scholarly journals Comparison and Optimization of Neural Networks and Network Ensembles for Gap Filling of Wind Energy Data

2014 ◽  
Vol 2014 ◽  
pp. 1-15
Author(s):  
Andres Schmidt ◽  
Maya Suchaneck
Keyword(s):  
Wind Energy ◽  
Wind Turbines ◽  
Extreme Values ◽  
Wind Farms ◽  
Electrical Energy ◽  
Energy Output ◽  
Rbf Networks ◽  
Topographic Complexity ◽  
Technical Issues ◽  
Multilayer Perceptron Networks

Wind turbines play an important role in providing electrical energy for an ever-growing demand. Due to climate change driven by anthropogenic emissions of greenhouse gases, the exploration and use of sustainable energy sources is essential with wind energy covering a significant portion. Data of existing wind turbines is needed to reduce the uncertainty of model predictions of future energy yields for planned wind farms. Due to maintenance routines and technical issues, data gaps of reference wind parks are unavoidable. Here, we present real-world case studies using multilayer perceptron networks and radial basis function networks to reproduce electrical energy outputs of wind turbines at 3 different locations in Germany covering a range of landscapes with varying topographic complexity. The results show that the energy output values of the turbines could be modeled with high correlations ranging from 0.90 to 0.99. In complex terrain, the RBF networks outperformed the MLP networks. In addition, rare extreme values were better captured by the RBF networks in most cases. By using wind meteorological variables and operating data recorded by the wind turbines in addition to the daily energy output values, the error could be further reduced to more than 20%.

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.

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 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.

Effect of Slotted Angle on Savonius Wind Turbine Performance

2021 ◽  
Vol 104 ◽  
pp. 83-88
Author(s):  
Rahmat Wahyudi ◽  
Diniar Mungil Kurniawati ◽  
Alfian Djafar
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Electrical Energy ◽  
Speed Ratio ◽  
Angle Variation ◽  
Wind Speeds ◽  
Turbine Performance ◽  
Savonius Wind Turbine ◽  
Low Wind Speeds

The potential of wind energy is very abundant but its utilization is still low. The effort to utilize wind energy is to utilize wind energy into electrical energy using wind turbines. Savonius wind turbines have a very simple shape and construction, are inexpensive, and can be used at low wind speeds. This research aims to determine the effect of the slot angle on the slotted blades configuration on the performance produced by Savonius wind turbines. Slot angle variations used are 5o ,10o , and 15o with slotted blades 30% at wind speeds of 2,23 m/s to 4,7 m/s using wind tunnel. The result showed that a small slot angle variation of 5o produced better wind turbine performance compared to a standard blade at low wind speeds and a low tip speed ratio.

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 An Evaluation of Primary Energy Factor Values of Wind Turbines

Proceedings ◽  
2019 ◽  
Vol 16 (1) ◽  
pp. 9 ◽  
Author(s):  
Rokas Tamašauskas ◽  
Jolanta Šadauskienė ◽  
Patrikas Bruzgevičius ◽  
Dorota Anna Krawczyk
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Wind Energy ◽  
Wind Turbines ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Energy Performance ◽  
Primary Energy ◽  
Energy Factor ◽  
Eu Member States

In order to fulfil the European Energy Performance of Buildings Directive (EPBD) requirements regarding the reduction of energy consumption in buildings, much attention has been paid to primary energy consumption. Wind energy is one type of primary energy. The analysis of the literature has revealed that wind energy is evaluated by different methods. Therefore, the aim of this article was to calculate the effect of the parameters of wind sources on the primary energy factor of wind turbines. In order to achieve this aim, the primary energy factor of 100 investigated wind turbines and 11 wind farms operating in Lithuania was calculated. Investigation results showed that the difference of the non-renewable primary energy factor between wind turbines due to capacity is 35%. This paper provides a recommendation with regard to EU energy efficiency and renewable energy directives and regulations: All EU member states should use the same or very similar methodology for the calculation of the primary energy factor of renewable and non-renewable energy sources.

