scholarly journals Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low generation limits

2016 ◽  
Vol 113 (48) ◽  
pp. 13570-13575 ◽  
Author(s):  
Lee M. Miller ◽  
Axel Kleidon

Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power limits that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 Wem−2) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 Wem−2) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power use can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 Wem−2of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power.

2015 ◽  
Vol 112 (36) ◽  
pp. 11169-11174 ◽  
Author(s):  
Lee M. Miller ◽  
Nathaniel A. Brunsell ◽  
David B. Mechem ◽  
Fabian Gans ◽  
Andrew J. Monaghan ◽  
...  

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 105 km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m−2, whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m−2, with VKE capturing this combination in a comparatively simple way.


2020 ◽  
Vol 28 (4) ◽  
Author(s):  
Adetona Tayo Fatigun ◽  
Ebenezer Babatope Faweya ◽  
Funmilola Olusola Ogunlana ◽  
Taiwo Hassan Akande

In this study, the wind electricity generation potential and energy cost at Ikeja were investigated using 31 years wind speed data obtained from Nigeria Meteorological Agency. The study addresses the challenges of inadequate electricity supply and the development of alternative source of electricity. The measured data, captured at 10m height were subjected to 2-parameter Weibull and other statistical analysis. Weibull analysis of wind speed showed good fit between actual data and Weibull predicted data confirming the adequacy of the model. The value of wind speed at 10m height ranged between 3.47m/s and 5.33m/s with annual average of 4.5m/s. Also, the Wind Power Density (WPD) ranged between 116.3 W/m² and 423.3W/m² with annual average value of 257.85W/m². The mean electric power outputs from the model turbines varied between 11KW and 290KW while its Capacity Factor (CF) ranged between 13.8% and 0.36%. Also, the generation cost per kilowatt-hour varied between $0.11 and $2.39 annually. Therefore, the wind energy potential at Ikeja could be adjudged marginal and belonging to wind power class 2. The generation cost of wind electricity is cost-effective in the months of April and August while cost-deficit in the remaining months of the year. The location is considered suitable for small to medium scale wind power generation, but economically infeasible for large scale grid connected wind electricity 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 ◽  
Author(s):  
Anasuya Gangopadhyay ◽  
Ashwin K Seshadri ◽  
Ralf Toumi

<p>Smoothing of wind generation variability is important for grid integration of large-scale wind power plants. One approach to achieving smoothing is aggregating wind generation from plants that have uncorrelated or negatively correlated wind speed. It is well known that the wind speed correlation on average decays with increasing distance between plants, but the correlations may not be explained by distance alone. In India, the wind speed diurnal cycle plays a significant role in explaining the hourly correlation of wind speed between location pairs. This creates an opportunity of “diurnal smoothing”. At a given separation distance the hourly wind speeds correlation is reduced for those pairs that have a difference of +/- 12 hours in local time of wind maximum. This effect is more prominent for location pairs separated by 200 km or more and where the amplitude of the diurnal cycle is more than about  0.5 m/s. “Diurnal smoothing” also has a positive impact on the aggregate wind predictability and forecast error. “Diurnal smoothing” could also be important for other regions with diurnal wind speed cycles.</p>


Inventions ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 59
Author(s):  
Hasanali Khojasteh ◽  
Younes Noorollahi ◽  
Mojtaba Tahani ◽  
Mehran Masdari

Nowadays, by increasing energy demand and considering the importance of environmental issues in recent decades, the use of renewable energies is expanding. Among renewable energies, wind power and its technology are growing and evolving more rapidly. Resource assessment in Iran has revealed the significant potential of wind energy around the country. To further develop wind energy in the country and create large-scale wind power plants, the consideration of distributed power generation using small wind turbines for applications in agricultural and residential use is needed. Conventional small wind turbines and small wind lens turbines have been developed in recent years. In this research project, a small wind lens turbine is designed. The advantages of this turbine are an increased production capacity and reduced cut-in speed and noise pollution. In this study, a lens (or shroud) is added to a small turbine, and the maximized annual energy production (AEP) and minimization of the levelized cost of energy (LCOE) are modeled. We applied the NSGA-II algorithm for optimization to find the best answer. The input parameters in the objective function of the AEP are cut-in, cut-out, rated speeds, scale factor, and shape factor. Additionally, the input parameters in the objective function of the LCOE are the power production, initial capital cost, annual operating expenses, and balance of energy. The results indicate that installing a wind lens turbine in Kish Island led to an LCOE decrease of 56% on average, and we can see an 83% increase in the AEP. In the Firoozkooh area, an average reduction of 59% in the LCOE and 74% increase in the AEP for a wind lens turbine is observed.


