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analysis</title> <meta name="description" content="Search results for: wind speed analysis"> <meta name="keywords" content="wind speed analysis"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="wind speed analysis"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 30362</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: wind speed analysis</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30362</span> Prediction of Wind Speed by Artificial Neural Networks for Energy Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Adjiri-Bailiche">S. Adjiri-Bailiche</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20M.%20Boudia"> S. M. Boudia</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Daaou"> H. Daaou</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Hadouche"> S. Hadouche</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Benzaoui"> A. Benzaoui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MATLAB" title="MATLAB">MATLAB</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20low" title=" power low"> power low</a>, <a href="https://publications.waset.org/abstracts/search?q=vertical%20extrapolation" title=" vertical extrapolation"> vertical extrapolation</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title=" wind energy"> wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed "> wind speed </a> </p> <a href="https://publications.waset.org/abstracts/17635/prediction-of-wind-speed-by-artificial-neural-networks-for-energy-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17635.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">692</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30361</span> Wind Energy Potential of Southern Sindh, Pakistan for Power Generation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Akhlaque%20Ahmed">M. Akhlaque Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Maliha%20Afshan%20Siddiqui"> Maliha Afshan Siddiqui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A study has been carried out to see the prospect of wind power potential of southern Sindh namely Karachi, Hawksbay, Norriabad, Hyderabad, Ketibander and Shahbander using local wind speed data. The monthly average wind speed for these area ranges from 4.5m/sec to 8.5m/sec at 30m height from ground. Extractable wind power, wind energy and Weibul parameter for above mentioned areas have been examined. Furthermore, the power output using fast and slow wind machine using different blade diameter along with the 4Kw and 20 Kw aero-generator were examined to see the possible use for deep well pumping and electricity supply to remote villages. The analysis reveals that in this wind corridor of southern Sindh Hawksbay, Ketibander and Shahbander belongs to wind power class-3 Hyderabad and Nooriabad belongs to wind power class-5 and Karachi belongs to wind power class-2. The result shows that the that higher wind speed values occur between June till August. It was found that considering maximum wind speed location, Hawksbay,Noriabad are the best location for setting up wind machines for power generation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20energy%20generation" title="wind energy generation">wind energy generation</a>, <a href="https://publications.waset.org/abstracts/search?q=Southern%20Sindh" title=" Southern Sindh"> Southern Sindh</a>, <a href="https://publications.waset.org/abstracts/search?q=seasonal%20change" title=" seasonal change"> seasonal change</a>, <a href="https://publications.waset.org/abstracts/search?q=Weibull%20parameter" title=" Weibull parameter"> Weibull parameter</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20machines" title=" wind machines"> wind machines</a> </p> <a href="https://publications.waset.org/abstracts/100211/wind-energy-potential-of-southern-sindh-pakistan-for-power-generation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/100211.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">149</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30360</span> Experimental Investigation of Tip-Speed-Ratio Effects on Wake Dynamics of Horizontal-Axis Wind Turbine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Paul%20Bayron">Paul Bayron</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%20Kelso"> Richard Kelso</a>, <a href="https://publications.waset.org/abstracts/search?q=Rey%20Chin"> Rey Chin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wind tunnel experiments were performed in the KC closed-circuit wind tunnel in the University of Adelaide to study the influence of tip-speed-ratio ( <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hotwire%20anemometry" title="hotwire anemometry">hotwire anemometry</a>, <a href="https://publications.waset.org/abstracts/search?q=wake%20dynamics" title=" wake dynamics"> wake dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20tunnel" title=" wind tunnel"> wind tunnel</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbines" title=" wind turbines"> wind turbines</a> </p> <a href="https://publications.waset.org/abstracts/137158/experimental-investigation-of-tip-speed-ratio-effects-on-wake-dynamics-of-horizontal-axis-wind-turbine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/137158.