Hourly Mean Wind Speed Research Articles

Pesisir Barat Lampung Offshore Wind Characteristic in Local Renewable Energy Development Studies

Renewable energy is one of the most researched topics. One renewable energy source is wind energy. As with some other energy sources, there are 2 locations for wind energy conversion, onshore and offshore. Using offshore wind energy requires more accurate wind data due to the higher risk. The characteristics of the wind at sea are one of these data. This study used data sets from ECMWF and BMKG from 2001 to 2020 (20 years). This research aims to examine the wind characteristics in the offshore of Pesisir Barat Lampung. The wind characteristics being examined are wind speed, wind direction, wind blowing duration, and wind speed distribution. The maximum hourly mean wind speed in these waters is 16.35 m/s. The dominant wind direction is blowing from the South East (SE). The maximum average wind-blowing duration to SE direction is 11 hours based on ECMWF and 14 hours based on BMKG. Based on the Chi-Square and Kolmogorov-Smirnov distribution fitting methods, the wind speed distribution in these waters is best fitted by the Weibull distribution for the ECMWF and the Lognormal distribution for BMKG. Using these two data sources, on average, ECMWF provides wind speeds 5% to 20% higher than BMKG. In analyzing wind potential, BMKG data will certainly provide more critical results than ECMWF data. In the analysis of offshore support structures, ECMWF data will certainly produce more critical structures. While the calculation of potential is better using BMKG data. Wind power potential in Pesisir Barat offshore is in the range of 44.6 to 82.9 W/m2.

Offshore Wind Power Resource Assessment in the Gulf of North Suez

Growing population, industrialization, and power requirements are adversely affecting the environment through increased greenhouse gases resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led nations to promote clean and self-renewable sources of energy to address this environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting an offshore wind power resource assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above mean sea level (AMSL), as well as temperature and pressure data near the surface, are used. The data is obtained from ERA5 (fifth generation global climate reanalysis) at six (L1–L6) chosen offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL, while temperature and pressure are available near water-surface level. At the L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL, respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at the L1 and L3 sites, and generally lower values of wind variability indices, are indicative of a favorable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at the L5 and L1 sites, corresponding to wind turbines WT1 and WT4. Based on this analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifier indices introduced will help decision-makers in targeting potential windy sites with more confidence.

Restoration of Wind Speed in Qinzhou, Guangxi during Typhoon Rammasun

In 2014, Typhoon Rammasun invaded Qinzhou, Guangxi, causing damage to the wind tower sensor at 80 m in Qinzhou. In order to restore the wind speed at 80 m at that time, this paper was based on the hourly average wind speed data of the wind tower and meteorological station from 2017–2019, and constructed the wind speed related model of Meteorological Station and the wind measuring tower in Qinzhou, Moreover, this paper Based on the hourly average wind speed data of Qinzhou Meteorological Station in 2014, Restored the hourly average wind speed of the anemometer tower during Rammasun landfalled. The results showed it is significant correlation that the hourly mean wind speed of the wind tower at 80 m and the hourly mean wind speed of meteorological station at 100 m (R2 = 0.9632), and speed of the wind measuring tower and speed of meteorological station constitutes an equation, This equation is Y = 0.7834X. The hourly average wind speed of the wind tower at 80 m during the 2014 Rammasun Landing was restored using this model. See the results in Schedule 4.

