scholarly journals AI Supported Maintenance and Reliability System in Wind Energy Production

2021 ◽  
pp. 211-221
Author(s):  
Mr Manjunath H R ◽  
Jeevitha Naveen Suvarna ◽  
Gowthami ◽  
Shrihastha ◽  
Gagan Raghavendra J
Keyword(s):  
Wind Energy ◽  
Wind Turbines ◽  
Energy Production ◽  
Fossil Fuel ◽  
Carbon Sources ◽  
Wind Farms ◽  
Low Carbon ◽  
Power Sources ◽  
The Past ◽  
Global Warming Potentials

Technology is advancing at an unbelievable rate. To the point many of us are not able to efficiently keep up. With the ever-increasing sophistication of Artificial Intelligence [AI]. The environmental impact of wind power is relatively minor when compared to that of fossil fuel power. Compared with other low carbon sources, wind turbines have one of the lowest global warming potentials per unit of electricity energy generated per power sources. Among the renewable energy arts wind energy plays a significant role and, as forecasted its ratio within the total energy production will rapidly increase. Wind turbines are relatively complex electro-mechanical systems, their smooth functioning is an important economical factor. This is why monitoring and diagnosis of wind turbines and wind farms gained extreme importance in the past years.

scholarly journals Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

2021 ◽  
Vol 13 (5) ◽  
pp. 2862
Author(s):  
Amer Al-Hinai ◽  
Yassine Charabi ◽  
Seyed H. Aghay Kaboli
Keyword(s):  
Data Analysis ◽  
Wind Energy ◽  
Wind Turbines ◽  
Energy Resource ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wind Data ◽  
Offshore Wind Energy ◽  
Offshore Wind Turbines ◽  
Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

scholarly journals Wealth of Wind and Visitors: Tourist Industry Attitudes towards Wind Energy Development in Iceland

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 693
Author(s):  
Anna Dóra Sæþórsdóttir ◽  
Margrét Wendt ◽  
Edita Tverijonaite
Keyword(s):  
Land Use ◽  
Wind Energy ◽  
Wind Turbines ◽  
Wind Farm ◽  
Service Providers ◽  
Wind Farms ◽  
Energy Development ◽  
Tourism Industry ◽  
Land Use Conflicts ◽  
Wind Energy Development

The interest in harnessing wind energy keeps increasing globally. Iceland is considering building its first wind farms, but its landscape and nature are not only a resource for renewable energy production; they are also the main attraction for tourists. As wind turbines affect how the landscape is perceived and experienced, it is foreseeable that the construction of wind farms in Iceland will create land use conflicts between the energy sector and the tourism industry. This study sheds light on the impacts of wind farms on nature-based tourism as perceived by the tourism industry. Based on 47 semi-structured interviews with tourism service providers, it revealed that the impacts were perceived as mostly negative, since wind farms decrease the quality of the natural landscape. Furthermore, the study identified that the tourism industry considered the following as key factors for selecting suitable wind farm sites: the visibility of wind turbines, the number of tourists and tourist attractions in the area, the area’s degree of naturalness and the local need for energy. The research highlights the importance of analysing the various stakeholders’ opinions with the aim of mitigating land use conflicts and socioeconomic issues related to wind energy development.

scholarly journals Effect of Wind Turbine Classes on the Electricity Production of Wind Farms in Cyprus Island

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Yiannis A. Katsigiannis ◽  
George S. Stavrakakis ◽  
Christodoulos Pharconides
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farms ◽  
Electricity Production ◽  
Wind Speeds ◽  
Wind Potential

This paper examines the effect of different wind turbine classes on the electricity production of wind farms in two areas of Cyprus Island, which present low and medium wind potentials: Xylofagou and Limassol. Wind turbine classes determine the suitability of installing a wind turbine in a particulate site. Wind turbine data from five different manufacturers have been used. For each manufacturer, two wind turbines with identical rated power (in the range of 1.5 MW–3 MW) and different wind turbine classes (IEC II and IEC III) are compared. The results show the superiority of wind turbines that are designed for lower wind speeds (IEC III class) in both locations, in terms of energy production. This improvement is higher for the location with the lower wind potential and starts from 7%, while it can reach more than 50%.