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">215</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30359</span> The Mechanism of Design and Analysis Modeling of Performance of Variable Speed Wind Turbine and Dynamical Control of Wind Turbine Power</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammadreza%20Heydariazad">Mohammadreza Heydariazad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title="wind energy">wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=generator" title=" generator"> generator</a>, <a href="https://publications.waset.org/abstracts/search?q=superconducting%20inductor" title=" superconducting inductor"> superconducting inductor</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine%20power" title=" wind turbine power"> wind turbine power</a> </p> <a href="https://publications.waset.org/abstracts/10467/the-mechanism-of-design-and-analysis-modeling-of-performance-of-variable-speed-wind-turbine-and-dynamical-control-of-wind-turbine-power" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10467.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">327</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30358</span> Wind Speed Forecasting Based on Historical Data Using Modern Prediction Methods in Selected Sites of Geba Catchment, Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halefom%20Kidane">Halefom Kidane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=forecasting" title=" forecasting"> forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=min-max%20normalization" title=" min-max normalization"> min-max normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a> </p> <a href="https://publications.waset.org/abstracts/169838/wind-speed-forecasting-based-on-historical-data-using-modern-prediction-methods-in-selected-sites-of-geba-catchment-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169838.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30357</span> Estimation of Wind Characteristics and Energy Yield at Different Towns in Libya </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farag%20Ahwide">Farag Ahwide</a>, <a href="https://publications.waset.org/abstracts/search?q=Souhel%20Bousheha"> Souhel Bousheha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A technical assessment has been made of electricity generation, considering wind turbines ranging between Vestas (V80-2.0 MW and V112-3.0 MW) and the air density is equal to 1.225 Kg/m3, at different towns in Libya. Wind speed might have been measured each 3 hours during 10 m stature at a time for 10 quite sometime between 2000 Furthermore 2009, these towns which are spotted on the bank from claiming Mediterranean ocean also how in the desert, which need aid Derna 1, Derna 2, Shahat, Benghazi, Ajdabya, Sirte, Misurata, Tripoli-Airport, Al-Zawya, Al-Kofra, Sabha, Nalut. The work presented long term "wind data analysis in terms of annual, seasonal, monthly and diurnal variations at these sites. Wind power density with different heights has been studied. Excel sheet program was used to calculate the values of wind power density and the values of wind speed frequency for the stations; their seasonally values have been estimated. Limit variable with rated wind pace to 10 different wind turbines need to be been estimated, which is used to focus those required yearly vitality yield of a wind vitality change framework (WECS), acknowledging wind turbines extending between 600 kW and 3000 kW). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=energy%20yield" title="energy yield">energy yield</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbines" title=" wind turbines"> wind turbines</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20power%20density" title=" wind power density"> wind power density</a> </p> <a href="https://publications.waset.org/abstracts/70620/estimation-of-wind-characteristics-and-energy-yield-at-different-towns-in-libya" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70620.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">298</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30356</span> Design a Small-Scale Irrigation Wind-Powered Water Pump Using a Savonius Type VAWT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getnet%20Ayele%20%20Kebede">Getnet Ayele Kebede</a>, <a href="https://publications.waset.org/abstracts/search?q=Tasew%20Tadiwose%20%20Zewdie"> Tasew Tadiwose Zewdie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a novel design of a wind-powered water pump for small-scale irrigation application by using the Savonius wind turbine of Vertical Axis Wind Turbine(VAWT) with 2 blades has been used. Calculations have been made on the energy available in the wind and an energy analysis was then performed to see what wind speed is required for the system to work. The rotor has a radius of 0.53 m giving a swept area of 1.27 m2 and this gives a solidity of 0.5, which is the minimum theoretical optimum value for wind turbine. The average extracted torque of the wind turbine is 0.922 Nm and Tip speed ratio is one this shows, the tips are moving at equal the speed of the wind and by 2 rotating of blades. This is sufficient to sustain the desired flow rate of (0.3125X 10-3) m3 per second with a maximum head of 10m and the expected working is 4hr/day, and also overcome other barriers to motion such as friction. Based on this novel design, we are able to achieve a cost-effective solution and simultaneously effective in self-starting under low wind speeds and it can catch the wind from all directions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Savonius%20wind%20turbine" title="Savonius wind turbine">Savonius wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=Small-scale%20irrigation" title=" Small-scale irrigation"> Small-scale irrigation</a>, <a href="https://publications.waset.org/abstracts/search?q=Vertical%20Axis%20Wind%20Turbine" title=" Vertical Axis Wind Turbine"> Vertical Axis Wind Turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=Water%20pump" title=" Water pump"> Water pump</a> </p> <a href="https://publications.waset.org/abstracts/121075/design-a-small-scale-irrigation-wind-powered-water-pump-using-a-savonius-type-vawt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/121075.