Internal seiches in a karstic mesotrophic lake (Prošće, Plitvice Lakes, Croatia)

A lake temperature experiment was performed at the Prošće, Plitvice Lakes, Croatia during a 4-month observational period (6 July–4 November, 2019) to investigate the occurrence and characteristics of internal seiches in the lake. Two-minute mean lake temperatures were measured at a single lake point at fifteen depths ranging from 0.2 to 27 m. Analysis of these data provided insight into the previously unknown and rather complex Prošće Lake seiching. Power spectral densities (PSDs) and magnitude-squared coherences (γ2), together with corresponding cross-spectrum phases that were obtained from the hourly mean lake temperature, air pressure and wind speed data, suggested the presence of three vertical modes of an internal seiche. The first mode (V1H1, period of 6.09 h) corresponds to free baroclinic oscillations; the second mode (V2H1, period of 11.64 h) and the third mode (V3H1, period of 25.60 h) are associated with forced baroclinic oscillations of the lake interior. Excitation of the higher vertical modes is attributed to the influence of dense tributary water. Due to this water influence, vertical temperature gradients in the lake interior were relatively weak; consequently, a single thick metalimnion and/or two metalimnetic layers were established, which resulted in the presence of the V2H1 and V3H1 modes, respectively. Additionally, due to the influence of tributary water, the lake did not attain the typical stratification that is characterized by hypolimnetic temperatures of ≈ 4°C. Instead, during the entire observational period, the hypolimnetic temperatures were consistently above 7.6 °C.

Wind Characteristics in the Taiwan Strait: A Case Study of the First Offshore Wind Farm in Taiwan

This study analyzed the wind speed data of the met mast in the first commercial-scale offshore wind farm of Taiwan from May 2017 to April 2018. The mean wind speed and standard deviation, wind rose, histogram, wind speed profile, and diurnal variation of wind speed with associated changes in wind direction revealed some noteworthy findings. First, the standard deviation of the corresponding mean wind speed is somewhat high. Second, the Hellmann exponent is as low as 0.05. Third, afternoons in winter and nights and early mornings in summer have the highest and lowest wind speed in a year, respectively. Regarding the histogram, the distribution probability of wind is bimodal, which can be depicted as a mixture of two gamma distributions. In addition, the corresponding change between the hourly mean wind speed and wind direction revealed that the land–sea breeze plays a significant role in wind speed distribution, wind profile, and wind energy production. The low Hellmann exponent is discussed in detail. To further clarify the effect of the land–sea breeze for facilitating future wind energy development in Taiwan, we propose some recommendations.

Analysis of Wind Speed and Wind Pressure on the Facades in Frequency Domain for the Modelling of Air Change Rate

Air exchange in buildings is driven by pressure difference across the building envelope caused by wind and difference in density between external and internal air. The evaluation of the influence of wind on the air change rate is usually limited to the analysis of the hourly mean wind speed. Wind is a random phenomenon characterized by the broad energy spectrum. The high frequency part can be responsible for the oscillation of the air through the openings resulting in the increased air exchange. Wind pressure coefficient on the leeward site mostly depends on the form characteristics of the object in relation to wind direction. The analysis of wind speed and wind pressure on the facades in frequency domain can deliver interesting data to air change rate model. Some of the results of continuous measurements carried out on a single-family house for 8 months are presented in frequency domain. The statistics of wind speed, wind direction and pressure differences across the 6 building components are calculated. The wind turbulence and the pressure fluctuations on the facades and the roof of the building are being investigated using energy spectra of their signals. Farther analysis of the experimental results is needed to be able to include high frequency wind in the infiltration model.

Assessment of Wind Energy Potential for the Generation of Power in Coastal and Sahel Savannah Locations in Nigeria

This study examines the wind power potential for different pressure heights in some Coastal and Sahel savannah stations in Nigeria. A 5-year hourly mean wind speed data at different heights and also at the hour of 00:00 and 12:00 were obtained from ERA Interim reanalysed data set. The data were statistically analyzed using Weibull distribution function. It was found out that Ikeja and Katsina stations have the maximum wind power density of 174.69 W/m² and 196.88 W/m² for both Coastal and Sahel savannah regions respectively at 100 m height and also at 12:00 hour of the day when there is occurrence of intensive wind speed as observed in the stations considered. Therefore, the analysis demonstrates the economic feasibility of using wind energy as a means of electricity supply at Ikeja in Coastal region and Katsina in Sahel savannah region of Nigeria. Thus, the wind power potential in these areas should be adequately harnessed which could be used to compliment the present power supply and reduce carbon dioxide emissions which contribute to global warming and lower long-term overdependence on fossil fuels in those areas and in Nigeria at large.

