Wind energy resource assessment for the Fiji Islands: Kadavu Island and Suva Peninsula

Wind energy assessment of two sites in the Fiji Islands is presented. The wind resource of the remote island of Kadavu is analysed along with the urban Suva Peninsula. The former has average (mean) wind speeds of 3.59 ms⁻¹and 3.88 ms^-1 at 20 m and 34 m above ground level (AGL). The latter has average wind speeds of 5.65 ms^-1 and 6.38 ms^-1, respectively. The prevailing wind direction for both the sites corresponds to the South-East winds. A wind shear analysis shows the variations in wind speeds during different periods of the day for the Suva site. A high resolution wind resource map of both the sites is simulated using the WAsP software for a radius of 5 km. The WasP analysis indicates good wind power development potential for Kadavu is for the windward side of the Kadavu ridge in the eastern region. The Suva Peninsula site showed good wind power development potential for the Laucala Bay area. A power analysis using the Vestas V27 225 kW turbine is carried out for the specific sites.     

Adequacy assessment of generating systems containing wind power considering wind speed correlation

Wind power is an important renewable energy resource. Electrical power generation from wind energy behaves quite differently from that of conventional sources, and maintaining a reliable power supply is an important issue in power systems containing wind energy. In these systems, the wind speeds at different wind sites are correlated to some degree if the distances between the sites are not very large. Genetic algorithm methods are applied here to adjust autoregressive moving-average time series models in order to simulate correlated hourly wind speeds with specified wind speed cross-correlation coefficients of two wind sites. Multi-state wind energy conversion system models are used to incorporate the correlated wind farms in reliability studies of generating systems. A method to generate random numbers with specified correlation coefficients for application in a state-sampling Monte Carlo simulation technique is introduced. It is shown that the proposed method can be used in the adequacy assessment of a generating system incorporating partially dependent wind farms.     

The potential of electricity generation on the east coast of Red Sea in Egypt

Wind characteristics have been analyzed based on long-term measured data of monthly mean wind speed of seven meteorological stations along the east coast of Red Sea in Egypt. It was found that the windiest stations (Region A) namely (Zafarana, Abu Darag, Hurghada and Ras Benas) have annual mean wind speeds (7.3, 7.2, 6.4 and 5.5 m/s) at 10 m height, respectively.Numerical estimations using measured wind speeds and frequencies to calculate the two Weibull parameters were carried out and two methods were applied.The methodical analysis for the corrected monthly wind power density at a height of 10 m above ground level, over roughness class 0 (water), for each station was done. The recommended correlation equation was also stated for Red Sea zone in Egypt. Also the corrected annual wind power density at the heights (50–70) m was obtained for all stations. Moreover, calculations show that the four stations in (Region A) have a huge energy potential available (430–1000 W/m²) at 70 m height, while Quseir and Suez stations (Region B) have good wind power density (170–190 W/m²) at 50 m height.A technical and economic assessment has been made of electricity generation from two turbines machines having capacity of (1000 and 600 kW) considered in Regions A & B, respectively, using WASP program. The yearly energy output, capacity factor and the electrical energy cost of kWh produced by the two different turbines in each region were estimated. The production costs of four stations in Region A was found to be less than 2€ cent/kWh and compared with retail tariff.     

Airborne wind energy: Optimal locations and variability

This paper explores the global wind power potential of Airborne Wind Energy (AWE), a relatively new branch of renewable energy that utilizes airborne tethered devices to generate electricity from the wind. Unlike wind turbines mounted on towers, AWE systems can be automatically raised and lowered to the height of maximum wind speeds, thereby providing a more temporally consistent power production. Most locations on Earth have significant power production potential above the height of conventional turbines. The ideal candidates for AWE farms, however, are where temporally consistent and high wind speeds are found at the lowest possible altitudes, to minimize the drag induced by the tether. A criterion is introduced to identify and characterize regions with wind speeds in excess of 10 m s⁻¹ occurring at least 15% of the time in each month for heights below 3000 m AGL. These features exhibit a jet-like profile with remarkable temporal constancy in many locations and are termed here “wind speed maxima” to distinguish them from diurnally varying low-level jets. Their properties are investigated using global, 40 km-resolution, hourly reanalyses from the National Center for Atmospheric Research's Climate Four Dimensional Data Assimilation, performed over the 1985–2005 period. These wind speed maxima are more ubiquitous than previously thought and can have extraordinarily high wind power densities (up to 15,000 W m⁻²). Three notable examples are the U.S. Great Plains, the oceanic regions near the descending branches of the Hadley cells, and the Somali jet offshore of the horn of Africa. If an intermediate number of AWE systems per unit of land area could be deployed at all locations exhibiting wind speed maxima, without accounting for possible climatic feedbacks or landuse conflicts, then several terawatts of electric power (1 TW = 10¹² W) could be generated, more than enough to provide electricity to all of humanity.     

