Wind Speed Region Research Articles

A control algorithm to increase the efficient operation of wind energy conversion systems under extreme wind conditions

This paper aims to increase the power production of gearless permanent magnet synchronous generator (PMSG) based wind energy conversion systems (WECS) in strong (greater than 25 m/s) wind speed regions. In general, most wind turbines cut off when wind speed is over the cut-out rate; as a result, the power generation of the wind farm decreases. This study introduces the look-up table pitch angle and rotational speed control to generate extra power in a strong wind region. Consequently, WECS can produce electric power at a reduced level until the wind speed reaches 35 m/s and the possibility of shutting down the wind turbines decreases. The proposed algorithm decreases the mechanical stress of wind turbine by decelerating rotational speed rather than turbine torque in strong wind regions. Furthermore, the model predictive control (MPC) is proposed to replace the PI controller in the inner current loop of the rotor speed control loop, thereby improving the performance of the stator current track. The proposed control method is validated in Matlab/SimPowerSystem software. The simulation result confirms that the proposed control method reduces the possibility of shutdown and guarantees temporally power production in strong wind conditions.

Variability of sea salt and methanesulfonate in firn cores from northern Victoria Land, Antarctica: Their links to oceanic and atmospheric condition variability in the Ross Sea

The potential ice core proxies of variability in oceanic and atmospheric conditions over the Ross Sea were evaluated. This study examined sea salt sodium (ss–Na+) and biogenic sulfur (methanesulfonate, MS–) records, covering 23 years between 1990 and 2012, from two firn cores drilled on the Styx Glacier plateau (SGP), northern Victoria Land, East Antarctica, to examine the potential links between those records and datasets for various climate variables. The comparison showed that the interannual variability of the ss–Na+ record is closely related to Pacific–South American mode 2 (PSA2) in the Ross Sea sector, exhibiting an increased ss–Na+ flux, owing most likely to more frequent penetration of maritime air masses from the western Ross Sea to the SGP when the winter/spring PSA2 mode becomes more pronounced. The observed MS– record revealed statistically significant positive correlations with the changes in the summertime chlorophyll a concentration in the Ross Sea polynya (RSP) and wind speed in the southern Ross Sea region. This indicates the dominant role of a combination of changes in the summertime primary productivity and wind speed over the RSP in modulating the MS– deposition flux at the SGP. These results highlight the suitability of the ss–Na+ and MS– records from the SGP as proxies for characterizing the dominant patterns of variability in oceanic and atmospheric conditions and their underlying mechanisms on interannual and longer timescales beyond the instrumental limits over the Ross Sea region.

Non-Gaussian multivariate statistical monitoring of spatio-temporal wind speed frequencies to improve wind power quality in South Korea.

The spatial and temporal variability of renewable energy resources, particularly wind energy, should be statistically evaluated to achieve sustainable economic development to mitigate climate change. In this study, a non-Gaussian multivariate statistical monitoring approach is proposed to investigate the wind speed frequencies across different regions of South Korea. Anemometer data were first collected in 11 different provinces of South Korea with hourly resolution for one year. The best-of-fit for the corresponding distribution function was identified to characterize the behavior of the wind speed frequency at each region among more than 60 candidate functions using the chi-squared test. Furthermore, a non-Gaussian multivariate statistical monitoring method based on the Hotelling T2 chart was developed to spatially and temporally analyze the physical patterns of the wind speed frequencies using the estimated distribution parameters. Then determination rule of cut-in and cut-out speeds of wind turbine was suggested to improve the wind power quality across the regions. The results indicated that Weibull and Gamma distributions are best-of-fit functions of each province in South Korea; the physical patterns of wind including the average wind speed and gale can be identified by distribution parameters. Furthermore, the proposed non-Gaussian multivariate monitoring approach can elucidate the spatial and temporal variability of the regional wind speed frequencies, including the average wind speeds and extreme wind events across South Korea. Based on the statistically identified variability of wind behavior, the wind power quality of wind turbines can be improved by 12% on average by adjusting the cut-in and cut-off speed. Thus, the proposed non-Gaussian multivariate monitoring approach can provide practical guidelines for manufacturers to achieve reliable wind energy generation by considering the spatial and temporal wind behavior.

