Assessment Of Wind Energy Potential Research Articles

A comprehensive assessment of wind energy potential and wind farm design in a coastal industrial city

Purpose Jubail Industrial City is one of the largest industrial centers in the Middle East, offering potential opportunities for renewable energy generation. This research paper presents a comprehensive analysis of the wind resources in Jubail Industrial City and proposes the design of a smart grid-connected wind farm for this strategic location. Design/methodology/approach The study used wind data collected at three different heights above ground level – 10, 50 and 90 m – over four years from 2017 to 2020. Key parameters, such as average wind speeds (WS), predominant wind direction, Weibull shape, scale parameters and wind power density (WPD), were analyzed. The study used Windographer, an exclusive software program designed to evaluate wind resources. Findings The average WS at the respective heights were 3.07, 4.29 and 4.58 m/s. The predominant wind direction was from the north-west. The Weibull shape parameter (k) at the three heights was 1.77, 2.15 and 2.01, while the scale parameter (c) was 3.36, 4.88 and 5.33 m/s. The WPD values at different heights were 17.9, 48.8 and 59.3 W/m2, respectively. Originality/value The findings suggest that Jubail Industrial City possesses favorable wind resources for wind energy generation. The proposed smart grid-connected wind farm design demonstrates the feasibility of harnessing wind power in the region, contributing to sustainable energy production and economic benefits.

Outlook for Offshore Wind Energy Development in Mexico from WRF Simulations and CMIP6 Projections

This study presents a comprehensive assessment of the offshore wind energy potential in Mexico across 40 years (1979–2018) of numerical simulations using the Weather Research and Forecasting (WRF) model and data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The WRF identifies three regions with moderate to good wind potential: off the north coast of Tamaulipas (Zone I), the northwest coast of Yucatan (Zone II), and the Gulf of Tehuantepec (Zone III). The analysis involves comparing 47 CMIP6 climate models with the WRF results and selecting the best performing models to obtain future projections for the short term (2040–2069) and the long term (2070–2099). Two ensemble-based strategies were implemented. The first one, which uses an intersection approach from which four CMIP6 models were considered, reveals positive percentage differences in Zone II for both future projections, especially for the long-term one. In Zones I and III, positive values are also observed near the coast, mainly for the long-term projection, but they are considerably lower compared to those in Zone II. The second ensemble strategy uses weight assignment through the Mean Absolute Percentage Error, so that a greater weight is given to the model that performed better in each particular zone, potentially providing more accurate results. The findings suggest the likelihood of increased offshore wind energy in these three zones of Mexico, for both short- and long-term future projections, with positive percentage differences of up to 10% in certain areas.

Comprehensive onshore wind energy assessment in Malawi based on the WRF downscaling with ERA5 reanalysis data, optimal site selection, and energy production

Malawi, despite its minimal CO2 emissions, faces huge climate impacts and a low electrification rate. Recognizing these challenges, this study presents a comprehensive and nationwide assessment of Malawi's wind energy potential, leveraging the high-resolution capabilities of the Weather Research and Forecasting (WRF) model. Unlike most site-specific studies, this study covers the entire country, factoring in different turbine hub heights. Through sensitivity analysis, the optimal configuration for the WRF model in Malawi was determined and ERA5 reanalysis data was used for initial and boundary conditions. The study's findings were validated using MERRA-2 reanalysis and actual observational datasets. A combination of GIS and the fuzzy analytic hierarchy process (AHP) was employed, integrating key factors like land use and topographical complexity to determine optimal wind farm sites. Notably, the wind suitability map uncovered significant potential for wind farm development. Furthermore, in the evaluation of a 50 MW wind farm, 80 m hub heights consistently outperformed 100 m elevations, both technically and economically. An 80 m wind farm at Site A can potentially power up to 32,931 urban and 84,475 rural households. Economically, 80 m hub heights showcased lower levelized cost of electricity (LCOE) values and faster payback periods than 100 m ones. Furthermore, these proposed wind projects can markedly reduce CO2 emissions, positioning Malawi in tandem with global sustainability aspirations. Overall, this study provides a key foundation for Malawi's renewable energy strategies, highlighting the potential for improved electrification and better climate change mitigation outcomes.