Data efficient measure-correlate-predict approaches to wind resource assessment for small-scale wind energy

The feasibility of predicting the long-term wind resource at 22 UK sites using a measure-correlate-predict (MCP) approach based on just three months onsite wind speed measurements has been investigated. Three regression based techniques were compared in terms of their ability to predict the wind resource at a target site based on measurements at a nearby reference site. The accuracy of the predicted parameters of mean wind speed, mean wind power density, standard deviation of wind speeds and the Weibull shape factor was assessed, and their associated error distributions were investigated, using long-term measurements recorded over a period of 10 years. For each site, 120 wind resource predictions covering the entire data period were obtained using a sliding window approach to account for inter-annual and seasonal variations. Both the magnitude and sign of the prediction errors were found to be strongly dependent on the season used for onsite measurements. Averaged across 22 sites and all seasons, the best performing MCP approach resulted in mean absolute and percentage errors in the mean wind speed of 0.21 ms⁻¹ and 4.8% respectively, and in the mean wind power density of 11 Wm⁻² and 14%. The average errors were reduced to 3.6% in the mean wind speed and 10% in the mean wind power density when using the optimum season for onsite wind measurements. These values were shown to be a large improvement on the predictions obtained using an established semi-empirical model based on boundary layer scaling. The results indicate that the MCP approaches applied to very short onsite measurement periods have the potential to be a valuable addition to the wind resource assessment toolkit for small-scale wind developers.     

Wind characteristics and energy potentials for Owerri, Nigeria

Wind characteristics and wind energy resource potentials for Owerri, Nigeria are presented. These were evaluated using routine wind data measurements at a height of 10 m above ground level at the Lake Nwebere Campus, Federal University of Technology, Owerri between 1988 and 1992. The most prevailing wind is from the Southwest and the average wind speed and its variation are 2.80 and 0.81 m s⁻¹, respectively.Accordingly, the maximum annual mean power density exploitable from the wind at this site is 7.66 ± 0.15 W m⁻² out of the estimated available annual mean wind power density of 12.91 ± 0.26 W m⁻². The annual mean energy density available in the wind was found to be 60.29 kW h m⁻². Thus, the potential for year-round wind energy utilization in Owerri, Nigeria is rather low.     

Thermodynamic analysis of wind energy

Wind energy is assessed thermodynamically, from resource and technology perspectives. The thermodynamic characteristics of wind are considered. Wind speed is affected by air temperature and pressure and has an effect on wind turbine performance, based on wind chill effect and Bernoulli's equation. The wind chill effect leads to temperature differences that suggest enthalpy and entropy components must be considered in a thermodynamic analysis. The wind pressure effect based on Bernoulli's equation affects the entropy of wind. These components have not previously been considered in evaluations of wind turbine efficiency for electricity generation. A new efficiency formula for wind energy systems is described, which provides important information about the system. It is seen that average differences between energy and exergy efficiencies are approximately 40% at low wind speeds and up to approximately 55% at high wind speeds. Copyright © 2005 John Wiley & Sons, Ltd.     

