Spatial Distribution Of Wind Speed Research Articles

A multi-factor spatio-temporal correlation analysis method for PV development potential estimation

The impact of wind speed on PV power generation is influenced by the monsoon and the complex topography and environmental factors found in mountainous areas. This complexity can reduce the correlation between PV power and irradiance. To better understand the impact of wind speed, we conducted an analysis in various topographical regions of the Hengduan Mountain in China. Our findings show that high wind speeds can enhance PV utilization, particularly in plateau and hill regions. This is due to the blocking and lifting effect of the north-south oriented mountains on the east-west wind, as well as the channeling effect on the north-south wind. To improve the efficiency of utilizing solar energy, it is important to consider the spatial distribution of wind speed when developing PV. Correlation analysis of multi-factors on a spatial and temporal scale can also offer insight. Furthermore, planning the layout of PV systems with meteorological resources in mind can enhance PV utilization in complex mountainous terrain.

Uncertainty analysis of wind speed of wind turbine

AbstractThe uncertainty of wind speed has a great impact on the reliability of wind turbines. However, previous studies usually used average wind speed or rated wind speed as inputs, ignoring the impact of time and space distribution on wind speed. Based on the hourly ground observation data of meteorological stations, four observation stations are taken as the research object of the uncertainty of wind speed spatial distribution. The four observation stations are divided into single day and one week, and seven data analysis indicators and normal distribution models are used day and night to analyze the uncertainty of wind speed time distribution. The results show that both spatial distribution and temporal distribution are important factors that cause the uncertainty of wind speed. Due to different geographical locations of four stations, their wind speed time domain diagrams are different, and the maximum wind speed, fluctuation frequency and fluctuation amplitude of wind speed at each observation station are different; The wind speed distribution of a single day is quite different from that of a week. The data of a single day and a week are analyzed by day and night, which is quite different from the overall data analysis. The necessity of wind speed uncertainty research of wind turbine considering the temporal and spatial distribution is verified, and it is concluded that normal distribution is not suitable for fitting the distribution model of four stations under study, which lays a foundation for determining the wind speed distribution model, analyzing the power characteristics of wind turbine, evaluating the generation capacity of wind turbine, and analyzing the reliability of wind turbine.

The temporal and spatial distribution of wind factor in Iraq

This work aims to study wind factor 10 m above the ground level for different stations in Iraq for determining the promising regions in the field of wind energy. For this purpose, the use of data (Wind Speed) for 25 years is performed. Missing data may occur within the time series of processing. Calculations are performed by using the statistical model (ARIMA model). The analysis of data is performed by using the Geographic Information System Program (Arc map). The temporal and spatial distribution of wind speed shows that the high value during the summer and the autumn in the southern stations (Hai, Nasiriyah, Basrah, Amara) can be considered as the promising regions in Iraq.

Impact of Residential Building Layouts on Microclimate in a High Temperature and High Humidity Region

Microclimatic condition is a fundamental indicator for evaluating outdoor space livability and vitality. Research has shown that poorly designed building layouts can lead to discomfort; however, the mechanisms influencing outdoor microclimate based on residential building layout are unclear for high temperature and high humidity regions. This study explores the relationship between residential building layouts and the outdoor wind and thermal environment at the pedestrian level in Wuhan, a city renowned for high temperatures and high humidity. Six typical residential building layouts were simulated, using the ENVI-met numerical model, to determine the spatial distribution of wind speed and air temperature. The Universal Thermal Climate Index was adopted as a comprehensive index with which to assess spatial and diurnal variations in microclimates surrounding each building layout. Results showed that parallel building layouts formed a ventilation corridor that increased wind speeds by approximately 0.3 m/s. A staggered building layout, in line with the prevailing wind direction, facilitated airflow in the ventilation corridor and further increased wind speeds. Windward buildings blocked high-temperature airflows and reduced air temperatures by approximately 1 ℃ in parallel layouts, and 1.4 ℃ in enclosed layouts. However, the cooling effect of windward buildings on high-temperature airflow was weaker than the warming effect caused by the wind shadow effect and direct sunlight. Additionally, the performance of the thermal comfort of the enclosed type layout was significantly better, for most of the day, than the parallel type layout.