A Novel Approach for Accurate Assessment of Design Wind Speed for Variable Wind Climate

For a widely varied wind climate in India, a single type of Extreme Value Distribution (EVD) is not suitable to fit wind speed data for all geographical locations and climatic conditions. This may lead to the inappropriate estimation of the design wind speed (Vd). In this study, a new approach, combining the merits of both the block maxima and the peaks over threshold approaches, has been used to determine the Vd. The hourly mean wind speed data of three stations, viz., Trivandrum, Bombay and Calcutta have been classified into block of months of the years 1973−2005, 1969−2007, and 1969−1994 respectively. The extreme peaks over the appropriate threshold value have been fitted into the generalized EVD (type-I, II and II). The results indicate that Fréchet distribution is the most suitable distribution for all three stations. March has the highest Vd for Trivandrum, whereas, for both Bombay and Calcutta it is September. Bombay shows highest overestimation of the Vd as given in Indian code of standard, whereas, for Trivandrum, and Calcutta these deviations have been found to be comparatively less. The five plotting position formulae have also been compared based on two goodness of fit tests, viz., R2, and RMSE.

Enhancing Short-Term Wind Power Forecasting through Multiresolution Analysis and Echo State Networks

This article suggests the application of multiresolution analysis by Wavelet Transform—WT and Echo State Networks—ESN for the development of tools capable of providing wind speed and power generation forecasting. The models were developed to forecast the hourly mean wind speeds, which are applied to the wind turbine’s power curve to obtain wind power forecasts with horizons ranging from 1 to 24 h ahead, for three different locations of the Brazilian Northeast. The average improvement of Normalized Mean Absolute Error—NMAE for the first six, twelve, eighteen and twenty-four hourly power generation forecasts obtained by using the models proposed in this article were 70.87%, 71.99%, 67.77% and 58.52%, respectively. These results of improvements in relation to the Persistence Model—PM are among the best published results to date for wind power forecasting. The adopted methodology was adequate, assuring statistically reliable forecasts. When comparing the performance of fully-connected feedforward Artificial Neural Networks—ANN and ESN, it was observed that both are powerful time series forecasting tools, but the ESN proved to be more suited for wind power forecasting.

A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property

To improve our capacity to use available wind speed data, it is necessary to develop a new statistical temporal downscaling method that uses one or a few input variables of any temporal scale for mean wind speed data to obtain wind statistics at finer temporal resolution. In the present study, a novel statistical temporal downscaling method for wind speed statistics and probability distribution is proposed. The proposed method uses the temporal structure to downscale the wind speed statistics to a fine temporal scale without the use of additional variables. The Weibull distribution of the hourly and 10-min mean wind speed data is obtained by the downscaled wind speed statistics. The proposed method provides the downscaled Weibull distribution of fine temporal wind speed data using coarse temporal wind statistics. Particularly, the use of sub-daily mean wind speed data in the downscaling of the wind speed Weibull distribution leads to good estimation precision. The Weibull distribution downscaled by the proposed method successfully reproduces the wind power density based on the wind potential energy estimation.

GHGs (greenhouse gases) emission and economic analysis of a GCRES (grid-connected renewable energy system) in the arid region, Algeria

This paper presents a method for economic evaluation and GHGs (greenhouse gases) emissions calculation from a GCRES (grid-connected renewable energy system). An investigation is made on large-scale operations of 67 MWh/day GCRES. A comparison is performed between a GCRES and a standard grid operation focusing on environmental and economic impacts. Emissions and the Renewable energy generation fraction (RF) of total energy consumption are calculated as the main environmental indicators. Costs including NPC (net present cost), COE (cost of energy) and payback period are calculated as the economic indicators. Using the hourly mean global solar irradiance, temperature and wind speed data relative to In Salah and Adrar locations characterized by an arid and hot climate according to the Koppen–Geiger climate classification, a long-term continuous implementation of hybrid renewable energy systems are simulated using HOMER software and are discussed. As results, it is observed that a GCRES reduce 30% and 35% of GHGs emission, and 81% and 76% of COE during the operation phase respectively for In Salah and Adrar.Investments in GCRES should be considered only by planning to produce parts of the equipment locally, which leads to significantly reduce the costs and, consequently, the emissions.

