Wind Energy Resource Assessment Research Articles

Wind energy resource assessment and wind turbine selection analysis for sustainable energy production

The objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO2 emission intensity factor (kg CO2/kWh) of the national electricity system.

Analysis of wind characteristics and wind energy resource assessment for Tonga using eleven methods of estimating Weibull parameters

Analysisof wind characteristics and assessment of wind energy resource is carried out at a location in Tonga with the help of twelve months of measurements carried out at 34 m and 20 m heights above ground level. The daily, monthly and annual averages are computed. The wind shear analysis and its diurnal variation were studied and compared with the temperature variation. The turbulence levels at the two heights were estimated for the entire measurement period as well as for some typical days. For estimating the Weibull parameters, eleven methods were employed along with goodness of fit and error estimates to find the best method. The overall averaged wind speed for the entire period of study is estimated to be 4.41 m/s at 34 m above ground level. The predominant wind direction was south-east for Tonga. ‘Moments’ is seen to be the best method to determine accurate Weibull parameters. The average net annual energy production from one Vergnet 275 kW wind turbine is 198.57 MWh. A payback period of 8.95 years by installing five turbines near the measurement location was estimated, which is very encouraging in terms of investment. Installing wind turbines will lower the heavy reliance on the imported fossil fuels in the country and also help in achieving Sustainable Development Goal 7.

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed > 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

Distribution characteristics and assessment of wind energy resources in the coastal areas of Guangdong

In order to improve the efficiency, availability and economy during construction and operation of wind farms, characteristic analysis and evaluation of the regional wind energies are key components. In this paper, wind energy resource evaluation was conducted for coastal areas of Guangdong, including spatial and seasonal characteristics and overall evaluation. Results indicate that: ① Effective wind speed frequency is the highest in the seaward area of the study area, followed by the excessive area and the lowest in the landward area. The seaward area is relatively suitable for wind energy development. ② Total theoretical exploitable area in the study area is 5.15×105 MW, and the high production area is mainly concentrated in the outer sea areas. Developable areas are in the nearshore areas, and the potential development areas are in the sea-land interface and estuary areas. Annual effective wind energy density values along the coast of eastern Guangdong are larger than that of western Guangdong. Its development potential is larger than that of western Guangdong. ③ Wind energy variation coefficient has significant seasonal differences. Wind energy density in winter and spring is more stable than that in summer and autumn. Additionally, overall seasonal variation index is smaller, which can provide stable wind energy.

Spatiotemporal variation of power law exponent on the use of wind energy

The power law, a common method in wind energy assessments, often assumes a global power law exponent (α) of 1/7, potentially leading to inaccuracies in estimating wind conditions and energy potential. This study uses high-frequency measurements from eight wind towers to assess the power law's reliability and demonstrates its general applicability, except in complex topography. The α value is found to differ significantly from 1/7 in validation sites, yet it can be reliably used in ERA5 data based on regional verification. To evaluate the global spatiotemporal variation of α, we analyze the hourly α from 1980 to 2022 using ERA5 wind speed data at 10 m and 100 m. Our findings reveal varying α value with time and geography, with particular disparities between land and ocean. Additionally, we observe changes related to diurnal cycles, seasons, and latitudes. This analysis of α value carries significant implications for a global-scale wind energy resource assessment, site selection, and turbine design.

Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations

Urban wind power is an appealing alternative for electricity supply. Comprehensive urban wind resource assessment is a prerequisite for cost-efficient deployment of wind turbines. Based on observations from multiple instruments, including a Doppler lidar (light detection and ranging) system, a microwave radiometer, and a cup anemometer/wind vane set, this study investigates the temporal (interannual, seasonal, and diurnal) variations of wind resources at various heights in a metropolitan city, Hong Kong. The long-term statistical distributions of wind speed, wind shear coefficient, and air density are analyzed, and their variations with height, wind direction, season, and time of day are thoroughly examined. Moreover, the wind power density and capacity factor of prototype wind turbines are estimated. It is observed that the statistical distributions of wind speed and air density are best represented by the Kappa and Normal-Weibull mixture distributions, respectively. There is a significant diurnal variation of wind shear coefficient, from 0.1 in the daytime to 0.4 at night. Moreover, a moderate potential for wind energy harvesting with wind power density of 110 W/m2 is found at the height of 120 m. This is the first known study that jointly uses lidar, microwave radiometer, and anemometer/wind vane for urban wind resource assessment. These instruments enable the investigation of the temporal variations of wind shear coefficient, air density, and wind power density at multiple heights, which were rarely examined in urban wind energy studies before.

Wind energy resource assessment based on the use of multiple satellite data for sustainable energy production in Sudan

Wind energy resource assessment based on the use of multiple satellite data for sustainable energy production in Sudan

Temporal assessment of wind energy resource in algerian highlands regions

The aim of this paper is to investigate the monthly, seasonal and annual variation of the wind resource in term of wind energy potential using the wind speed data collected in the last decade for the meteorological stations at four locations situated in Algerian highlands from East to West boundaries. After the study of temporal Weibull parameters, the vertical extrapolation of Weibull parameters and mean wind speed at a height of 50 m was made and the analysis of annual energy efficiency, seasonal and monthly was made for wind energy conversion systems of 600 kW rated capacity. The results show that M’Sila has the highest wind potential among the studied sites with the annual mean wind speed V = 4 m/s and the annual wind energy production equal to 2.4GWh/year, while Kasr Chellala gives a good potential too but affected by an important rate of zero wind frequency. The study gives the regions situated in Algerian highland with an average wind potential, where the better wind energy potential is given in coldest months.

Integration of atmospheric stability in wind resource assessment through multi-scale coupling method

The abundance level of wind resources is the first and most important factor to consider in the wind farm design. The accuracy of wind energy resource assessment directly determines the operating income of a wind farm after its construction is completed. Therefore, aiming to meet the requirements of accurate wind resource assessment in areas with a complex terrain or those lacking the observation information, this paper proposes a multi-scale coupling numerical simulation method based on atmospheric stability. First, the atmospheric flow field simulation results at the heights of 200 m, 300 m, and 400 m are extracted from the mesoscale Weather Research and Forecasting (WRF) model and used as inlet boundary conditions of a microscale Computational fluid dynamics (CFD) model. Then, to obtain more accurate coupling data at the height of a wind turbine hub, the atmospheric stability parameter is introduced into the multi-scale coupling process, data correction is conducted at the three heights, and a comparison with the observation data of a wind tower is made. Finally, a numerical analysis is conducted using real data of a wind farm in eastern Inner Mongolia and Jilin. The analysis results show that the proposed method can improve the assessing accuracy of wind resources of wind farms using mesoscale data, which is valuable to a certain extent in real-world applications.

A wind speed forecasting model based on multi-objective algorithm and interpretability learning

More accurate and reliable wind speed forecasting results can provide an effective assessment of wind energy resources and improve the efficiency of wind energy utilization. Therefore, this paper is devoted to constructing accurate wind speed forecasting models and quantitatively analyzing the models by using interpretable analysis. Firstly, a multivariate wind speed forecasting model (PMI-CMOGSA-RELM) is proposed based on machine learning methods and a clustering-based multi-objective gravity search algorithm (CMOGSA). Among them, wavelet packet decomposition (WPD) is used for noise reduction, candidate input feature pool and partial mutual information (PMI) are used for feature selection, and CMOGSA is used to optimize the final combined weights. Secondly, a new evaluation metric, Absolute Error Coverage Probability (AECP), is proposed to better evaluate forecasting accuracy. Then, post-hoc attribution analysis methods and visualization tools are used to analyze the forecasting model interpretability to help us better analyze the robustness and reliability of the forecasted results. Finally, this paper validates and evaluates the proposed model with two data sets of different resolutions. The experimental results not only prove the rationality of the AECP evaluation criteria, but also demonstrate that the proposed model has smaller errors, higher estimation accuracy, and is easier to understand.