Spatiotemporal Characteristics of Near-Surface Wind in Shenzhen

The spatiotemporal characteristics of near-surface wind in Shenzhen were investigated in this study by using hourly observations at 92 automatic weather stations (AWSs) from 2009 to 2018. The results show that during the past 10 years, most of the stations showed a decreasing trend in the annual mean of the 10 min average wind speed (avg-wind) and the mean of the 3 s average wind speed (gust wind). Over half of the decreasing trends at the stations were statistically significant (p < 0.05). Seasonally, the decrease in wind speed was the most severe in spring, followed by autumn, winter, and summer. The distribution of wind speed tends to be greater in the east and coastal areas for both avg-wind and gust wind. From September to March of the following year, the prevailing wind direction in Shenzhen was northerly, and from April to August, the prevailing wind direction was southerly. The seasonal wind speed distribution exhibited two different types, spring–summer type and autumn–winter type, which may be induced by their different prevailing wind directions. The analysis by the empirical orthogonal function (EOF) method confirmed the previous findings that the mean wind speed was decreasing in Shenzhen and that two different seasonal wind speed spatial distribution patterns existed. Such a study could provide references for wind forecasting and risk assessment in the study area.

Projected changes in wind speed and its energy potential in China using a high‐resolution regional climate model

AbstractFollowing its commitment to Paris Agreement in 2015, China has started to explore potential renewable energy solutions with low carbon emissions to mitigate global warming. Though wind energy is one of the most cost‐effective solutions and has been favored for climate policy development around the world, its high sensitivity to climate change raises some critical issues for the long‐term effectiveness in providing sustainable energy supply. Particularly, how wind speed and its energy potential in China will change in the context of global warming is still not well understood. In this paper, we simulate the near‐surface wind speed over China using the PRECIS regional climate modeling system under different RCP emission scenarios for assessing the possible changes in wind speed and wind energy availability over China throughout the 21st century. Overall, the PRECIS model can reasonably reproduce the mesoscale climatological near‐surface wind speed and directions as documented in reanalysis data across most regions of China, while some local discrepancies are reported in the southwestern regions. In the future, the annual mean wind speed would be decreasing in most regions of China, except for a slightly increase in the southeast. The expected changes in wind speed are characterized with different amplitudes and rates under different RCP emission scenarios. The changes in the spatial distribution of wind speed seem to be sensitive for RCP climate emission scenarios, especially in the late 21st century. The spatiotemporal changes in wind energy potential exhibit a similar behavior to those in near‐surface wind speed, but the magnitudes of these changes are larger. In general, the wind power density is expected to increase by over 5% in winter in the major wind fields in China (ie, Northwest, Northcentral and Northeast), while significant decreases (by about 6% on average) are projected for other seasons (ie, spring, summer and autumn). By contrast, the wind energy potential in the northeast would increase over most months in the year, especially in winter and summer. The results of this research are of great importance for understanding where and to what extent the wind energy can be utilized to contribute renewable energy system development in China in support of its long‐term climate change mitigation commitment.

Dynamic Modeling of Wind Turbines Based on Estimated Wind Speed under Turbulent Conditions

Large-scale wind turbines with a large blade radius rotates under fluctuating conditions depending on the blade position. The wind speed is maximum in the highest point when the blade in the upward position and minimum in the lowest point when the blade in the downward position. The spatial distribution of wind speed, which is known as the wind shear, leads to periodic fluctuations in the turbine rotor, which causes fluctuations in the generator output voltage and power. In addition, the turbine torque is affected by other factors such as tower shadow and turbine inertia. The space between the blade and tower, the tower diameter, and the blade diameter are very critical design factors that should be considered to reduce the output power fluctuations of a wind turbine generator. To model realistic characteristics while considering the critical factors of a wind turbine system, a wind turbine model is implemented using a squirrel-cage induction motor. Since the wind speed is the most important factor in modeling the aerodynamics of wind turbine, an accurate measurement or estimation is essential to have a valid model. This paper estimates the average wind speed, instead of measuring, from the generator power and rotating speed and models the turbine’s aerodynamics, including tower shadow and wind shear components, without having to measure the wind speed at any height. The proposed algorithm overcomes the errors of measuring wind speed in single or multiple locations by estimating the wind speed with estimation error less than 2%.