Simulation of Flow Field on a Large Scale Wind Turbine

2008 ◽  
Author(s):  
I. Janajreh ◽  
C. Ghenai
Keyword(s):  
Flow Field ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Cross Sections ◽  
Large Scale ◽  
Wind Farms ◽  
Operating Characteristics ◽  
Cross Sectional ◽  
Capital Costs

Large scale wind turbines and wind farms continue to evolve mounting 94.1GW of the electrical grid capacity in 2007 and expected to reach 160.0GW in 2010 according to World Wind Energy Association. They commence to play a vital role in the quest for renewable and sustainable energy. They are impressive structures of human responsiveness to, and awareness of, the depleting fossil fuel resources. Early generation wind turbines (windmills) were used as kinetic energy transformers and today generate 1/5 of the Denmark’s electricity and planned to double the current German grid capacity by reaching 12.5% by year 2010. Wind energy is plentiful (72 TW is estimated to be commercially viable) and clean while their intensive capital costs and maintenance fees still bar their widespread deployment in the developing world. Additionally, there are technological challenges in the rotor operating characteristics, fatigue load, and noise in meeting reliability and safety standards. Newer inventions, e.g., downstream wind turbines and flapping rotor blades, are sought to absorb a larger portion of the cost attributable to unrestrained lower cost yaw mechanisms, reduction in the moving parts, and noise reduction thereby reducing maintenance. In this work, numerical analysis of the downstream wind turbine blade is conducted. In particular, the interaction between the tower and the rotor passage is investigated. Circular cross sectional tower and aerofoil shapes are considered in a staggered configuration and under cross-stream motion. The resulting blade static pressure and aerodynamic forces are investigated at different incident wind angles and wind speeds. Comparison of the flow field results against the conventional upstream wind turbine is also conducted. The wind flow is considered to be transient, incompressible, viscous Navier-Stokes and turbulent. The k-ε model is utilized as the turbulence closure. The passage of the rotor blade is governed by ALE and is represented numerically as a sliding mesh against the upstream fixed tower domain. Both the blade and tower cross sections are padded with a boundary layer mesh to accurately capture the viscous forces while several levels of refinement were implemented throughout the domain to assess and avoid the mesh dependence.

scholarly journals Wind Energy Potential at Badin and Pasni Costal Line of Pakistan

2017 ◽  
Vol 6 (2) ◽  
pp. 103 ◽  
Author(s):  
Ghulam Sarwar Kaloi ◽  
Jie Wang ◽  
Mazhar H Baloch ◽  
Sohaib Tahir
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Urban Areas ◽  
Interconnection Network ◽  
Wind Farms ◽  
Energy Sector ◽  
Energy Crisis ◽  
Energy Potential ◽  
The Past ◽  
Wind Energy Potential

Unfortunately, Pakistan is facing an acute energy crisis since the past decade due to the increasing population growth and is heavily dependent on imports of fossil fuels. The shortage of the electricity is 14-18 hours in rural areas and 8-10 hours in urban areas. This situation has been significantly affecting the residential, industrial and commercial sectors in the country. At this time, it is immense challenges for the government to keep the power supply provision continue in the future for the country. In this situation, it has been the increased research to explore renewable energy resources in the country to fulfill the deficit scenario in the state. The renewable energy sector has not penetrated in the energy mix, currently in the upcoming markets. This paper highlights the steps taken by the country in the past and is taking steps at the present time to get rid of from the existing energy crisis when most urban areas are suffering from power outages for 12 hours on regular basis. Until 2009, no single grid interconnected wind established, but now the circumstances are changing significantly and wind farms are contributing to the national grid is the reality now. The initiation of the three wind farms interconnection network and many others in the pipeline are going to be operational soon. The federal policy on wind energy system has recently changed. Surprisingly, the continuing schemes of the wind farm are getting slow. This paper reviews developments in the wind energy sector in the country and lists some suggestions that can contribute to improving the penetration of wind energy in the national energy sector.Keywords: Wind energy, evolution of wind resource, Wind sites of PakistanArticle History: Received Dec 16th 2016; Received in revised form May 15th 2017; Accepted June 18th 2017; Available onlineHow to Cite This Article: Kaloi,G.S., Wang, J., Baloch, M.H and Tahir, S. (2017) Wind Energy Potential at Badin and Pasni Costal Line Pakistan. Int. Journal of Renewable Energy Development, 6(2), 103-110.https://doi.org/10.14710/ijred.6.2.103-110