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30355</span> Exergy Analyses of Wind Turbine </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Abid">Muhammad Abid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Utilization of renewable energy resources for energy conservation, pollution prevention, resource efficiency and systems integration is very important for sustainable development. In this study, we perform energy and exergy analyses of a wind turbine, located on the roof of Mechanical Engineering Department, King Saud University, and Riyadh, Saudi Arabia. The turbine is part of a hybrid photovoltaic (PV)-wind system with hydrogen storage. The power output from this turbine varies between 1.5 and 5.5 kW with a rated wind speed of 12 m/s and a cut-in wind speed of 2.4 m/s. We utilize a wide range of experimental data in the analysis and assessment. We determine energy and exergy efficiencies. The energy efficiency changes between 0% to 45% while the exergy efficiency varies between 0% and 31.3%. We also determined some of the exergoeconomic parameters that are the ratios of energy and exergy loss rates to the capital cost (R en and R ex), respectively. (R en) changes between 0.96% and 59.03% for different values of velocity while R ex has a maximum value of 53.62% for the highest wind speed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=exergy" title="exergy">exergy</a>, <a href="https://publications.waset.org/abstracts/search?q=efficiency" title=" efficiency"> efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20evaluation" title=" performance evaluation"> performance evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title=" wind energy"> wind energy</a> </p> <a href="https://publications.waset.org/abstracts/7227/exergy-analyses-of-wind-turbine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7227.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">366</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30354</span> Comparison Approach for Wind Resource Assessment to Determine Most Precise Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tasir%20Khan">Tasir Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ishfaq%20Ahmad"> Ishfaq Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Yejuan%20Wang"> Yejuan Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Salam"> Muhammad Salam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind-speed%20modeling" title="wind-speed modeling">wind-speed modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=goodness%20of%20fit" title=" goodness of fit"> goodness of fit</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20method" title=" maximum likelihood method"> maximum likelihood method</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20moment" title=" linear moment"> linear moment</a> </p> <a href="https://publications.waset.org/abstracts/161794/comparison-approach-for-wind-resource-assessment-to-determine-most-precise-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161794.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">84</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30353</span> An Investigation on Designing and Enhancing the Performance of H-Darrieus Wind Turbine of 10KW at the Medium Range of Wind Speed in Vietnam</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ich%20Long%20Ngo">Ich Long Ngo</a>, <a href="https://publications.waset.org/abstracts/search?q=Dinh%20Tai%20Dang"> Dinh Tai Dang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ngoc%20Tu%20Nguyen"> Ngoc Tu Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Minh%20Duc%20Nguyen"> Minh Duc Nguyen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes an investigation on designing and enhancing the performance of H-Darrieus wind turbine (HDWT) of 10kW at the medium wind speed. The aerodynamic characteristics of this turbine were investigated by both theoretical and numerical approaches. The optimal design procedure was first proposed to enhance the power coefficient under various effects, such as airfoil type, number of blades, solidity, aspect ratio, and tip speed ratio. As a result, the overall design of the 10kW HDWT was well achieved, and the power characteristic of this turbine was found by numerical approach. Additionally, the maximum power coefficient predicted is up to 0.41 at the tip speed ratio of 3.7 and wind speed of 8 m/s. Particularly, a generalized correlation of power coefficient with tip speed ratio and wind speed is first proposed. These results obtained are very useful for enhancing the performance of the HDWTs placed in a country with high wind power potential like Vietnam. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computational%20fluid%20dynamics" title="computational fluid dynamics">computational fluid dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=double%20multiple%20stream%20tube" title=" double multiple stream tube"> double multiple stream tube</a>, <a href="https://publications.waset.org/abstracts/search?q=h-darrieus%20wind%20turbine" title=" h-darrieus wind turbine"> h-darrieus wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=renewable%20energy" title=" renewable energy"> renewable energy</a> </p> <a href="https://publications.waset.org/abstracts/163982/an-investigation-on-designing-and-enhancing-the-performance-of-h-darrieus-wind-turbine-of-10kw-at-the-medium-range-of-wind-speed-in-vietnam" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163982.