Reliability analysis of roof sheathing panels on wood-frame houses under wind loads in Canadian cities

A reliability analysis of roof sheathing panels was performed to assess the current minimum requirements specified in the National Building Code of Canada (NBCC). The present analysis considers the variations in the annual, hourly-mean wind speeds in cities across Canada, the external wind pressures due to roof shape, roof slope, eave height and upstream terrain, the internal wind pressures, for the range of fasteners typical of current construction practice. It was found that the use of 6d (51 mm) common nails with 300 mm spacing on intermediate supports, which is the minimum requirement of NBCC, is not adequate for many regions of the country. It was found that relatively small differences in fastener size result in large differences in roof sheathing performance. Recommendations for revisions to NBCC are made, which involve using 8d (63 mm) nails, with 150 mm spacing on intermediate supports.

Regimes do vento à superfície na área de Petrolina, submédio São Francisco

Neste trabalho o ciclo diário do vento à superfície é investigado com ênfase na variação sazonal e nas circulações locais. Os dados da estação automática instalada a 25-30 km de Petrolina, e da estação convencional localizada na cidade são utilizados. Os resultados mostram que as velocidades médias horárias aumentam (diminuem) no decorrer do trimestre abril-maio-junho (outubro-novembro-dezembro), devido à intensificação (enfraquecimento) da alta subtropical do Atlântico Sul. No trimestre julho-agosto-setembro os valores são máximos e muito próximos, com direção no intervalo 120-130 graus. O ciclo diário tem um máximo de intensidade às 8-9 HL (hora local) e dois mínimos, um às 5-6 HL e outro às 17-18 HL, em todos os meses. Os hodógrafos do vento local nas duas estações mostram circulações fracas de janeiro a maio, uma característica que pode estar relacionada com o maior teor de umidade do solo e, consequentemente, com valores mais baixos do gradiente do fluxo de calor sensível. No restante do ano, período de estiagem, as circulações locais são comparativamente fortes. Os hodógrafos apresentam forma irregular que indica um regime preferencial na direção sudeste-noroeste. As circulações locais são mais intensas às 9 e 18 HL, horários de máxima e mínima velocidade no ciclo diário, respectivamente.

Short-term spatio-temporal prediction of wind speed and direction

This paper aims to produce a low-complexity predictor for the hourly mean wind speed and direction from 1 to 6 h ahead at multiple sites distributed around the UK. The wind speed and direction are modelled via the magnitude and phase of a complex-valued time series. A multichannel adaptive filter is set to predict this signal on the basis of its past values and the spatio-temporal correlation between wind signals measured at numerous geographical locations. The filter coefficients are determined by minimizing the mean square prediction error. To account for the time-varying nature of the wind data and the underlying system, we propose a cyclo-stationary Wiener solution, which is shown to produce an accurate predictor. An iterative solution, which provides lower computational complexity, increased robustness towards ill-conditioning of the data covariance matrices and the ability to track time-variations in the underlying system, is also presented. The approaches are tested on wind speed and direction data measured at various sites across the UK. Results show that the proposed techniques are able to predict wind speed as accurately as state-of-the-art wind speed forecasting benchmarks while simultaneously providing valuable directional information.