Ensemble-Based Data Assimilation for Wind Forecasting – Application to Wind Farm

2020 ◽  
Author(s):  
Yang-Ming Fan
Keyword(s):  
Wind Speed ◽  
Natural Gas ◽  
Data Assimilation ◽  
Wind Energy ◽  
Wind Farm ◽  
Initial Conditions ◽  
Wind Farms ◽  
Weather Conditions ◽  
Energy Output ◽  
Combining Data

<p>The purpose of this study is to develop an ensemble-based data assimilation method to accurately predict wind speed in wind farm and provide it for the use of wind energy intelligent forecasting platform. As Taiwan government aimed to increase the share of renewable energy generation to 20% by 2025, among them, the uncertain wind energy output will cause electricity company has to reserve a considerable reserve capacity when dispatching power, and it is usually high cost natural gas power generation. In view of this, we will develop wind energy intelligent forecasting platform with an error of 10% within 72 hours and expect to save hundred millions of dollars of unnecessary natural gas generators investment. Once the wind energy can be predicted more accurately, the electricity company can fully utilize the robustness and economy of smart grid supply. Therefore, the mastery of the change of wind speed is one of the key factors that can reduce the minimum error of wind energy intelligent forecasting.</p><p>There are many uncertainties in the numerical meteorological models, including errors in the initial conditions or defects in the model, which may affect the accuracy of the prediction. Since the deterministic prediction cannot fully grasp the uncertainty in the prediction process, so it is difficult to obtain all possible wind field changes. The development of ensemble-based data assimilation prediction is to make up for the weakness of deterministic prediction. With the prediction of 20 wind fields as ensemble members, it is expected to include the uncertainty of prediction, quantify the uncertainty, and integrate the wind speed observations of wind farms as well to provide the optimal prediction of wind speed for the next 72 hours. The results show that the prediction error of wind speed within 72 hours is 6% under different weather conditions (excluding typhoons), which proves that the accuracy of wind speed prediction by combining data assimilation technology and ensemble approach is better.</p>

scholarly journals Integrating Wind Electrical Energy for the Marine Electrical Power System

2019 ◽  
Vol 9 (1) ◽  
pp. 4413-4418
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Wind Energy ◽  
Wind Power ◽  
Electrical Power ◽  
Electrical Energy ◽  
Energy Output ◽  
Future Research ◽  
Electrical Power System ◽  
Bus System

Utilization of renewable energy for the reduction of fuel consumption and green house gas (GHG) emissions in the shipping industry has been increased rapidly in the recent years. Wind energy is a clean renewable energy with no pollution which is abundantly available at sea. This paper proposes two different possible configurations of connecting wind power energy into the ship’s main grid bus system . Wind electrical energy output has been connected to ship’s main ac bus system in one configuration and it is connected to ship’s main dc bus system. Even though Wind assisted ship propulsion (WASP) had been started already in the last decades in the form of wing sails, kites, Flettener rotor etc which could assist auxiliary propulsion of the ships, the application of wind power generator on the ship is not often applied. Therefore this paper has a relevant significance in applying wind electrical energy for the marine electrical power system needs. This paper also reveals the benefits and challenges in the area of onboard wind generation and opens future research possibilities in integrating wind energy into marine industry.

scholarly journals Perancangan dan Perhitungan Sudu Turbin Angin Horisontal NACA 4412 Variasi Sudut Serang Menggunakan Simulasi BEM

2020 ◽  
Vol 8 (2) ◽  
pp. 34-37
Author(s):  
Gian Roni Ignatius ◽  
Agus Sugiri ◽  
Ahmad Suudi
Keyword(s):  
Wind Energy ◽  
Wind Turbines ◽  
Fossil Fuels ◽  
Mechanical Energy ◽  
Angle Of Attack ◽  
Electrical Energy ◽  
Shaft Speed ◽  
A Value ◽  
Mechanical Rotation ◽  
Main Material

The need for electricity in Indonesia becoming increasingly part of people's needs. Fossil fuels suchas oil and coal used as the main material for producing electrical energy the more limitedavailability, especially in its use of fossil fuels that pollute the environment. Wind energy is arenewable energy source that could potentially be developed. Wind energy is clean and does notpollute the environment in utilization into mechanical or electrical energy. The conversion of windenergy into electrical energy by converting this energy into mechanical rotation. In the wind energyutilization process made a tool to convert wind energy into electrical energy, that is windturbines.Wind turbine or windmill is a tool for converting wind energy. Wind turbines transformkinetic energy into mechanical energy in the form of a round shaft. Shaft speed is then used to rotatethe dynamo or a generator which produces electricity. The research was carried out on a horizontalaxis wind turbine NACA 4412, diameter 1 m, the number of blades 3 pieces and variations in windspeed 2-8 m / s. Results showed the greatest lift (CL) at 14o angle of attack with a value of 1.583.The driving force of the smallest (CD) at an angle of attack -4o to 2o with a value of 0.008. Value CL/ CD was found in the angle of attack of 6o with a value of 93.057. The maximum power generatedby 484.63 Watt. Wind speed, the number of blades, angle of attack and the election of the airfoileffect on the generated power.Keywords : wind energy, wind turbines, airfoil NACA 4412.

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