transportation and installation vessel was designed. In this paper, as the first stage of applying the proposed one-step integrated construction technique, the floating behavior during the transportation of CBF with a wind turbine tower for the Xiangshui wind farm in the Jiangsu province was monitored. The influences of speed, wave height, and wind on the floating behavior of the structure were studied. The results show that the roll and pitch angles remain close to level during the process of lifting and towing the wind turbine structure. In addition, the safety of the aircushion structure of the CBF was verified by analyzing the measurement results for the interaction force and the depth of the liquid within the bucket. The results of the three-DOF (degree of freedom) acceleration monitoring on the top of the test tower indicate that the wind turbine could meet the specified acceleration value limits during towing.


Author(s):  
Paul Sclavounos ◽  
Christopher Tracy ◽  
Sungho Lee

Wind is the fastest growing renewable energy source, increasing at an annual rate of 25% with a worldwide installed capacity of 74 GW in 2007. The vast majority of wind power is generated from onshore wind farms. Their growth is however limited by the lack of inexpensive land near major population centers and the visual pollution caused by large wind turbines. Wind energy generated from offshore wind farms is the next frontier. Large sea areas with stronger and steadier winds are available for wind farm development and 5MW wind turbine towers located 20 miles from the coastline are invisible. Current offshore wind turbines are supported by monopoles driven into the seafloor at coastal sites a few miles from shore and in water depths of 10–15m. The primary impediment to their growth is visual pollution and the prohibitive cost of seafloor mounted monopoles in larger water depths. This paper presents a fully coupled dynamic analysis of floating wind turbines that enables a parametric design study of floating wind turbine concepts and mooring systems. Pareto optimal designs are presented that possess a favorable combination of nacelle acceleration, mooring system tension and displacement of the floating structure supporting a five megawatt wind turbine. All concepts are selected so that they float stably while in tow to the offshore wind farm site and prior to their connection to the mooring system. A fully coupled dynamic analysis is carried out of the wind turbine, floater and mooring system in wind and a sea state based on standard computer programs used by the offshore and wind industries. The results of the parametric study are designs that show Pareto fronts for mean square acceleration of the turbine versus key cost drivers for the offshore structure that include the weight of the floating structure and the static plus dynamic mooring line tension. Pareto optimal structures are generally either a narrow deep drafted spar, or a shallow drafted barge ballasted with concrete. The mooring systems include both tension leg and catenary mooring systems. In some of the designs, the RMS acceleration of the wind turbine nacelle can be as low as 0.03 g in a sea state with a significant wave height of ten meters and water depths of up to 200 meters. These structures meet design requirements while possessing a favorable combination of nacelle accleration, total mooring system tension and weight of the floating structure. Their economic assessment is also discussed drawing upon a recent financial analysis of a proposed offshore wind farm.


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