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

A multi‐criteria methodology for wind energy resource assessment and development at an intercontinental level: Facing low‐carbon energy transition

A multi‐criteria methodology for wind energy resource assessment and development at an intercontinental level: Facing low‐carbon energy transition

Wind energy resources assessment of Cuba using the regional climate model PRECIS in high resolution scenarios of climate change RCPs

An analysis of the behavior of the wind speed using the regional climate model PRECIS in high resolution scenarios of climate change RCPs is presented. The projections indicate that throughout the century, the speed of the surface wind will continue to increase to a greater or lesser extent (depending on the scenario) in most of the national territory, mainly towards the coast north, as an intensification and westward shift of the anticyclone North Atlantic could occur. The most important thing about this increase is that allows to consolidate the current projection of the Cuban wind program, in which the construction of 13 wind farms is proposed, precisely where the wind potential of Cuba will be increased. Finally this increase is added to the wind speed outputs of the Numerical Wind Atlas of Cuba to estimate the values of wind speed over the future periods.

Assessment of Wind Energy Resources in Jordan Using Different Optimization Techniques

Wind energy has become one of the world’s most renewable energy sources in recent years. It is regarded as a clean energy source because it produces no greenhouse gas emissions. The assessment of wind energy resources is an important step in the development of any wind energy conversion system (WECS). As a result, this article examines the wind energy potential of nine Jordanian wind locations: Queen Alia Airport, Civil Amman Airport, King Hussein Airport, Irbid, Mafraq, Ma’an, Ghor Al Safi, Safawi, and Irwaished. The available wind speed data were implemented using three statistical distribution models, Weibull, Rayleigh, and Gamma distributions, and one traditional estimation method, the Maximum Likelihood Method (MLM). Three optimization techniques were used to assign parameters to each distribution model: Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). To determine the optimal distribution model, the performance of these distribution models was tested. According to the findings, King Hussein Airport features the highest wind power density, followed by Queen Alia Airport, while Irbid features the lowest, followed by Ghor Al Safi.

Wind Energy Resource Assessment for Cook Islands With Accurate Estimation of Weibull Parameters Using Frequentist and Bayesian Methods

Wind energy resource assessments at two islands in the Cook Islands are carried out in the present work. The wind data were collected for one year from sites on Mauke and Rarotonga Islands in the Cook Islands and the daily, monthly and seasonal average wind speeds, the diurnal variations of the wind shear coefficient, average temperature and turbulence intensity were estimated. Eleven frequentist methods and a Bayesian technique were used to determine the Weibull parameters and the wind power density (WPD) for each site. The best method was determined using the goodness of fit test and error measures. The average wind speeds were 4.65 m/s and 3.86 m/s at 34 m above ground level for the sites on Mauke and Rarotonga respectively. Based on the goodness of fit tests and error measures, the Least Squares Method performed best for estimating the Weibull parameters at the Mauke site, while for the Rarotonga site, the median and quartiles method performed the best. For both the sites, the Bayesian method, which is being used for the first time for wind resource assessments, ranked second of the twelve methods, indicating good potential for this method. The annual energy production (AEP) was also determined which was calculated to be 2192.34 MWh from a total of ten Vergnet 275 kW turbines at the two sites. Finally, an economic analysis, carried out for the two sites, indicated a payback period of 7.72 years.