Assessment of wind and wave energy potential along the Indian coast

Assessment of wind and wave energy potential along the Indian coast

Assessment of wind energy potential in Zambia

An assessment of potential for wind energy in Zambia was carried out to help address the shortage of energy due to increasing energy needs arising from energy requirements for newly opened mining industries and unreliable hydropower generation due to climate change. The assessment was carried out by collecting wind speed data of 25 sites owned by Zambia Meteorological Department. The objective of the study was to analyse wind patterns and determine areas in Zambia where production of electricity from wind can be invested. The analysis was based on the use of Weibull shape factor and yielded 3.32 m/s wind speed and 13.2 shape factor from a site with the most suitable wind speeds (Kasama Meteorological Station). A correlation study was carried out using these results and Goldwin 1.5 MW wind turbine of model GW82/1500. The study results showed that 44.46 kW power output could be obtained at 3.83 m/s wind speed by a correlation equation of this turbine power output with wind speeds. A series of similar power output results were obtained for wind speeds recorded in the years from 2013 to 2021 and compared with those obtained in the same period by using model equation due to Al Buhariri, and found that the power outputs compared very closely at low wind speeds ranging 3 to 3.2 m/s but rather widely at higher wind speeds.This study is significant in that it provides information on decision making and helps determine policy direction for wind utilization in Zambia and it can also help influence investment decision by Zambian mining companies who have financial ability to undertake large scale investments.

Wind energy potential assessment: a case study in Central India

Access to sustainable energy is important for economic development and environmental protection. The shift towards renewable energy is essential for mitigating climate change and ensuring long-term energy sustainability. Though developing nations possess significant renewable energy capacity, transitioning to renewable sources remains a challenge. India's expanding wind energy sector has the potential to lower carbon dioxide emissions and produce energy in a sustainable manner. This research uses the Windographer software to conduct a comprehensive analysis of the wind energy potential at a distinct site in Nagpur, India. The assessment includes monthly average wind speeds, wind rose diagrams that show the prevailing wind directions, and wind power density (WPD) calculations. These factors together establish the site's classification. In this study, Weibull parameters are derived using four distinct methods to estimate the probability distribution function. The average WPD is found to be 13.63 and 71.08 W/m2 at heights of 10 and 100 m above ground level, respectively. Through wind turbine output analysis, numerous turbine models are assessed for suitability at the specified location. The Windtec DD 3000-125 model, interestingly, has a maximum capacity factor of 9.27%. The results highlight comparatively low wind potential in the studied region. Nevertheless, a wind turbine at this location can produce about 2 412 379 kW of electricity annually using the aforementioned wind turbine model.

THE COMPARISON SOME EXTENDED WEIBULL DISTRIBUTION (WEIBULL (W), EXPONENTIATED WEIBULL (EW), EXPONENTIATED EXPONENTIAL WEIBULL (EEW) AND ADDITIVE WEIBULL (AW)) FOR THE WIND SPEED PROBABILITY MODELLING

Accurate wind speed modeling is critical in estimating wind energy potential for harnessing wind power effectively. One of the bases for assessment of wind energy potential for a specified region is the probability distribution of wind speed, therefore wind speed data is needed to produce statistical modeling, especially in determining the best probability distribution. For this purpose, several modified weibull distributions will be used and tested to determine the best model to describe wind speed in Pekanbaru. The main goal of this study is to find the best fitting distribution to the daily wind speed measured over Pekanbaru region for the years 1999-2020 by using the four modified weibull distributions, namely Weibull (W), Exponentiated Weibull (EW), Additive Weibull (AW) and Exponentiated Exponential Weibull (EEW). The maximum likelihood method will be used to get the estimated parameter value from the distribution used in this study. Furthermore, the graphical inspection (density-density plot and cumulative plot) and numerical criteria (Akaike’s information criterion (AIC), Bayesian Information Criteria (BIC), - log likelihood (- l) ) were used to determine the best fit model. In most cases, the results produced by the graphical inspection were similar, and differed from the numerical criteria . The best fit result was chosen as the distribution with the lowest values of AIC, BIC and - l. In general, the Exponentiated Exponential Weibull (EEW) distribution has been selected as the best model.

A geospatial integrated multi-criteria approach for assessment of solar and wind energy potentials with economic and environmental analysis

India has made an international commitment to generate about 50% of its total energy needs from renewable energy sources by 2030. Here, to meet such a commitment, this study developed high-resolution (1 × 1 km2) geospatial solar and wind geographical potential maps with an aim to calculate the theoretical and technical potentials with economic and environmental sustainability. These geographical potential maps are developed by taking into account 13 evaluation and restriction factors pertaining to technical, economic, and socio-environmental categories. The investigation identifies that Rajasthan, Karnataka, and Gujarat have a plurality of extremely favorable land areas for solar and wind energy sources. Furthermore, the results imply that appropriate planning for the installation of renewable projects at the identified optimum locations can fulfill India's commitments with regard to an optimal energy mix scenario, with energy available twice the available potential for consumption in 2030. Furthermore, with the least average levelized cost of energy of 38.8 $/MWh (2.83₹/kWh) and 42.3 $/MWh (3.09₹/kWh), solar and wind energy sources are potentially more appealing and affordable than conventional energy sources. The findings of this study will also significantly advance India's attempts to accept and develop renewable energy sources, helping to realize the government's objective for sustainable electricity production.