基于成本模型法的1MW变速风电机组的参数优化设计分析

主要针对大型变速变距风力发电机组样机在产业化过程中如何以降低机组发电成本、提高经济性为目标对机组参数的优化设计进行探讨。首先阐述了发电成本的计算过程和成本模型法的基本计算规则,然后以国家863"兆瓦级变速恒频风电机组"研制成果SUT-1000的成本构成为例,分别对机组的主要设计参数即风轮直径和额定风速进行了优化设计和对比,并对依据经验确定的变化因子进行了敏感性分析,最后进行了同等容量约束条件下机组的参数综合优化设计,可适用于不同安装场址。     

A GIS based assessment of potential for windfarms in India

The Wind Energy Potential for India has been assessed, assuming as if the whole of the country (apart from the urban and the Himalayan areas) is covered with windfarms, by an innovative approach using GIS platform, wind speed measurements under government’s program and the NCEP/NCAR Reanalysis data.¹ The methodology involves setting up a grid of 1 sqkm resolution over areas other than urban settlements and Himalayan regions, computation of wind speeds at boundary layer level through vertical extrapolation of known or measured mean annual wind speed and interpolation of the extrapolated wind speeds to arrive at a mean annual wind field at boundary layer level and then computation of wind speed at the hub-height of the wind turbine. Power output from a standard wind turbine is computed and only areas showing a Plant Load Factor (PLF) higher than 15% are considered in the potential assessment. The results of this exercise indicate the potential for windfarms in India to be significantly higher than what was assumed earlier. The analysis and its revalidation using data measured at varying heights in different parts of the country establishe this approach as useful and perhaps a powerful tool to undertake wind resource potential assessments. This analysis and the results are discussed in the backdrop of the general energy scenario in India and earlier assessments of wind potential in the country.     

Low wind speed turbines and wind power potential in Minnesota, USA

Wind power development in Minnesota largely has been focused in the “windy” southwestern part of the state. This research evaluates the additional power that potentially could be generated via low wind speed turbines, particularly for areas of the state where there has been comparatively little wind energy investment. Data consist of 3 years (2002–2004) of wind speed measurements at 70–75 m above ground level, at four sites representing the range of wind speed regimes (Classes 2–5) found in Minnesota. Power estimates use three configurations of the General Electric 1.5-MW series turbine that vary in rotor diameter and in cut-in, cut-out, and rated speeds. Results show that lower cut-in, cut-out, and rated speeds, and especially the larger rotor diameters, yield increases of 15–30% in wind power potential at these sites. Gains are largest at low wind speed (Class 2) sites and during the summer months at all four sites. Total annual wind power at each site shows some year-to-year variability, with peaks at some sites partially compensating for lulls at others. Such compensation does not occur equally in all years: when large-scale atmospheric circulation patterns are strong (e.g., 2002), the four sites show similar patterns of above- and below-average wind power, somewhat reducing the ability of geographic dispersion to mitigate the effects of wind speed variability.     

Evaluating the performance of wind turbines in selected locations in Oyo state,Nigeria

The wind speed distribution and wind energy potential are investigated in three selected locations in Oyo state using wind speed data that span between 12 and 20 years measured at 10 m height. In addition, the performance of selected small to medium size wind turbines in these sites were examined. The annual energy output and capacity factor for these turbines were determined. It was found that the monthly mean wind speeds in Oyo state ranges from 2.85 m/s to 5.20 m/s. While the monthly mean power density varies between 27.08 W/m² and 164.48 W/m², while the annual mean power density is in the range of 67.28 W/m² and 106.60 W/m². Based on annual energy output, wind turbines with cut-in wind speed of about 2.5 m/s and moderate rated wind speeds will be best suited for all the sites.     

On wind speed pattern and energy potential in Nigeria

The aim of this paper is to review wind speed distribution and wind energy availability in Nigeria and discuss the potential of using this resource for generation of wind power in the country. The power output from a wind turbine is strongly dependent on the wind speed and accurate information about the wind data in a targeted location is essential. The annual mean wind speeds in Nigeria range from about 2 to 9.5 m/s and the annual power density range between 3.40 and 520 kW/m² based on recent reported data. The trend shows that wind speeds are low in the south and gradually increases to relatively high speeds in the north. The areas that are suitable for exploitation of wind energy for electricity generation as well as for water pumping were identified. Also some of the challenges facing the development of wind energy and suggested solutions were presented.     