ПРИВЕДЕННЯ ДАНИХ ВИМІРЮВАНЬ ШВИДКОСТІ ВІТРУ ДО УМОВ ВІДКРИТОЇ МІСЦЕВОСТІ

Wind speed spatial distribution over the territory of Ukraine built based on weather stations measurements has been analyzed. Interpolated field of wind speed averaged over 1981-2010 indicated fairly heterogeneous structure with a number of artificial spots of larger/smaller values compared to surrounding areas. The main reason of such heterogeneity might be associated with representativeness of observation site regarding the landscape zone. It is well known that surrounding obstacles have a great impact on wind flow in horizontal direction. In order to solve this problem we have corrected sub-daily wind speed data measured at 207 meteorological stations of Ukraine for the period of 1981-2010 according to the open terrain conditions and the standard height (10 m). Generally, aerodynamic characteristics (e.g. surface roughness length) of measurement sites are needed in order to perform such adjustment. However, the only usable parameter available at a climatological reference book is horizon closure degree. The research revealed significant relationship between this characteristic and wind speed records (Pearson correlation coefficient equals -0.58). Given that horizon closure degree could not be used in correction procedure directly, surface roughness length has been calculated for 10 stations and statistical relationship has been determined between these two parameters. Based on the obtained relation and additional information we have found roughness length for all 207 stations at eight directions. Supplementary materials for analysis included observation sites description and Google Earth snapshots as well. In the final step, there has been applied a correction formula derived from the neutral logarithmic profile of wind speed in the atmospheric surface layer. The output of the research is new database of corrected wind speed measurements for the multiyear period. These results have been compared with observations. Mean 30-yr corrected speeds are featured by more homogeneous distribution over Ukraine and mostly higher values (with positive mean spatial bias ~0.35 m/s). The applied method allowed us to remove uncertainties related to differences in vertical level of measurements and considerably eliminate influence of the micro-scale terrain inhomogeneity. Obtained datasets may facilitate to perform spatial interpolation and further development of Ukrainian Wind Atlas.

Generation and transmission expansion planning with high penetration of wind farms considering spatial distribution of wind speed

This paper represents the effect of wind speed’s spatial distribution on the simultaneous generation and transmission expansion planning of power systems including wind farms. To this end, wind farm’s capacity factor is used as a practical parameter to model its output power. It is shown that ignoring wind speed’s spatial distribution affects the expected exploitable wind power. In other words, the utilizable wind power of a wind farm in a power system would be overestimated if the spatial distribution of the wind speed is not considered and the wind farm’s owner expects more utilizable wind power than what happens in the real world.The objective function of the proposed mixed integer linear programming (MILP) model is to minimize total cost which includes three main parts: 1. The total investment cost of thermal generation units, transmission lines, and wind farms, 2. Expected operation cost of thermal generators, which is related to fuel consumption and penalty of the CO2 emission, and 3. Expected loss cost of transmission lines. Furthermore, it is investigated that how different values of operation cost, as well as CO2 emission tax, affect the proposed expansion planning model. Two test systems, namely IEEE 24-bus RTS and IEEE 118-bus test systems, are employed to evaluate the effectiveness of the proposed method. The results show that ignoring wind speed’s spatial distribution not only changes the optimal plan but also makes the planner expect a further reduction in the value of objective function. This outcome is particularly true for high values of operation cost and emission taxes of greenhouse gases as well as high wind power penetration levels.

Fault-tolerant Individual Pitch Control using Adaptive Sliding Mode Observer

Due to the increasing size of wind turbines, the unbalanced loads caused by the uneven spatial distribution of wind speed and turbulence are becoming larger and larger. As has been proved, individual pitch control (IPC) can mitigate the blade asymmetric loads greatly in region 3. On the other hand, the pitch actuator faults can affect the pitching performance with slow dynamics, resulting in generator power instability and even deteriorating the unbalanced loads of blades. However, the effects of unbalanced blade loads deterioration caused by pitch actuator faults have not been taken into account by the traditional IPC design. In the present paper, a fault-tolerant control (FTC) strategy using adaptive sliding mode estimation is combined with a traditional IPC system based on two different control methods (Proportional-Integral and H∞ loop-shaping). It maintains the nominal pitch performance and removes the negative effects of pitch actuator faults on generator power and unbalanced blade loads perfectly. The effectiveness of the proposed strategy is verified on the 5MW NREL wind turbine system.