Analysis of Spatial and Temporal Variations of the Near-Surface Wind Regime and Their Influencing Factors in the Badain Jaran Desert, China

Wind regime is one of the main natural factors controlling the evolution and distribution of aeolian sand landforms, and sand drift potential (DP) is usually used to study the capacity of aeolian sand transport. The Badain Jaran Desert (BJD) is located where polar cold air frequently enters China. Based on wind data of eight nearby meteorological stations, this research is intended to explore the temporal variation and spatial distribution features of wind speed and DP using linear regression and cumulative anomaly method, and reveal the relationship between atmospheric circulation and wind speed with correlation analysis. We found that the wind speed and frequency of sand-blowing wind in the BJD decreased significantly during 1971–2016, and the wind speed obviously mutated in 1987. The regional wind speed change was affected by the Asian polar vortex, the northern hemisphere polar vortex and the Tibet Plateau circulation. The wind rose of the annual sand-blowing wind in this region was the “acute bimodal” type. Most of the annual wind directions clustered into the W-NW, and the prevailing wind direction was WNW. During 1971–2016, the annual DP, the resultant drift potential (RDP) and the directional variability (PDP/DP) in the desert showed an obvious downtrend, with a “cliff-like” decline in the 1980s and relative stable fluctuation thereafter. The BJD was under a low-energy wind environment with the acute bimodal wind regime. Wind speed, sand-blowing wind frequency and DP were high in the northeast and low in the southwest.

Comparison of severe convection forecasts over China from assimilating Doppler radar observations using 4DEnKF and EnKF approaches

This study compared forecasts of a squall line and a mesoscale convective system (MCS) over China produced by assimilating Doppler radar data using four-dimensional ensemble Kalman filter (4DEnKF) and EnKF methods. In the 4DEnKF approach, four-dimensional ensemble covariances were incorporated to consider the time differences of the radar data collected at different elevation angles within a volume scan. In comparison with EnKF, results showed that 4DEnKF exhibited substantially higher quantitative forecast skills of radar reflectivity for a 6-h forecast, and better representation of structure and intensity of the squall line and MCS; EnKF largely failed to capture the intense convection segments of both cases. 4DEnKF demonstrated greater skills than EnKF in probabilistic reflectivity forecasts for thresholds of moderate and heavy precipitation. It was also found that 4DEnKF strengthened the cold pool and wind speed in the convective regions, and outperformed EnKF in terms of all standard variables at most levels, especially middle and lower levels. Diagnosis indicated that 4DEnKF was capable of producing much stronger analysis increments of temperature, wind and moisture during radar data assimilation cycles, which was favorable for initialization and development of convection.

Feasibility Study of Harnessing Low Wind Speed Turbine as Hybrid Power Source for Offshore Platforms

In this study, the viability of harnessing wind energy for offshore oil and gas (O&G) platforms as a micro-grid solution in low wind speed regions to power O&G platforms is explored. However, wind, as a renewable energy, is known to be highly variable and is unable to provide standalone power reliably within a micro-grid solution due to the variation of the wind speed at hub height, which subsequently leads to a variation of the power outcome. Here, a hybrid power generation concept is developed in which one gas turbine generator (GTG) is replaced with a floating horizontal axis wind turbine (WT) system. By setting up this system, the reduction of the maintenance costs of the GTGs and the reduction of fuel gas consumption reduces carbon dioxide (CO2) emissions. In addition to this, the fuel gas savings in terms of the business side of such a solution provide a positive revenue impact. In this feasibility study, a technical framework is developed, followed by an economic framework. In the technical framework, wind assessments are performed to obtain the annual energy production for the selected field. Furthermore, an economic framework is established for both conventional and hybrid concepts in two scenarios: greenfield and brownfield, where the incremental net present value (NPV) and levelized cost of energy are calculated. The resultant difference in NPV for hybrid power generation compared to conventional power generation was found to be between 22% and 37%. The levelized cost of energy (LCOE) for WT is USD 165.52/MWh, which is 39% lower than for conventional, gas turbine-only operations. The LCOE for the hybrid approach is lower than for the conventional scenario by 22%. In conclusion, the hybrid micro-grid concept solution can harness wind energy from low wind regions with better economic benefits compared to conventional methods through the proper selection of the WT system, its floating substructure, and efficient micro-grid system for powering oil and gas platforms.