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30352</span> Applied Bayesian Regularized Artificial Neural Network for Up-Scaling Wind Speed Profile and Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aghbalou%20Nihad">Aghbalou Nihad</a>, <a href="https://publications.waset.org/abstracts/search?q=Charki%20Abderafi"> Charki Abderafi</a>, <a href="https://publications.waset.org/abstracts/search?q=Saida%20Rahali"> Saida Rahali</a>, <a href="https://publications.waset.org/abstracts/search?q=Reklaoui%20Kamal"> Reklaoui Kamal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bayesian%20regularization" title="bayesian regularization">bayesian regularization</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20shear" title=" wind shear"> wind shear</a>, <a href="https://publications.waset.org/abstracts/search?q=accuracy" title=" accuracy"> accuracy</a> </p> <a href="https://publications.waset.org/abstracts/24218/applied-bayesian-regularized-artificial-neural-network-for-up-scaling-wind-speed-profile-and-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24218.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">501</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30351</span> An Assessment of Wind Energy in Sanar Village in North of Iran Using Weibull Function</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ehsanolah%20Assareh">Ehsanolah Assareh</a>, <a href="https://publications.waset.org/abstracts/search?q=Mojtaba%20Biglari"> Mojtaba Biglari</a>, <a href="https://publications.waset.org/abstracts/search?q=Mojtaba%20Nedaei"> Mojtaba Nedaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sanar village in north of Iran is a remote region with difficult access to electricity, grid and water supply. Thus the aim of this research is to evaluate the potential of wind as a power source either for electricity generation or for water pumping. In this study the statistical analysis has been performed by Weibull distribution function. The results show that the Weibull distribution has fitted the wind data very well. Also it has been demonstrated that wind speed at 40 m height is ranged from 1.75 m/s in Dec to 3.28 m/s in Aug with average value of 2.69 m/s. In this research, different wind speed characteristics such as turbulence intensity, wind direction, monthly air temperature, humidity wind power density and other related parameters have been investigated. Finally it was concluded that the wind energy in the Sanar village may be explored by employing modern wind turbines that require very lower start-up speeds. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title="wind energy">wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine" title=" wind turbine"> wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=weibull" title=" weibull"> weibull</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanar%20village" title=" Sanar village"> Sanar village</a>, <a href="https://publications.waset.org/abstracts/search?q=Iran" title=" Iran"> Iran</a> </p> <a href="https://publications.waset.org/abstracts/16648/an-assessment-of-wind-energy-in-sanar-village-in-north-of-iran-using-weibull-function" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16648.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">523</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30350</span> Prediction of the Mechanical Power in Wind Turbine Powered Car Using Velocity Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelrahman%20Alghazali">Abdelrahman Alghazali</a>, <a href="https://publications.waset.org/abstracts/search?q=Youssef%20Kassem"> Youssef Kassem</a>, <a href="https://publications.waset.org/abstracts/search?q=H%C3%BCseyin%20%C3%87amur"> H眉seyin 脟amur</a>, <a href="https://publications.waset.org/abstracts/search?q=Ozan%20Erenay"> Ozan Erenay</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Savonius is a drag type vertical axis wind turbine. Savonius wind turbines have a low cut-in speed and can operate at low wind speed. This makes it suitable for electricity or mechanical generation in low-power applications such as individual domestic installations. Therefore, the primary purpose of this work was to investigate the relationship between the type of Savonius rotor and the torque and mechanical power generated. And it was to illustrate how the type of rotor might play an important role in the prediction of mechanical power of wind turbine powered car. The main purpose of this paper is to predict and investigate the aerodynamic effects by means of velocity analysis on the performance of a wind turbine powered car by converting the wind energy into mechanical energy to overcome load that rotates the main shaft. The predicted results based on theoretical analysis were compared with experimental results obtained from literature. The percentage of error between the two was approximately around 20%. Prediction of the torque was done at a wind speed of 4 m/s, and an angular velocity of 130 RPM according to meteorological statistics in Northern Cyprus. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mechanical%20power" title="mechanical power">mechanical power</a>, <a href="https://publications.waset.org/abstracts/search?q=torque" title=" torque"> torque</a>, <a href="https://publications.waset.org/abstracts/search?q=Savonius%20rotor" title=" Savonius rotor"> Savonius rotor</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20car" title=" wind car"> wind car</a> </p> <a href="https://publications.waset.org/abstracts/73215/prediction-of-the-mechanical-power-in-wind-turbine-powered-car-using-velocity-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73215.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">337</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30349</span> Wind Power Potential in Selected Algerian Sahara Regions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Dahbi">M. Dahbi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Sellam"> M. Sellam</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Benatiallah"> A. Benatiallah</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Harrouz"> A. Harrouz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The wind energy is one of the most significant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Algeria The main purpose of this paper is to compared and discuss the wind power potential in three sites located in sahara of Algeria (south west of Algeria) and to perform an investigation on the wind power potential of desert of Algeria. In this comparative, wind speed frequency distributions data obtained from the web site SODA.com are used to calculate the average wind speed and the available wind power. The Weibull density function has been used to estimate the monthly power wind density and to determine the characteristics of monthly parameters of Weibull for these three sites. The annual energy produced by the BWC XL.1 1KW wind machine is obtained and compared. The analysis shows that in the south west of Algeria, at 10 m height, the available wind power was found to vary between 136.59 W/m2 and 231.04 W/m2. The highest potential wind power was found at Adrar, with 21h per day and the mean wind speed is above 6 m/s. Besides, it is found that the annual wind energy generated by that machine lie between 512 KWh and 1643.2 kWh. However, the wind resource appears to be suitable for power production on the sahara and it could provide a viable substitute to diesel oil for irrigation pumps and rural electricity generation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Weibull%20distribution" title="Weibull distribution">Weibull distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters%20of%20Wiebull" title=" parameters of Wiebull"> parameters of Wiebull</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title=" wind energy"> wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine" title=" wind turbine"> wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=operating%20hours" title=" operating hours"> operating hours</a> </p> <a href="https://publications.waset.org/abstracts/19968/wind-power-potential-in-selected-algerian-sahara-regions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19968.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">495</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30348</span> Wind Turbines Optimization: Shield Structure for a High Wind Speed Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Daniyar%20Seitenov">Daniyar Seitenov</a>, <a href="https://publications.waset.org/abstracts/search?q=Nazim%20Mir-Nasiri"> Nazim Mir-Nasiri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimization of horizontal axis semi-exposed wind turbine has been performed using a shield protection that automatically protects the generator shaft at extreme wind speeds from over speeding, mechanical damage and continues generating electricity during the high wind speed conditions. A semi-exposed to wind generator has been designed and its structure has been described in this paper. The simplified point-force dynamic load model on the blades has been derived for normal and extreme wind conditions with and without shield involvement. Numerical simulation has been conducted at different values of wind speed to study the efficiency of shield application. The obtained results show that the maximum power generated by the wind turbine with shield does not exceed approximately the rated value of the generator, where shield serves as an automatic break for extreme wind speed values of 15 m/sec and above. Meantime the wind turbine without shield produced a power that is much larger than the rated value. The optimized horizontal axis semi-exposed wind turbine with shield protection is suitable for low and medium power generation when installed on the roofs of high rise buildings for harvesting wind energy. Wind shield works automatically with no power consumption. The structure of the generator with the protection, math simulation of kinematics and dynamics of power generation has been described in details in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=renewable%20energy" title="renewable energy">renewable energy</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine" title=" wind turbine"> wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine%20optimization" title=" wind turbine optimization"> wind turbine optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20wind%20speed" title=" high wind speed"> high wind speed</a> </p> <a href="https://publications.waset.org/abstracts/99809/wind-turbines-optimization-shield-structure-for-a-high-wind-speed-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99809.