Design Wind Speed Evaluation Technique in Wind Turbine Installation Point by Using the Meteorological and CFD Models

It is highly important in Japan to choose a good site for wind turbines, because the spatial distribution of wind speed is quite complicated over steep complex terrain. We have been developing the unsteady numerical model called the RIAM-COMPACT (Research Institute for Applied Mechanics, Kyushu University, Computational Prediction of Airflow over Complex Terrain). The RIAM-COMPACT is based on the LES (Large-Eddy Simulation). The object domain of the RIAM-COMPACT is from several m to several km, and can predict the airflow and gas diffusion over complex terrain with high precision. In the present paper, the design wind speed evaluation technique in wind turbine installation point by using the mesoscale meteorological model and RIAM-COMPACT CFD model was proposed. The design wind speed to be used for designing WTGs can be calculated by multiplying the ratio of the mean wind speed at the hub-height to the mean upper-air wind speed at the inflow boundary, i.e., the fractional increase of the mean hub-height wind speed, by the reduction ratio, R. The fractional increase of the mean hub-height wind speed was evaluated using the CFD simulation results. This method was proposed as Approach 1 in the present paper. A value of 61.9 m/s was obtained for the final design wind speed, Uh, in Approach 1. In the evaluation procedure of the design wind speed in Approach 2, neither the above-mentioned reduction rate, R, nor an upper-air wind speed of 1.7 Vo, where Vo is the reference wind speed, was used. Instead, the value of the maximum wind speed which was obtained from the typhoon simulation for each of the investigated wind directions was adopted. When the design wind speed was evaluated using the 50-year recurrence value, the design wind speed was 48.3 m/s. When a somewhat conservative safety factor was applied, that is, when the 100 year recurrence value was used instead, the design wind speed was 52.9 m/s.

Modelling the Spatial Distribution of Wind Energy Resources in Latvia

Abstract The paper studies spatial wind energy flow distribution in Latvia based on wind speed measurements carried out at an altitude of 10 m over a period of two years, from 2015 to 2016. The measurements, with 1 min increments, were carried out using certified measuring instruments installed at 22 observation stations of the Latvian National Hydrometeorological and Climatological Service of the Latvian Environment, Geology and Meteorology Centre (LEGMC). The models of the spatial distribution of averaged wind speed and wind energy density were developed using the method of spatial interpolation based on the historical measurement results and presented in the form of colour contour maps with a 1×1 km resolution. The paper also provides the results of wind speed spatial distribution modelling using a climatological reanalysis ERA5 at the altitudes of 10, 54, 100 and 136 m with a 31×31 km resolution. The analysis includes the comparison of actual wind speed measurement results with the outcomes of ERA5 modelling for meteorological observation stations in Ainazi, Daugavpils, Priekuli, Saldus and Ventspils.

Estimating potential wind energy from sparsely located stations in a mountainous coastal region

ABSTRACTFor the spatial planning of a potential wind power plant (WPP) site, the efficient assessment of the wind power potential is important. However, observations are lacking for most potential sites. Here, a statistical three‐step approach is presented to estimate the spatial distribution of potential wind power in a region in which observational stations are sparsely located. First, multiple linear regression is used to fill the gaps in the wind data collected at the stations. Second, spatial interpolation with hybrid Kriging is used to construct the grid‐based data based on the station‐based, gap‐filled data. Third, the wind power potential is estimated according to the theoretical relationship between wind speed and power. As a case study, the spatial distribution of wind power potential is estimated over Jeju Island, where WPPs currently exist. Initially, the selected regression model in this case study showed correlation co‐efficients ranging from 0.48 to 0.82. In a second step, the spatially interpolated data with the gap‐filled data reasonably captured the expected spatial distribution of wind speed than those with the observed data. Finally, the results showed that the coastal region might be the best region for WPPs rather than the high elevation region far from the coast and that all the existing WPPs are located in regions with high potential wind power. The proposed statistical approach is simple and efficient for preliminary spatial planning. Furthermore, it can be applied to other regions with sparsely distributed wind speed data, including mountainous coastal regions.