SPLNet: A sequence-to-one learning network with time-variant structure for regional wind speed prediction

Although regional wind speed prediction is of great value in the development of wind power, it is rarely studied in the past years. To fill this gap, we introduce a deep learning method for multi-step regional wind speed prediction, which aims to model the spatiotemporal dynamics of wind speed in a given region and make predictions across time steps. There are several important challenges for it: (1) how to simultaneously build long-term temporal dependencies and long-range spatial interactions of wind speed; (2) how to capture the fluctuant, intermittent, and chaotic nature of wind speed. In this paper, we propose a novel framework named Sequence-to-one Predictive Learning Net (SPLNet) for multi-step regional wind speed prediction. To effectively utilize historical information and build the long-term temporal dependencies, SPLNet regards multi-step prediction as multi-time sequence-to-one (Seq2one) learning, where each prediction is made based on a previous historical sequence. Besides, a new spatiotemporal dynamics attention (STD-Atten) unit is developed as the key component of SPLNet, which can realize Seq2one learning and capture long-range spatial dependencies. Moreover, to better model the non-stationary and violent nature of wind speed, SPLNet adopts a time-variant structure, where different STD-Atten units are used for predicting wind speed at different time steps. To stabilize model training and enhance prediction performance, a step-separated training procedure is put forward. Comprehensive experiments have been conducted on three real-world datasets, where regional wind speed is illustrated as images. Experimental results demonstrate the effectiveness and superiority of the proposed method over state-of-the-art techniques.

Aircraft observations and reanalysis depictions of trends in the North Atlantic winter jet stream wind speeds and turbulence

AbstractMultiple studies have considered whether increased anthropogenic CO2 will affect the wind speeds and turbulence associated with the winter North Atlantic polar‐front jet stream in the upper atmosphere. Key questions are whether any effects can already be seen and, if so, can they be seen independent of computer models of the atmosphere. In this study we use two reanalyses, NCEP/NCAR and the ECMWF ERA5, and two large observational archives, AMDAR/ACARS and the Global Aircraft Data Set (GADS), to try to answer these questions for the period 2002–2020 when automated aircraft observations were plentiful over the North Atlantic. We focus on eastbound, New York to London, flights. No significant increase appears in reanalyses during the last roughly 40 years (1979–2020) which is our best estimate for the modern satellite era. In contrast, for the last roughly 20 years (2002–2020) both the ERA5 reanalysis (2.5% per year) and the GADS archive (1.2% to 1.4% per year) show a statistically significant rise in the wind speed in the North Atlantic jet streak exit region. These results must be considered in the context of atmospheric oscillations, changes to the North Atlantic Track System (NATS), and the effects of aircraft step climbs. We estimate that up to 0.5% of the rise may be due to improvements in the NATS operations and an unknown additional amount may be due to the substantial increase in automated aircraft observations starting in 1997. We also examine the impact of aircraft observations on one's confidence in drawing conclusions from secular changes in the reanalyses. For turbulence, the Light turbulence trends are not statistically significant. Our confidence in the turbulence results is more limited since these observations reflect medium‐term changes in tactical and strategic aircraft operational procedures as well as the underlying prevalence of turbulence.

지역빈도해석을 이용한 남해안 지역의 극치풍속 추정

We performed the regional frequency analysis to estimate the extreme wind speed in southern coastal region of Korea using annual maximum wind speed (AMWS) and linear-moments method proposed by Hosking. Data at all station is found to be accordance. It is confirmed that all data could represent one homogeneous region through the heterogeneity test. Generalized Normal (GNO) and Generalized Extreme Value (GEV) distributions were selected as probability distributions representing the southern coastal region from the goodness-of-fit tests. The stability of the two distributions was evaluated using the relative error (RB) and the root mean square error (RRMSE). It is found that the GNO distribution is more stable than the GEV distribution. Finally, the extreme wind speed of the stations is estimated use the quantile representing the southern coast region, the average, median value, and location parameters of each station. The regional frequency analysis is effective to estimate the extreme wind speed at station where data are insufficient or not measured.