Imdaa Regional Reanalysis: A New Source of Information for Wind and Solar Energy Resource Assessment Over India

Imdaa Regional Reanalysis: A New Source of Information for Wind and Solar Energy Resource Assessment Over India

Calculation and Application of Important Parametersin Wind Energy Resource Assessment of Wind Farm Based on T-S Fuzzy Linearization

Calculation and Application of Important Parametersin Wind Energy Resource Assessment of Wind Farm Based on T-S Fuzzy Linearization

Solar energy available and energy generated in photovoltaic systems in different inclinations and orientations of roofs of buildings

This work aimed to determine the solar energy available in different inclinations and orientations of roofs of buildings in the four seasons, using data of Global Solar Irradiation in the horizontal plane, temperatures, and wind speed. The inclined hourly solar irradiation and the energy generated by photovoltaic systems of different capacities installed in Cascavel-PR were simulated, with different orientations and inclinations and types of roofs (ceramic, fiber cement and metal). SWERA (Solar and Wind Energy Resource Assessment) daily global solar irradiation and wind velocity data were used to simulate daily inclined global solar irradiation in PVSyst software. Thus, also with the help of the software, the energy generated by photovoltaic systems of different capacities installed in Cascavel - PR, with different orientations and inclinations of roofs was determined. Consequently, the levels of losses in different seasons of the year were calculated and an analysis of the economic viability of the undertakings was made. Thus, the losses, profits and income of the systems were compared. Solar panels installed in northern oriented ceramic roofs provide better energy production performance throughout the year compared to metallic roofs and fibrocement. However, for the other orientations (South, East and West), the losses for ceramic roofs were twice as high as the metallic and fibrocement roofs in relation to their respective northern orientated slopes. Regarding orientation, roofs oriented to the North receive more Irradiation annually and therefore produce more energy. Then there is East, West and South as the most unfavorable condition.

Future wind and wave energy resources and exploitability in the Mediterranean Sea by 2100

A state-of-the-art regional assessment of future wind and wave energy resource in the Mediterranean Sea and the projected changes with respect to hindcast is presented. A multi-model EURO-CORDEX ensemble of future wind field and wave climate conditions with a spatial resolution of ≈10–12.5 km and 3–6 h temporal resolution in the Mediterranean Sea is used for the assessment of future changes wind power, wave energy and combined exploitability under the climate change scenario RCP8.5. The results allow to identify climate change impacts in wind and wave power potential and the projected changes in the locations in the Mediterranean basin that were considered suitable for joint exploitations in previous studies. The future ES-Index allows to assess the optimized temporal-availability of combined wind and wave resources in a changing climate. Results show a robust decrease in the ES-Index during fall and winter in regions previously identified as suitable for coupled systems which would reduce the overall energy extraction but also attenuate the seasonal fluctuation. In addition, the Alboran Sea presents increases in ES-Index emerging as a probable suitable area for coupled systems under RCP8.5.

Wind energy resource assessment for Mukdahan, Thailand

ABSTRACT The generation of electricity from wind energy can reduce the fossil sources imported and carbon dioxide emissions. The wind is free, clean, and green energy. This study aims to present a wind energy assessment for Mukdahan site of Thailand. The wind speed at heights of 60, 90, and 120 m above ground level was measured from January 1st, 2012 to December 31st, 2017. The annual mean wind speeds were 3.59, 4.02, and 4.51 m/s at 60, 90, and 120 m AGL, respectively. The majority of wind directions were contributed by the monsoon for this region. The Wind Atlas Analysis and Application Program (WAsP) was used to predict the Annual Energy Production and Capacity Factor for five selected wind turbines in a capacity range of 0.85 − 3.30 MW. Moreover, the high-resolution wind resource map also indicated the high potential for wind around the site. The low cut-in speed and high hub-height wind turbines such as VestasV110-2.0 MW and V126-3.3 MW can produce higher energy output, capacity factor and better cost of energy, especially when the wind turbine site is located on the ridges and peaks of hills around the site. The best cost of energy was 0.030 USD/kWh, which was observed for the V110 wind turbine and the second best was 0.041 USD/kWh for the V126 wind turbine, especially when considering placement on the peak of a hill. The important data from this study can be developed for wind farm project installation and suitable wind turbine design for the whole local region.