High-Resolution Micro-Siting Technique for Large Scale Wind Farm Outside of Japan Using LES Turbulence Model

The spatial distribution of wind speed varies greatly over steep complex terrain, thus the selection of an optimal site in such terrain for wind turbine construction requires great care. We have developed a numerical model for simulating unsteady flows called RIAM-COMPACT (Research Institute for Applied Mechanics, Kyushu University, COM putational Prediction of Airflow over Complex Terrain), which is based on the LES (Large-Eddy Simulation) technique. The computational domain of RIAM-COMPACT can be varied from several meters to several kilometers, and the model is able to predict airflow over complex terrain with high accuracy. The present paper discusses the application of RIAM-COMPACT to the micro-siting of wind turbines at sites outside Japan. The results from two case studies will be presented.

Application of MK-PRISM for interpolation of wind speed and comparison with co-kriging in South Korea

The spatial distribution of wind speed is important information required to understand climate-related regional phenomena. This paper presents the Modified Korean Parameter-elevation Regression on Independent Slopes Model (MK-PRISM) as a method for spatial interpolation of monthly wind speeds. A database of gridded monthly mean wind speeds with a spatial resolution of 1 km for the period of March 2011–February 2014 is constructed by MK-PRISM. Wind speed observation data collected from the 529 to 641 meteorological stations in South Korea were utilized as the input data for interpolation. The wind speed distribution estimated by co-kriging is used for comparison with the MK-PRISM results. Research demonstrates that the efficiency difference between the two models, MK-PRISM and co-kriging, is insignificant. The Kling and Gupta efficiencies of both models were 0.68-0.78 and the root mean square errors (RMSEs) were 0.44-0.68 m/s. The spatial distribution of wind speeds, however, differs between MK-PRISM and co-kriging, which can be considered a reflection of the influence of topographic features such as terrain convexity, aspect, and coastal proximity. MK-PRISM can perform more appropriately to represent the phenomena where similar wind speeds appear continuously along ridges and coastlines. This suggests that a knowledge-based approach that considers topographic features can be successfully applied to the interpolation of monthly or seasonal wind speeds, similar to temperature and precipitation. The wind speed distribution generated by MK-PRISM can be utilized as important data for different geographical studies.

Optimal wind energy penetration in power systems: An approach based on spatial distribution of wind speed

Contributing in power system expansions, the present study establishes an efficient scheme for optimal integration of wind energy resources. The proposed approach highly concerns the spatial distribution of wind speed at different points of a wind farm. In mathematical statements, a suitable probability distribution function (PDF) is well-designed for representing such uncertainties. In such conditions, it is likely to have dissimilar output powers for individual and identical wind turbines. Thus, the overall aggregated PDF of a wind farm remarkably influences the critical parameters including the expected power and energy, capacity factor, and the reliability metrics such as loss of load expectation (LOLE) and expected energy not supplied (EENS). Furthermore, the proposed approach is deployed for optimal allocation of wind energy in bulk power systems. Hence, two typical test systems are numerically analyzed to interrogate the performance of the proposed approach. The conducted survey discloses an over/underestimation of harvestable wind energy in the case of overlooking spatial distributions. Thus, inaccurate amounts of wind farm’s capacity factor, output power, energy and reliability indices might be estimated. Meanwhile, the number of wind turbines may be misjudged to be installed. However, the proposed approach yields in a fair judgment regarding the overall performance of the wind farm. Consequently, a reliable penetration level of wind energy to the power system is assured. Extra discussions are provided to deeply assess the promising merits of the founded approach.