Alternative Method of Nature Inspired Geometrical Design Strategy for Drag Induced Wind Turbine Blade Morphology

Although drag driven wind turbine is regarded as an efficient rotor for low wind speed region, design reconfiguration is a continuous process in order to improve the performance of the rotor. The main governing factor that influences the performance of the rotor is the blade morphology. Hence, this paper presents a proposed nature inspired design approach for the development of drag driven wind turbine blade morphology. The design approach framework comprise of 3 main elements namely image processing, geometrical analysis and bio-hybridization. The proposed bio-hybridized design consist of blade mainframe curve inspired by nautilus shell and barnacle on the blade surface. It is found that integration of barnacle geometries on the surface of the blade has affected the performance of the rotor. Result shows that the peak Cm is at λ = 0.55 for experimental and CFD is Cm = 0.238 and Cm = 0.253 respectively. The proposed design resulted in experimental and numerical Cp = 0.113 and Cp = 0.127 respectively at 7 m/s and λ = 0.7. The presented design technique with appropriate design bio-element provides a systematic method for engineers to model wind turbine blade morphologies.

Application of Machine Learning Algorithms in Decision Making of State Enterprises

One of the conditions that Bosnia and Herzegovina needs to meet in order to become a member of the European Union is to increase the share of electricity production from renewable sources. The aim of this paper is to use a Linear Regression algorithm, Support Vector Machine algorithm and Random Forest algorithm to make a contribution in this area from the aspect of machine learning - more precisely to determine the parameters that most affect the wind speed in Mostar region. The obtained model showed that parameter that most affects the wind speed in Mostar are short-term wind accelerations. The model can be easily generalized and applicable to other data sets.

CFD assessment of wind energy potential for generic high-rise buildings in close proximity: Impact of building arrangement and height

High-rise building complexes are of great importance for enabling sustainable urban development in large parts of the world. Earlier studies have indicated that high wind speed regions can be present along the passage between two high-rise buildings as well as above the roofs. At such locations, urban wind energy could be harvested by installing wind turbines between and/or above the roof of the buildings. However, the available wind energy potential around an array of generic high-rise buildings in close proximity has not yet been assessed for different building configurations. This paper conducts a detailed evaluation of the impacts of the building arrangement and height for a 2 × 2 array with a building height-to-street width ratio of 30 on the mean wind velocity and the wind energy potential along the passages between both upstream and downstream buildings as well as on their roofs. The following parameters are analyzed: (i) the passage width between the two upstream buildings (w), (ii) the streamwise distance between the upstream and downstream buildings (d), and (iii) the height difference between the upstream and downstream buildings (ΔH). The 3D steady Reynolds-averaged Navier-Stokes (RANS) equations are solved using the Reynolds stress model (RSM) turbulence model for closure. The CFD results are validated using wind-tunnel measurements of mean wind speed and turbulence intensity performed for the same building array. The results show elevated wind power density along the upstream passages for small w (=0.15B), high d (=0.6B), and equal building height (ΔH = 0). In contrast, comparatively high values of w, small d, and ΔH < 0 yield high wind power densities between the downstream buildings. Among the different wind turbine types considered, horizontally-mounted vertical axis wind turbines seem the most promising option for wind energy harvesting between the buildings.

Error-Based Active Disturbance Rejection Control for Pitch Control of Wind Turbine by Improved Coyote Optimization Algorithm

Wind energy systems are expected to supply the majority of future generation from renewables due to the maturity of technology and the availability of energy resources. In this paper, in order to improve the ability of tracking a desired power reference at high wind speed region, a pitch control strategy based on error-based active disturbance rejection control (ADRC) approach is proposed for variable speed wind turbine system, providing a novel practically appealing control structure. The stability analysis of the proposed pitch controller based on singular perturbation theory is provided. Next, an improved coyote optimization algorithm (COA) fused with L <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm {\acute{e}}$</tex-math></inline-formula> vy flight and Sinusoidal map is proposed to address the controller parameters tuning issue. Then, the effectiveness of the proposed solution is verified on a 1.5 MW FAST simulator taking into account both multi-step and IEC turbulence wind conditions. Finally, an analysis in frequency domain of the pitch control system with the proposed control strategy is presented.