Assessment of offshore wind energy potential on the Syrian
 coast based on mathematical modeling in a GIS environment

Assessment of offshore wind energy potential on the Syrian
 coast based on mathematical modeling in a GIS environment

Statistical analysis of wind speed distribution based on sixWeibull Methods for wind power evaluation in Garoua, Cameroon

Wind data analysis and accurate wind energy potential assessment are critical factors for suitable development of wind power application at a given location. This paper explores wind speed distribution to select the two-parameter Weibull methods that provide accurate and efficient estimation of energy output for Wind Energy Conversion Systems (WECS).The dimensionless shape parameter k and the scale parameter C are determined based on measured hourly mean wind speed data in times-series from 2007 to 2012, collected at the Garoua International Airport, main meteorological station, in Garoua, Cameroon. Six numerical methods, namely Empirical Method (EM), Energy Pattern Factor method (EPF), Graphical Method (GM), Maximum Likelihood Method (MLM), Moment Method (MM) and Modified Maximum Likelihood Method (MMLM) are examined to estimate the Weibull parameters. To analyze the efficiency of the methods and to ascertain how closely the measured data follow the Weibull methods, goodness of fit tests were performed using the chi-square test (X2), correlation coefficient (R2), root mean square error (RMSE) and Kolmogorov-Smirnov test (KOL). The results revealed that the EPF followed by the MM were the most accurate and efficient methods for determining the value of C and k to approximate wind speed distribution. The statistical tests rejected the GM as an adequate method and revealed as well that the EM, MLM and MMLM ranked respectively third, fourth and fifth. Furthermore, the potential for wind energy development in Garoua is not fitted for generating electricity and a very fruitful result would be achieved if windmills were installed for producing community water supply, livestock watering, and farm irrigation.

Assessment of wind energy potential within through-building openings under twisted wind flows

Integrating wind turbines into high-rise buildings can generate renewable energy on-site. Through-building openings can effectively increase the utilization of wind energy in high-rise buildings. However, current research on wind energy potential within these openings is limited to conventional wind conditions. Meteorological observations indicate that cities near mountainous terrain, such as Hong Kong and Tokyo, often experience twisted wind flows due to topography. These wind flows cause changes in the wind direction angle with increasing vertical height, and previous studies have demonstrated significant differences in flow fields around high-rise buildings in twisted wind fields as compared to conventional wind fields. Consequently, the wind energy potential within through-building openings of high-rise buildings may be significantly impacted by twisted winds. This paper applies high-fidelity methods (LES) to evaluate the wind energy potential within through-building openings of buildings with different heights under twisted wind field conditions, and compares the results with those obtained under conventional wind conditions. The results show that the passage near the inflow experiences higher wind speed and wind power compared to the passage far from the inflow under the twisted wind profile. The twisted wind flows cause an increase in local wind power density within the through-building openings, but it also results in an elevation of turbulence intensity, which is unfavorable for enhancing the efficiency of wind turbines. Furthermore, the degree of enhancement in local wind power and local turbulence intensity within the through-building openings gradually intensifies as the wind twisted angle increases.

Comparative Analysis of Wind Speed and Energy Potential Assessment of Two Distribution Models in Medan, Indonesia

Comparative Analysis of Wind Speed and Energy Potential Assessment of Two Distribution Models in Medan, Indonesia

Bayesian method for estimating Weibull parameters for wind resource assessment in a tropical region: a comparison between two-parameter and three-parameter Weibull distributions