Characterization of the wind speed variability and future change in the Iberian Peninsula and the Balearic Islands

AbstractWind energy is susceptible to global climate change because it could alter the wind patterns. Then, improvement of our knowledge of wind field variability is crucial to optimize the use of wind resources in a given region.Here, we quantify the effects of climate change on the surface wind speed field over the Iberian Peninsula and Balearic Islands using an ensemble of four regional climate models driven by a global climate model.Regions of the Iberian Peninsula with coherent temporal variability in wind speed in each of the models are identified and analysed using cluster analysis. These regions are continuous in each model and exhibit a high degree of overlap across the models. The models forced by the European Reanalysis Interim (ERA‐Interim) reanalysis are validated against the European Climate Assessment and Dataset wind. We find that regional models are able to simulate with reasonable skill the spatial distribution of wind speed at 10 m in the Iberian Peninsula, identifying areas with common wind variability.Under the Special Report on Emissions Scenarios (SRES) A1B climate change scenario, the wind speed in the identified regions for 2031–2050 is up to 5% less than during the 1980–1999 control period for all models. The models also agree on the time evolution of spatially averaged wind speed in each region, showing a negative trend for all of them. These tendencies depend on the region and are significant at p = 5% or slightly more for annual trends, while seasonal trends are not significant in most of the regions and seasons. Copyright © 2015 John Wiley & Sons, Ltd.

An Examination of the Taikoyama Wind Farm Nacelle Separation Accident Using a CFD Approach

Because a significant portion of the topography of Japan is characterized by steep, complex terrain, which results in a complex spatial distribution of wind speed, great care is necessary for selecting a site for the construction of wind turbines. We have developed a computational fluid dynamics (CFD) model for unsteady flow called Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain (RIAM-COMPACT®). The RIAM-COMPACT® CFD model is based on the large-eddy simulation (LES) technique. In this paper, a numerical wind simulation for the Taikoyama Wind Farm is performed using high-resolution terrain elevation data. The results suggest that all six wind turbines at the Taikoyama Wind Farm are subject to significant influence from separated flow (terrain-induced turbulence) which is generated due to the topographical irregularities in the vicinity of the wind turbines. A proposal has been also made on reconstruction of the wind farm.

Towards the modelling of pedestrian wind speed using high-resolution digital surface models and statistical methods

Wind is a complex phenomenon and a critical factor in assessing climatic conditions and pedestrian comfort within cities. To obtain spatial information on near-ground wind speed, 3D computational fluid dynamics (CFD) modelling is often used. This is a computationally intensive method which requires extensive computer resources and is time consuming. By using a simpler 2D method, larger areas can be processed and less time is required. This study attempts to model the relationship between near-ground wind speed and urban geometry using 2.5D raster data and variable selection methods. Such models can be implemented in a geographic information system (GIS) to assess the spatial distribution of wind speed at street level in complex urban environments at scales from neighbourhood to city. Wind speed data, 2 m above ground, is obtained from simulations by CFD modelling and used as a response variable. A number of derivatives calculated from high-resolution digital surface models (DSM) are used as potential predictors. A sequential variable selection algorithm followed by all-possible subset regression was used to select candidate models for further evaluation. The results show that the selected models explain general spatial wind speed pattern characteristics but the prediction errors are large, especially so in areas with high wind speeds. However, all selected models did explain 90 % of the wind speed variability (R2 ≈ 0.90). Predictors adding information on width and height ratio and alignment of street canyons with respect to wind direction are suggested for improving model performance. To assess the applicability of any derived model, the results of the CFD model should be thoroughly evaluated against field measurements.

Calculation Method of Instantaneous Wind Speed Spatial Distribution of Wind Farm

Instantaneous wind speed spatial distribution of wind farm is the basis of the optimal control for wind turbines. A calculation method was proposed for the instantaneous wind speed spatial distribution in wind farm, which made the instantaneous wind speed spatial distribution is divided into wake and non-wake zone. For the non-wake zone, the instantaneous wind speed spatial distribution is mainly affected by the flow field coupling between wind turbines, in order to describe the influence accurately, a cross spectral matrix was constructed including the wind turbine mutual distance and the azimuth in wind farm, and the solving calculation process of the cross spectral matrix was deduced. For the wake zone, single wind turbine wake model and wake superposition model were established according to conservation of momentum, and then the average wind speed spatial distribution in wake zone was calculated. According to the average wind speed spatial distribution, the instantaneous wind speed spatial distribution was calculated. A wind farm is selected as case to verify the calculation method, and the results show that this calculation method can accurately describe the instantaneous wind speed spatial distribution of wind farm.