An assessment of a three-beam Doppler lidar wind profiling method for use in urban areas

Currently there are few observations of the urban wind field at heights other than rooftop level. Remote sensing instruments such as Doppler lidars provide wind speed data at many heights, which would be useful in determining wind loadings of tall buildings, and predicting local air quality. Studies comparing remote sensing with traditional anemometers carried out in flat, homogeneous terrain often use scan patterns which take several minutes. In an urban context the flow changes quickly in space and time, so faster scans are required to ensure little change in the flow over the scan period. We compare 3993h of wind speed data collected using a three-beam Doppler lidar wind profiling method with data from a sonic anemometer (190m). Both instruments are located in central London, UK; a highly built-up area. Based on wind profile measurements every 2min, the uncertainty in the hourly mean wind speed due to the sampling frequency is 0.05–0.11ms−1. The lidar tended to overestimate the wind speed by ≈0.5ms−1 for wind speeds below 20ms−1. Accuracy may be improved by increasing the scanning frequency of the lidar. This method is considered suitable for use in urban areas.

Pacific Storms Climatology Products (PSCP): Understanding Extreme Events

E xtreme events: the f loods that displace us from our homes, the high waves that wash out coastal roads, or the toppling of trees and power poles from a passing storm. For locations around the Pacific Basin, where remote island chains sit perilously close to sea level and where rainfall is the primary source of water, questions arise concerning the return frequency and duration of such events, and whether or not they are getting more extreme. Understanding the long-term variability and change in coastal climate extremes has grown in public awareness given the potentially severe impacts related to sea-level rise coupled with coastal storms. To reduce vulnerability to the economic, social, and environmental risks associated with these phenomena, decision makers in coastal communities need timely access to accurate and contextually relevant information that affords them an opportunity to plan and respond accordingly. To address this need, the Pacific Storms Climatology Products (PSCP) project—or Pacific Storms— was established under the direction of the NOAA National Climatic Data Center (NCDC). Pacific Storms is focused on improving our understanding of patterns and trends in storm frequency and intensity—“storminess”—within the Pacific Basin. Pacific Storms is exploring how the climate-related processes that govern extreme storm events are expressed within and between three thematic areas: strong winds, heavy rains, and high seas. Theme-specif ic data integration and product development teams were formed to conduct analyses and create a broad suite of derived data products, which are publicly available online (www.pacificstormsclimatology.org). These teams included representatives from NCDC, as well as NOAA’s Center for Operational Products and Services (CO-OPS), Coastal Services Center (CSC), and National Weather Service (NWS), and the University of Hawaii, University of Alaska, University of Guam, and Oregon State University. Sources of information include NOAA’s Integrated Surface Hourly (ISH) mean sea-level pressure and wind speed data, the Global Historical Climate Network-Daily (GHCN-D) precipitation dataset, the National Water Level Observing Network (NWLON) tide gauge records, the University of Hawaii Sea Level Center (UHSLC) Joint Archive for Sea Level research quality dataset and Global Sea Level Observing System (GLOSS)/Climate Variability and Predictability (CLIVAR) “fast delivery” sea level dataset, the National Data Buoy Center (NDBC) wave buoy records, the U.S. Army Corps of Engineers’ Coastal Data Information (CDIP) buoy data, and other data sources. The data analysis and product development framework and guidelines outlined below are innovative in a number of ways. First, they focus on extreme events, and integrate data and products across a range of storm-related phenomena. Furthermore, they also paint a comprehensive picture of changes and variation in extreme-event magnitude and frequency for a mix of theme-specific parameters on seasonal, annual, and interannual time frames. The resulting extremes climatology datasets are unique, as are some of the specific products. Finally, success of the project is fundamentally tied to the collaborative efforts of the data integration and product development teams.