scholarly journals Tourist Viewshed Externalities and Wind Energy Production

2017 ◽  
Vol 46 (2) ◽  
pp. 224-241 ◽  
Author(s):  
Jacob R. Fooks ◽  
Kent D. Messer ◽  
Joshua M. Duke ◽  
Janet B. Johnson ◽  
Tongzhe Li ◽  
...  
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Hotel Room ◽  
Negative Effect ◽  
The Impact ◽  
Large Wind

This study uses an experiment where ferry passengers are sold hotel room “views” to evaluate the impact of wind turbines views on tourists’ vacation experience. Participants purchase a chance for a weekend hotel stay. Information about the hotel rooms was limited to the quality of the hotel and its distance from a large wind turbine, as well as whether or not a particular room would have a view of the turbine. While there was generally a negative effect of turbine views, this did not hold across all participants, and did not seem to be effected by distance or hotel quality.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

scholarly journals The Wind Energy Potential of Kurdistan, Iran

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Farzad Arefi ◽  
Jamal Moshtagh ◽  
Mohammad Moradi
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbines ◽  
Wind Farms ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Energy Assessment ◽  
Technical Specifications ◽  
Weather Stations ◽  
Calm Wind

In the current work by using statistical methods and available software, the wind energy assessment of prone regions for installation of wind turbines in, Qorveh, has been investigated. Information was obtained from weather stations of Baneh, Bijar, Zarina, Saqez, Sanandaj, Qorveh, and Marivan. The monthly average and maximum of wind speed were investigated between the years 2000–2010 and the related curves were drawn. The Golobad curve (direction and percentage of dominant wind and calm wind as monthly rate) between the years 1997–2000 was analyzed and drawn with plot software. The ten-minute speed (at 10, 30, and 60 m height) and direction (at 37.5 and 10 m height) wind data were collected from weather stations of Iranian new energy organization. The wind speed distribution during one year was evaluated by using Weibull probability density function (two-parametrical), and the Weibull curve histograms were drawn by MATLAB software. According to the average wind speed of stations and technical specifications of the types of turbines, the suitable wind turbine for the station was selected. Finally, the Divandareh and Qorveh sites with favorable potential were considered for installation of wind turbines and construction of wind farms.

scholarly journals Managing Wind Power Generation via Indexed Semi-Markov Model and Copula

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4246 ◽  
Author(s):  
Guglielmo D’Amico ◽  
Giovanni Masala ◽  
Filippo Petroni ◽  
Robert Adam Sobolewski
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Wind Energy ◽  
Output Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Energy Systems ◽  
Wind Farms ◽  
Energy System ◽  
Spatial Dependencies

Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR).

scholarly journals Evaluation of AEP Predictions for Commercial Wind Farms in Sweden

2020 ◽  
Vol 10 (22) ◽  
pp. 7995
Author(s):  
Erik Möllerström ◽  
Daniel Lindholm
Keyword(s):  
South Africa ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farms ◽  
Project Planning ◽  
Data Availability ◽  
Energy Calculation ◽  
The Mean ◽  
Over Time

Based on data from 1162 wind turbines, with a rated power of at least 1.8 MW, installed in Sweden after 2005, the accuracy of the annual energy production (AEP) predictions from the project planning phases has been compared to the wind-index-corrected production. Both the production and the predicted AEP data come from the database Vindstat, which collects information directly from wind turbine owners. The mean error was 7.1%, which means that, overall, the predicted AEP has been overestimated. The overestimation was higher for wind turbines situated in open terrain than in forest areas and was higher overall than that previously established for the British Isles and South Africa. Dividing the result over the installation year, the improvement which had been expected due to the continuous refinement of the methods and better data availability, was not observed over time. The major uncertainty comes from the predicted AEP as reported by wind turbine owners to the Vindstat database, which, for some cases, might not come from the wind energy calculation from the planning phase (i.e., the P50-value).

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