Regional forecasting of wind speed in large scale wind plants

ABSTRACT The ultra-short-term forecasting of the wind speed in large-scale wind plants not only helps to monitor system operation but also improves the acceptance rate for the power system. The present study establishes a single unit and a regional wind speed forecasting models and achieves the fast prediction of the wind speed in the large-scale wind plant. On the basis, by combining the variational mode decomposition (VMD) and autoregressive integrated moving average (ARIMA) model, an improved VMD-ARIMA model for wind speed forecasting of the single unit is proposed, and the cross-correlation coefficient is presented to determine the number of modes in VMD. Moreover, according to the similarity of wind speed series of different units, the wind plant is divided into several sub-regions based on the correlation of different units. Finally, by calculating the proportion coefficient between the key unit and the non-key one, the wind speed of the whole wind plant is forecasted fast. To assess the performance of the proposed model, it is compared with some forecasting model. Results validated by the actual data sets for Jishanliang wind plant, Shaanxi province, China, show higher efficiency and better reliability of the proposed model in comparison with other forecasting methods.

The impact of long-term weather changes on air quality in Brazil

In this study, we estimate the weather-related increases in ambient air pollution (CO, NO2, SO2, O3 and PM2.5) in Brazil between 2003 and 2018. The impact of long-term weather changes on each air pollutant was defined as “weather penalty”. Overall, ambient air pollution levels in Brazil during the period 2003–2018 have decreased in most of the Brazilian regions. We estimated significant trends in meteorological variables, indicating an increase in temperature, relative humidity, and wind speed in all Brazilian regions over the 16-study period. Our findings suggest that PM2.5 was the pollutant most impacted by weather changes. For the 16-year period of analysis, we estimated a weather penalty ranging from 1.58 μg/m−3 (CI 95%:1.25; 1.91) to 0.41 μg/m−3 (CI 95%:0.28; 0.53) among the different Brazilian regions. If weather parameters had remained constant, PM2.5 would have decreased by 1.10 μg/m3 (95%CI: 0.74; 1.46) in the South and by 2.25 μg/m3 (95%CI: 2.72; 1.79) in the Midwest. Over the 16-year study period, the weather impact on PM2.5 in Brazil was associated with over 6500 excess deaths.

Granule Ripples in the Kumtagh Desert, China: Morphological and Sedimentary Characteristics, and Development Processes

AbstractGranule ripples are widespread on Earth and are a fundamental component of dryland sedimentary systems, but the relationship between their wavelength and surface particle size is unclear; in addition, their sedimentary bedding and granule ripple development are incompletely understood. In this study, we examined the relationship between granule ripple development, morphology, and the surface grain‐size distribution. We measured the morphology and particle‐size distribution of granule ripples in China's Kumtagh Desert, and found an exponential relationship between ripple wavelength and average crest particle size, which contradicts previous results. We hypothesize the ripples resulted from creep of coarse particles caused by saltation impacts, accompanied by decreasing bed elevation, leading to crest migration and increased crest height. The size composition and wind regime determined the movement mode of particles, which controlled ripple development and size, but dry–wet and freeze–thaw cycles also contributed. We established a new conceptual model for the development of large granule ripples. Sand ripples and small granule ripples develop similarly, but large ripples did not form from merger of smaller ripples. We report for the first time that particles between 2.3 and 4.7 mm in diameter were missing in the ripple crests (confirmed in wind tunnel experiments). This gap affects the particle movement mode. Since the threshold wind speed for particle saltation at 4.7 mm approaches the regional maximum wind speed, quantifying the missing particles may permit prediction of regional maximum wind speeds, and has practical significance for identifying wind conditions elsewhere, including the surface of Mars.