Author(s):  
Rambod Rayegan ◽  
Yong X. Tao ◽  
Frank Y. Fang

This study utilizes two sets of wind speed data at 3 m above the ground surface level retrieved from two on-campus weather stations to study the wind power generating potential at the University of North Texas Campus. Weather stations have been installed approximately 5 miles away from each other. The mean wind speed data of 10 minute intervals in a one-year period from February 1st 2011 to January 31st 2012 has been adopted and analyzed. The numerical values of the dimensionless Weibull shape parameter (k) and Weibull scale parameter (c) have been determined. Monthly average wind speed and standard deviation, power generation, and power density at the sensor level for both locations has been discussed. Lower values of wind speed were found during summer months and higher during spring months. The results show that the wind power density in the area is fair enough to be considered as a renewable power source for the University. Thereafter annual energy production by using two wind turbines with nominal capacities of 100 and 3.5 kW for both weather stations has been studied. Initial costs of using each turbine to maintain power demands of selected buildings have been compared. In order to utilize wind energy, it is recommended to install highly efficient wind turbines for electricity supply of campus buildings with lower power demands. Using grant monies to maintain the initial costs of the installation of wind turbines make them economically more desirable. Since wind power potential is low during summer, PV panels as proper supplements to the power generating system are suggested.


2020 ◽  
Author(s):  
Ricardo García-Herrera ◽  
Jose M. Garrido-Perez ◽  
Carlos Ordóñez ◽  
David Barriopedro ◽  
Daniel Paredes

<p><span><span>We have examined the applicability of a new set of 8 tailored weather regimes (WRs) to reproduce wind power variability in Western Europe. These WRs have been defined using a substantially smaller domain than those traditionally used to derive WRs for the North Atlantic-European sector, in order to maximize the large-scale circulation signal on wind power in the region of study. Wind power is characterized here by wind capacity factors (CFs) from a meteorological reanalysis dataset and from high-resolution data simulated by the Weather Research and Forecasting (WRF) model. We first show that WRs capture effectively year-round onshore wind power production variability across Europe, especially over northwestern / central Europe and Iberia. Since the influence of the large-scale circulation on wind energy production is regionally dependent, we have then examined the high-resolution CF data interpolated to the location of more than 100 wind farms in two regions with different orography and climatological features, the UK and the Iberian Peninsula. </span></span></p><p><span><span>The use of WRs allows discriminating situations with varied wind speed distributions and power production in both regions. In addition, the use of their monthly frequencies of occurrence as predictors in a multi-linear regression model allows explaining up to two thirds of the month-to-month CF variability for most seasons and sub-regions. These results outperform those previously reported based on Euro-Atlantic modes of atmospheric circulation. The improvement achieved by the spatial adaptation of WRs to a relatively small domain seems to compensate for the reduction in explained variance that may occur when using yearly as compared to monthly or seasonal WR classifications. In addition, our annual WR classification has the advantage that it allows applying a consistent group of WRs to reproduce day-to-day wind speed variability during extreme events regardless of the time of the year. As an illustration, we have applied these WRs to two recent periods such as the wind energy deficit of summer 2018 in the UK and the surplus of March 2018 in Iberia, which can be explained consistently by the different combinations of WRs.</span></span></p>


2011 ◽  
Vol 347-353 ◽  
pp. 2342-2346
Author(s):  
Rong Fu ◽  
Bao Yun Wang ◽  
Wan Peng Sun

With increasing installation capacity and wind farms penetration, wind power plays more important role in power systems, and the modeling of wind farms has become an interesting research topic. In this paper, a coherency-based equivalent model has been discussed for the doubly fed induction generator (DFIG). Firstly, the dynamic models of wind turbines, DFIG and the mechanisms are briefly introduced. Some existing dynamic equivalent methods such as equivalent wind model, variable speed wind turbine model, parameter identification method and modal equivalent method to be used in wind farm aggregation are discussed. Then, considering wind power fluctuations, a new equivalent model of a wind farm equipped with doubly-fed induction generators is proposed to represent the interactions of the wind farm and grid. The method proposed is based on aggregating the coherent group wind turbines into an equivalent one. Finally, the effectiveness of the equivalent model is demonstrated by comparison with the wind farm response obtained from the detailed model. The dynamic simulations show that the present model can greatly reduce the computation time and model complexity.