Empirical Analysis of Wind Power Potential at Multiple Heights for North Dakota Wind Observation Sites

Wind speed is the most critical factor that determines wind power potential and generation. In this paper, the wind speed data of multiple years from various observation sites in North Dakota, U.S. was analyzed to assess the wind power potential. The study first applied probability density functions (PDFs) to characterize the wind speed data and fit the distributions at various heights for each observation site. The fitted distributions were then used to estimate the wind power potential based on the theoretical cubic power relationship between energy potential and wind speed. Due to the complexity of functions, the numerical integration approach was employed. The following major findings were obtained from this empirical study: (1) Weibull distribution is not always the best function to fit wind speed data, while gamma and lognormal distributions produce better fitting in many occasions; (2) For different height levels at one observation site, the best performing distributions may be different; (3) The estimation accuracies of wind energy potential based on the fitted wind speed distributions range from -4% to 3.8%; (4) The rank of energy potential estimation accuracies is not always consistent with that of goodness-of-fit for wind speed distributions. In addition, a simplified approach that only relies on the hourly mean wind speed to estimate wind power potential is evaluated. Based on the theoretical cubic relationship for wind power estimation, it was found that the simplified approach may provide significantly lower estimates of wind power potential by 42-54%. As such, this approach will become more practical if this amount of difference is to be compensated. Key words: Wind speed; Distribution; Goodness-of-fit; Wind power potential; North Dakota

Wind power assessment and evaluation of electricity generation in the Gulf of Tunis, Tunisia

Abstract Wind data basing on an analysis of the hourly mean wind speed with a 10-min time step provided by the NRG meteorological weather station in the central coast of the gulf of Tunis were used for statistical analysis to determine the wind energy characteristics. In order to identify the Weibull parameters, four different methods were applied. The investigation is focused on the determination of wind speed availability, wind rose and probability of wind power generation at different hub heights. The assessment of the electricity generation and the capacity factor for eight commercial turbines at different hub heights was made. The simulation shows the potential for wind power generation on the central coast of the gulf of Tunis.

Clustering of extreme winds in the mixed climate of South Africa

A substantial part of South Africa is subject to more than one strong wind source. The effect of that on extreme winds is that higher quantiles are usually estimated with a mixed strong wind climate estimation method, compared to the traditional Gumbel approach based on a single population. The differences in the estimated quantiles between the two methods depend on the values of the Gumbel distribution parameters for the different strong wind mechanisms involved. Cluster analysis of the distribution parameters provides a characterization of the effect of the relative differences in their values, and therefore the dominance of the different strong wind mechanisms. For gusts, cold fronts tend to dominate over the coastal and high-lying areas, while other mechanisms, especially thunderstorms, are dominant over the lower-lying areas in the interior. For the hourly mean wind speeds cold fronts are dominant in the south-west, south and east of the country. On the West Coast the ridging of the Atlantic Ocean high-pressure system dominate in the south, while the presence of a deep trough or coastal low pressure system is the main strong wind mechanism in the north. In the central interior cold fronts tend to share their influence almost equally with other synoptic-scale mechanisms.

The effect of climate change and natural variability on wind loading values for buildings

Since 2006, a number of countries developed reports on climate change following the IPCC 4th assessment reports. For the Netherlands, the Royal Netherlands Meteorological Institute (KNMI) presented four new climate scenarios. Typically, climate change is described in terms of average changes, but much of the social and economic costs associated with climate change in the built environment will result from shifts in the frequency and severity of extreme events. In this study, the consequences of the climate change scenarios on the design wind speeds used in building regulations are discussed. Based on the best actual available knowledge of climate change models, the effect of climate change implies a change of −0.8% to +2.3% in the hourly mean wind speed with return period of 50 years, which is the basis of current building codes. To confirm the outcomes, further development of climate change scenarios is needed with more focus on extreme events with large return periods and small time scales. Natural variability of wind speed appears to have a great effect on wind trends for extreme wind velocities, and when adapting values for extreme climatic effects in building codes, both climate change effects and effects of natural variability should be considered. The analysis as presented for extreme wind speeds can be applied to other domains, such as thermal and precipitation where extreme values of climatic conditions define building design, and can therefore serve as general framework to assess extreme events.