Abstract. The two-parameter Weibull distribution has garnered much attention in the assessment of wind energy potential. The estimation of the shape and scale parameters of the distribution has brought forth a successful tool for the wind energy industry. However, it may be inappropriate to use the two-parameter Weibull distribution to assess energy at every location, especially at sites where low wind speeds are frequent, such as in tropical regions. In this work, a robust technique for wind resource assessment using a Bayesian approach for estimating Weibull parameters is first proposed. Secondly, the wind resource assessment techniques using a two-parameter Weibull distribution and a three-parameter Weibull distribution, which is a generalized form of two-parameter Weibull distribution, are compared. Simulation studies confirm that the Bayesian approach seems a more robust technique for accurate estimation of Weibull parameters. The research is conducted using data from seven sites in the tropical region from 1∘ N of the Equator to 21∘ S of the Equator. Results reveal that a three-parameter Weibull distribution with a non-zero shift parameter is a better fit for the wind data with a higher percentage of low wind speeds (0–1 m s−1) and low skewness. However, wind data with a smaller percentage of low wind speeds and high skewness showed better results with a two-parameter distribution that is a special case of the three-parameter Weibull distribution with a zero shift parameter. The proposed distribution can be incorporated into commercial software like WAsP to improve the accuracy of wind resource assessments. The results also demonstrate that the proposed Bayesian approach and application of a three-parameter Weibull distribution are extremely useful for accurate estimation of wind power density.

Modelling approach and predictive assessment of wind energy potential in the Nouakchott region, Mauritania

Modelling approach and predictive assessment of wind energy potential in the Nouakchott region, Mauritania

Copula‐based joint distribution analysis of wind speed and wind direction: Wind energy development for Hong Kong

AbstractAccurate and reliable assessment of wind energy potential has important implication to the wind energy industry. Most previous studies on wind energy assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In this paper, a copula‐based method is proposed to better characterize the direction‐related wind energy potential at six typical sites in Hong Kong. The joint probability density function (JPDF) of wind speed and wind direction is constructed by a series of copula models. It shows that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites while Gumbel copula outperforms other models at urban sites. The derived JPDFs are applied to estimate the direction‐related wind power density at the considered sites. The obtained maximum direction‐related wind energy density varies from 41.3 W/m2 at an urban site to 507.9 W/m2 at a hilltop site. These outcomes are expected to facilitate accurate micro‐site selection of wind turbines, thereby improving the economic benefits of wind farms in Hong Kong. Meanwhile, the developed copula‐based method provides useful references for further investigations regarding direction‐related wind energy assessments at various terrain regions. Notably, the proposed copula‐based method can also be applied to characterize the direction‐related wind energy potential somewhere other than Hong Kong.

Wind energy potential assessment for Mexico's Yucatecan Shelf

The objective of significantly decreasing the use of fossil fuels due to their environmental impact has led to rethinking strategies to satisfy the global energy demand. Thus, the study and understanding of renewable energy resources is of great importance. Due to the maturity of the technology, wind is currently one of the most competitive sources of renewable energy, and development has focused on making wind power production more efficient, particularly in regions with great potential. The Yucatan Peninsula, Mexico, is one of these regions where inland commercial wind farms are already operating. However, these projects have caused environmental and social problems. Therefore, here we propose the development of offshore wind as an alternative. This study aims to calculate the offshore wind potential on the northern Yucatan Peninsula and its continental shelf, to outline/study a design of an offshore wind farm on a selected location at/on the northwest Yucatan coast. WRF atmospheric model data from 2005 to 2016 were used. The numerical simulations were validated with measured data from meteorological stations in the region, both inland and offshore. Characterization of the wind field at different temporal scales was performed, and subsequently, the wind potential was analyzed. The offshore zone with the highest potential was delimited, and a wind farm outline was proposed. The offshore wind farm potential was estimated, showing to be within an ideal range to reach a maximum power level. Besides having a significant wind potential, this zone provides additional advantages, such as mild wave conditions and a shallow depth far from the coast.

Techno-economic assessment of offshore wind energy potential at selected sites in the Gulf of Guinea