Wind energy resources in the Ionian Sea

The wind speed and direction as well as the availability, the duration and the diurnal variation of two offshore sites, Zakinthos and Pylos (BZK and BPY) in the Ionian Sea were assessed. For an analysis period of two years, the mean wind speed at 10 m was determined as 5.7 ± 0.1 m s^?1 and 5.8 ± 0.1 m s^?1 for the BZK and BPY sites, respectively. The wind speed variations over the hours of the day were quite small. The monthly variation in the average wind speeds was between 4.3 (May) and 7.5 m s^?1 (December) for the BZK site and 4.4 (August) and 7.3 m s^?1 (December) for the BPY site. Moreover, QuikSCAT satellite mean values for the grids of the two buoy regions were systematically overestimated in comparison to the buoy data with differences in the range from 8 to 13%. Statistical analysis revealed the high QuikSCAT data uncertainty for wind speeds less than 5 m s^?1 as the major factor of the observed mean value differences. The mean wind power densities were calculated with the buoy wind speed measurements and were found more than 250 W m^?2 at 10 m, suggesting the suitability of the sites for offshore wind energy applications. Capacity factors of up to 48% for energy production were calculated with the existing offshore turbines technology at a hub height of 100 m. Furthermore, the energy yield for different wind turbines and a service life of 20 years were determined from 6.5 to 8.7 and the energy pay-back periods from 2.8 to 2.1 years, respectively. The maximum avoided greenhouse emissions were 140 kt CO₂-e for an offshore turbine generator of 5 MW and a period of 20 years.     

Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by the Weather Research and Forecasting model using seven sets of simulations with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights ranging from 10 to 160 m, wind shears, temperatures and surface turbulent fluxes from seven sets of hindcasts are evaluated against observations at Høvsøre, Denmark. The ability of these hindcast sets to simulate mean wind speeds, wind shear, and their time variability strongly depends on atmospheric static stability. Wind speed hindcasts using the Yonsei University PBL scheme compared best with observations during unstable atmospheric conditions, whereas the Asymmetric Convective Model version 2 PBL scheme did so during near‐stable and neutral conditions, and the Mellor–Yamada–Janjic PBL scheme prevailed during stable and very stable conditions. The evaluation of the simulated wind speed errors and how these vary with height clearly indicates that for wind power forecasting and wind resource assessment, validation against 10 m wind speeds alone is not sufficient. Copyright © 2012 John Wiley & Sons, Ltd.     

Examining wind quality and wind power prospects on Fiji Islands

Wind resource analysis was carried out for two major islands in the Fiji. Wind data from July 1993 to June 2005 from NASA data base was analysed. Annual seasonal variation in wind speed, direction and power density were analysed for various locations. The average yearly wind speed for Fiji is between 5 and 6 m/s with average power density of 160 W/m². Site specific validation showed no significant relationship between NASA and experimental data. The wind resource at Laucala Bay has a power density of 131 W/m² at 55 m. The expected annual energy produced from a 275 kW GEV Vergnet wind turbine is 344 MWh. The capacity factor of the turbine is expected to be 14.3% with an overall efficiency of 37%. The electricity generated would cost $FJ 0.27 per kWh. The system will payback its worth in 12.2 years.     

Evaluating the impact of wind induced roughness change and tidal range on extrapolation of offshore vertical wind speed profiles

Wind energy resource estimation frequently requires extrapolation of wind speeds from typical measurement heights to turbine hub‐heights. However, this extrapolation is uncertain, and this uncertainty is exacerbated in the offshore environment by the effect of the dynamic surface (i.e. surface roughness and height respond to wind speed or vary over time). This paper examines the impact of roughness variations and small tidal ranges on mean predicted wind speeds in near‐neutral conditions. Roughness variations offshore are in the range 0.002 and 0.00002 m. This range of roughnesses gives a difference in predicted wind speed extrapolated from 10 to 50 m of less than 8%. For a more typical range of 0.0005 tp 0.00005 m, the difference will be smaller (～3%). With a tidal range of 4 m the difference in mean wind speed extrapolated from 10 to 50 m height is about 1%. Copyright © 2001 John Wiley & Sons, Ltd.     