2020 ◽  
Vol 13 (10) ◽  
pp. 4993-5005
Author(s):  
Axel Kleidon ◽  
Lee M. Miller

Abstract. With the current expansion of wind power as a renewable energy source, wind turbines increasingly extract kinetic energy from the atmosphere, thus impacting its energy resource. Here, we present a simple, physics-based model (the Kinetic Energy Budget of the Atmosphere; KEBA) to estimate wind energy resource potentials that explicitly account for this removal effect. The model is based on the regional kinetic energy budget of the atmospheric boundary layer that encloses the wind farms of a region. This budget is shaped by horizontal and vertical influx of kinetic energy from upwind regions and the free atmosphere above, as well as the energy removal by the turbines, dissipative losses due to surface friction and wakes, and downwind outflux. These terms can be formulated in a simple yet physical way, yielding analytic expressions for how wind speeds and energy yields are reduced with increasing deployment of wind turbines within a region. We show that KEBA estimates compare very well to the modelling results of a previously published study in which wind farms of different sizes and in different regions were simulated interactively with the Weather Research and Forecasting (WRF) atmospheric model. Compared to a reference case without the effect of reduced wind speeds, yields can drop by more than 50 % at scales greater than 100 km, depending on turbine spacing and the wind conditions of the region. KEBA is able to reproduce these reductions in energy yield compared to the simulated climatological means in WRF (n=36 simulations; r2=0.82). The kinetic energy flux diagnostics of KEBA show that this reduction occurs because the total yield of the simulated wind farms approaches a similar magnitude as the influx of kinetic energy. Additionally, KEBA estimates the slowing of the region's wind speeds, the associated reduction in electricity yields, and how both are due to the depletion of the horizontal influx of kinetic energy by the wind farms. This limits typical large-scale wind energy potentials to less than 1 W m−2 of surface area for wind farms with downwind lengths of more than 100 km, although this limit may be higher in windy regions. This reduction with downwind length makes these yields consistent with climate-model-based idealized simulations of large-scale wind energy resource potentials. We conclude that KEBA is a transparent and informative modelling approach to advance the scientific understanding of wind energy limits and can be used to estimate regional wind energy resource potentials that account for the depletion of wind speeds.


2019 ◽  
pp. 36-41
Author(s):  
Kachan Yu ◽  
Kuznetsov V

Purpose. Identify the features of operation of wind farms as an auxiliary supplier of electricity for non-traction consumers of railway networks and analyze the main factors that directly affect the use of wind farms due to the random nature of wind flow and additional factors due to the above conditions in different climates. The research methodology is based on modern methods of computational mathematics, statistics and information analysis using modern computer technology. Findings. The need to use renewable energy sources in the power supply systems of non-traction consumers of railway transport is obvious. Given the constant growth of prices and tariffs for electricity in Ukraine, more and more attention is paid to its savings and the search for the cheapest and most affordable alternative sources. The authors consider issues related to the possibility of using additional generation of electricity in the power supply systems of railway transport through the use of wind turbines, including for non-traction consumers. The analysis of wind flow features in some regions of Ukraine was carried out, and the measurement of wind speed in Zaporizhia and Dnipropetrovsk regions was obtained with the help of a compact wind speed sensor manufactured by Micro-Step-MIS LLC (Russia). The obtained values of wind speed were recorded and stored digitally. The received information of the above device was processed. The authors conclude that in the case of using wind turbines as an additional power source in the networks of non-traction consumers of railway power supply systems it is economically advantageous to connect them directly to these networks and fully use all electricity produced by them, reducing its consumption from this power supply system. The originality is that the use of renewable energy sources in the power supply systems of non-traction consumers of railway transport, in particular wind turbines, is proposed. Practical implications. Introduction of wind power plants as an auxiliary supplier of electricity for non-traction consumers of railway power grids in order to minimize electricity costs. Keywords: renewable energy sources, quality of electric energy, wind power plant, power supply networks of railway transport, non-traction consumers of railway electric networks, electricity production, wind speed.


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