Wind turbine LIDAR-assisted control: Power improvement, wind coherence and loads reduction

This paper aims to firstly review various LIDAR-assisted wind turbine control methods proposed in the past ten years for improving power production in the below rated wind speed region in order to clarify their performance and quantify the potential benefits and drawbacks of LIDAR-assisted control. Secondly, a new LIDAR-assisted control algorithm based on Extremum Seeking Control (ESC) using LIDAR preview information for tracking the optimal power coefficient value is presented and compared to the traditional control strategy. The results show that the newly proposed LIDAR-assisted control strategy is beneficial in the below rated wind speed region when the aerodynamic properties of blades are changed largely compared to the original design. Lastly, the effects of the wind field coherence between the LIDAR measured points and the rotor plane on the LIDAR-assisted control for loads reduction in above rated region is discussed. An important conclusion is that the major benefit of LIDAR-assisted wind turbine control is to improve collective pitch control for reducing fatigue loads in above rated region, when the coherence bandwidth between the LIDAR measured wind speed and the rotor effective wind speed is high.

An individual pitch control method for floating offshore wind turbine

As the vast deep-water wind resource represents a potential development of a superior resource in comparison to the coast and land, the floating offshore wind turbine (FOWT) represents a viable solution for increasing renewable energy generation. However, above the rated wind speed region, the influence of turbulent wind loads is more severe on the floating offshore wind turbine. Thus, the control system’s primary objective should be to minimize fatigue loads and irregular power output swings to achieve smooth power output. This paper proposes a feedback method of individual pitch control for FOWT that, by utilizing a feedback control strategy, effectively reduces asymmetric aerodynamic loads and platform motion. The effectiveness of the method is verified through simulation verification.

A robust gain scheduling method for a PI collective pitch controller of multi-MW onshore wind turbines

This work proposes a robust tuning method for full-load pitch control by deriving new design formulae for collective Proportional Integral (PI) pitch controllers. The paper investigates the frequency domain characteristics of a full state linearized turbine model extracted from the aeroelastic simulation tool HawcStab2, and suggests a reduced order model that captures the low-frequency behaviour and may be used to derive PI tuning formulae that account for collective blade flap modes. The proposed controllers are then compared to traditional PI controllers based on a single degree of freedom (1-DOF) model of the drive-train using linearized NREL5MW and DTU10MW models. The 10 MW model is investigated in more detail through non-linear simulations in HAWC2 using wind step and turbulent wind conditions. The proposed design formulae show robust results, giving more consistent gain and phase margins than 1-DOF designs throughout the above rated wind speed region, and may be used to increase controller bandwidth while maintaining acceptable stability margins, achieving 49% and 63% reductions in standard deviation of the output power for the DTU10MW model in turbulent conditions. Statistical analysis for both controllers was also performed to investigate fatigue loading on the main shaft caused by the pitch actuation.

Approaches for Joint Retrieval of Wind Speed and Significant Wave Height and Further Improvement for Tiangong-2 Interferometric Imaging Radar Altimeter

The interferometric imaging radar altimeter (InIRA) adopts a short baseline along with small incidence angles to acquire interferometric signals from the sea surface with high accuracy, thus the wide-swath sea surface height (SSH) and backscattering coefficient (σ0) can be obtained simultaneously. This work presents an approach to jointly retrieve the wind speed and significant wave height (SWH) for the Chinese Tiangong-2 interferometric imaging radar altimeter (TG2-InIRA). This approach utilizes a multilayer perceptron (MLP) joint retrieval model based on σ0 and SSH data. By comparing with the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data, the root mean square errors (RMSEs) of the retrieved wind speed and the SWH are 1.27 m/s and 0.36 m, respectively. Based on the retrieved SWH, two enhanced wind speed retrieval models are developed for high sea states and low sea states, respectively. The results show that the RMSE of the retrieved wind speed is 1.12 m/s when the SWHs &lt; 4 m; the RMSE is 0.73 m/s when the SWHs ≥ 4 m. Similarly, two enhanced SWH retrieval models for relatively larger and relatively smaller wind speed regions are developed based on the retrieved wind speed with corresponding RMSEs of 0.19 m and 0.16 m, respectively. The comparison between the retrieved results and the buoy data shows that they are highly consistent. The results show that the additional information of SWH can be used to improve the accuracy of wind speed retrieval at small incidence angles, and also the additional information of wind speed can be used to improve the SWH retrieval. The stronger the correlation between wind speed and SWH, the greater the improvement of the retrieved results. The proposed method can achieve joint retrieval of wind speed and SWH accurately, which complements the existing wind speed and SWH retrieval methods for InIRA.