The influence of the wind speed profile on wind turbine performance measurements

To identify the influence of wind shear and turbulence on wind turbine performance, flat terrain wind profiles are analysed up to a height of 160 m. The profiles' shapes are found to extend from no shear to high wind shear, and on many occasions, local maxima within the profiles are also observed. Assuming a certain turbine hub height, the profiles with hub‐height wind speeds between 6 m s^?1 and 8 m s^?1 are normalized at 7 m s^?1 and grouped to a number of mean shear profiles. The energy in the profiles varies considerably for the same hub‐height wind speed. These profiles are then used as input to a Blade Element Momentum model that simulates the Siemens 3.6 MW wind turbine. The analysis is carried out as time series simulations where the electrical power is the primary characterization parameter. The results of the simulations indicate that wind speed measurements at different heights over the swept rotor area would allow the determination of the electrical power as a function of an ‘equivalent wind speed’ where wind shear and turbulence intensity are taken into account. Electrical power is found to correlate significantly better to the equivalent wind speed than to the single point hub‐height wind speed. Copyright © 2008 John Wiley & Sons, Ltd.     

Economic viability and production capacity of wind generated renewable hydrogen

Generally, wind to power conversion is calculated by assuming the quality of wind as measured with a Weibull probability distribution at wind speed during power generation. We build on this method by modifying the Weibull distributions to reflect the actual range of wind speeds and wind energy density. This was combined with log law that modifies wind speed based on the height from the ground, to derive the wind power potential at windy sites. The study also provides the Levelized cost of renewable energy and hydrogen conversion capacity at the proposed sites. We have also electrolyzed the wind-generated electricity to measure the production capacity of renewable hydrogen. We found that all the sites considered are commercially viable for hydrogen production from wind-generated electricity. Wind generated electricity cost varies from $0.0844 to $0.0864 kW h, and the supply cost of renewable hydrogen is $5.30 to $ 5.80/kg-H₂. Based on the findings, we propose a policy on renewable hydrogen fueled vehicles so that the consumption of fossil fuels could be reduced. This paper shall serve as a complete feasibility study on renewable hydrogen production and utilization.     

Wind power resource in the south-western region of Algeria

In this study, we present a statistical analysis of wind speeds at Tindouf in Algeria using Risoe National Laboratory's Wind Atlas Analysis and Application Program (WAsP). It requires information related to the sheltering obstacles, surface roughness changes and terrain height variations in order to calculate their effects on the wind. Wind data, consisting of hourly wind speed records over a 5-year period, 2002–2006, were obtained from SONELGAZ R&D Office; the average wind speed at a height of 17 m above ground level was found to range from 7.19 to 7.95 m/s. The Weibull distributions parameters (c and k) were found to vary between 8.0 and 8.9 m/s and 2.54–3.23, respectively, with average power density ranging from 318 to 458 W/m². The dominant wind directions and the frequency distributions were also determined.     

A method for mapping the turbulence intensity and excess energy available to building mounted wind turbines over a UK City

Assessing the potential of proposed urban wind installations is hindered by insufficient assessments of both urban wind resource, and the effectiveness of commercial gust control solutions within built up areas. Evaluating the potential performance of wind turbines within the urban environment requires an estimation of the total energy that would be available to them were effective control systems to be used. This paper presents a methodology for estimating the excess energy content (EEC) present in the gusty urban wind, which is usually under represented when using assessments based only on mean wind speeds. The method is developed using high temporal resolution wind measurements from eight potential turbine sites within the urban and suburban environment. By assessing the relationship between turbulence intensities and the EEC, an analytical methodology for predicting the total wind energy available at a potential turbine site is proposed. Sensitivity analysis with respect to temporal data resolution on the predicted EEC is also demonstrated. The methodology is then integrated with an analytical methodology that was initially developed to predict mean wind speeds at different heights within a UK city based on detailed mapping of its aerodynamic characteristics. Additional estimates of turbulence intensities and EEC based on the current methodology allow a more complete assessment of the wind resource available. The methodology is applied to the UK city of Leeds as a case study and the potential to map turbulence intensities and the total kinetic energy available at different heights within a typical urban city is demonstrated. Copyright © 2015 John Wiley & Sons, Ltd.