Offshore wind power has been found to stand out among the most dynamic renewable energy technologies. With its long coastal line, Nigeria has an overwhelming advantage in developing marine energy resources to relieve the power crisis effectively. This work analyzed and characterized observation data of sea-surface wind speed and direction at 30-minute intervals between 1979 and 2015 at five synoptic offshore stations in the Gulf of Guinea. The seasonal variations in hourly surface wind speed and directions as well as the Weibull distribution of wind speed and wind power at 100 m hub height were examined. The wind shears, capacity factors, and accumulated energy outputs for seven offshore wind turbine types were determined for the selected locations. In addition, the economic analysis of the selected offshore turbines using levelized cost of energy was carried out, while sensitivity analysis of the total levelized cost of energy to key input parameters was further determined. The results revealed large spatial and temporal variations in wind speed and wind power in the Gulf of Guinea. The most viable offshore site for wind energy exploitation was Agbami (the deepest offshore site), while Bonny (the shallow coastal site) had the least. The findings established very good fits (having mean bias (between −0.08 ms−1 and −2.44 ms−1), percentage bias (between −0.47% and −13.98%), correlation coefficients (between 0.97 and 0.98), Chi-square (between 0.2 and 1.2), and root mean square error (between 1.2 ms−1 and 3.1 ms−1)) between Weibull distribution and the actual wind data. The wind turbines with the highest and the lowest wind power densities, capacity factors, and power outputs across the seasons and sites were V236-15.0 MW and Siemens SWT113, respectively. The levelized cost of energy was considered for the deep waters due to the moderately high-capacity factors. The highest values ranged between 101.48 and 137.12 USD/MWh at Sea Eagle with V236-15 MW and V117-4.2 MW, respectively, while the lowest ranged from 52.29 to 69.66 USD/MWh at Agbami with V236-15 MW and Siemens (SWT113), respectively. The exploitation of Nigeria’s offshore wind resources could also be dedicated to producing renewable hydrogen and can serve to meet the country’s ambitious targets set for carbon neutrality by 2060.

Research on Suitable Array Power Installation Density of Wind Turbines for the Assessment of Wind Energy Potential for Data Platform

Research on Suitable Array Power Installation Density of Wind Turbines for the Assessment of Wind Energy Potential for Data Platform

Wind Energy Resource Potential Evaluation based on Statistical Distribution Models at Four Selected Locations in Amhara Region, Ethiopia

In Ethiopia, and particularly in the Amhara region, the government as well as the concerned organization would not give special attention to establishing wind energy plants. Lack of scientific research inputs about potential assessment can be one of the reasons behind it. In this paper, a wind energy potential assessment for Debel, Malawa, Enwari, and Ayba Eyesus sites in the Amhara region has been investigated. Five statistical distribution methods namely Weibull 3P, Weibull 2P, Rayleigh 2P, Normal, and Lognormal are used to fit the data to the probability density function and cumulative distribution function. The proposed parameter estimation method, to precisely predict the values of the shape parameter, scale parameter, and location parameter, was the Maximum Likelihood Estimation Method (MLE). To analyze the goodness of fit of the models, Kolmogorov, Andersen Darling, and Chi-Square have been used. The test indicated that Weibull 3P is the best fitting method, except for Ayba Eyesus, which is suited to Weibull 2P. For Debel, Malawa, Enwari, and Ayba Eyesus, the maximum annual average wind power density was found to be 74.291 W/m2, 19.183 W/m2, 68.972 W/m2, and 49.221 W/m2 correspondingly. The evaluations show that VENSYS 87 turbine model has better performance in all three sites except Enwari, where Inox Wind DF 100 is favored. With their best performance turbine, the capacity factor of the sites is determined as 14%, 7%, 12%, and 14% for Debel, Malawa, Enwari, and Ayba Eyesus respectively. Furthermore, Economical analysis by initial cost, lifetime, operation, and maintenance cost, has been carried out to estimate the cost of energy. With VENSYS 87 turbine model, the three sites' present value costs are $5,479,586, while it costs $7,306,115 in Enwari with Inox Wind DF 100 turbine. The cost of electricity per kWh is estimated to be $0.00231, $0.00455, $0.00391, and $0.00312 for Debel, Malawa, Enwari, and Ayba Eyesus respectively, and it is significantly lower than the cost from Ethiopian electric utility (EEU), which is around 0.009$/kwh. Access to electricity in Ethiopia was reported at 45% in 2019. This indicates there is a shortage of energy in the country. This kind of study can help authorities and policymakers in taking into account wind power to mitigate energy poverty in the country.

Software-Based Wind Energy Potential Assessment: A Case Study from Western Turkey

In this research, wind energy potential of a specific region in Western Turkey has been analyzed by using WindPRO software. The analyzed site is located in Ayvacık district of Çanakkale province of Turkey. Two types of wind energy turbines with 3 MW power including Enercon E-101/3000 and Nordex N117/3000 have been selected for the analyses. Weibull distribution has been utilized in the wind energy potential assessment. Also, average wind speed values and prevailing wind directions have been calculated for the selected locations in the analyzed region. The prevailing wind direction was determined for Enercon E-101/3000 and Nordex N117/3000 turbines as NNW and SSE, respectively. Estimated electrical energy generation values for Enercon E-101/3000 and Nordex N117/3000 turbines were obtained between 10177-11925 MWh/year and 9283-10954 MWh/year, respectively. Moreover, shape and scale parameters for each wind directions and annual energy generation values of each location have been calculated within the scope of this work.