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">179</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30347</span> Vibration Signals of Small Vertical Axis Wind Turbines </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aqoul%20H.%20H.%20Alanezy">Aqoul H. H. Alanezy</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20M.%20Abdelsalam"> Ali M. Abdelsalam</a>, <a href="https://publications.waset.org/abstracts/search?q=Nouby%20M.%20Ghazaly"> Nouby M. Ghazaly</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, progress has been made in increasing the renewable energy share in the power sector particularly in the wind. The experimental study conducted in this paper aims to investigate the effects of number of blades and inflow wind speed on vibration signals of a vertical axis Savonius type wind turbine. The operation of the model of Savonius type wind turbine is conducted to compare two, three and four blades wind turbines to show vibration amplitudes related with wind speed. It is found that the increase of the number of blades leads to decrease of the vibration magnitude. Furthermore, inflow wind speed has reduced effect on the vibration level for higher number of blades. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Savonius%20type%20wind%20turbine" title="Savonius type wind turbine">Savonius type wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=number%20of%20blades" title=" number of blades"> number of blades</a>, <a href="https://publications.waset.org/abstracts/search?q=renewable%20energy" title=" renewable energy"> renewable energy</a>, <a href="https://publications.waset.org/abstracts/search?q=vibration%20signals" title=" vibration signals "> vibration signals </a> </p> <a href="https://publications.waset.org/abstracts/106098/vibration-signals-of-small-vertical-axis-wind-turbines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/106098.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">155</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30346</span> Wind Speed Prediction Using Passive Aggregation Artificial Intelligence Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tarek%20Aboueldahab">Tarek Aboueldahab</a>, <a href="https://publications.waset.org/abstracts/search?q=Amin%20Mohamed%20Nassar"> Amin Mohamed Nassar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=passive%20aggregation" title=" passive aggregation"> passive aggregation</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed%20prediction" title=" wind speed prediction"> wind speed prediction</a> </p> <a href="https://publications.waset.org/abstracts/45705/wind-speed-prediction-using-passive-aggregation-artificial-intelligence-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45705.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">450</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30345</span> Potentiality of the Wind Energy in Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20Benoudjafer">C. Benoudjafer</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20N.%20Tandjaoui"> M. N. Tandjaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Benachaiba"> C. Benachaiba</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The use of kinetic energy of the wind is in full rise in the world and it starts to be known in our country but timidly. One or more aero generators can be installed to produce for example electricity on isolated places or not connected to the electrical supply network. To use the wind as energy source, it is necessary to know first the energy needs for the population and study the wind intensity, speed, frequency and direction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Algeria" title="Algeria">Algeria</a>, <a href="https://publications.waset.org/abstracts/search?q=renewable%20energies" title=" renewable energies"> renewable energies</a>, <a href="https://publications.waset.org/abstracts/search?q=wind" title=" wind"> wind</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20power" title=" wind power"> wind power</a>, <a href="https://publications.waset.org/abstracts/search?q=aero-generators" title=" aero-generators"> aero-generators</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energetic%20potential" title=" wind energetic potential"> wind energetic potential</a> </p> <a href="https://publications.waset.org/abstracts/19479/potentiality-of-the-wind-energy-in-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19479.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">431</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30344</span> Wind Velocity Climate Zonation Based on Observation Data in Indonesia Using Cluster and Principal Component Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=I%20Dewa%20Gede%20Arya%20Putra">I Dewa Gede Arya Putra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Principal Component Analysis (PCA) is a mathematical procedure that uses orthogonal transformation techniques to change a set of data with components that may be related become components that are not related to each other. This can have an impact on clustering wind speed characteristics in Indonesia. This study uses data daily wind speed observations of the Site Meteorological Station network for 30 years. Multicollinearity tests were also performed on all of these data before doing clustering with PCA. The results show that the four main components have a total diversity of above 80% which will be used for clusters. Division of clusters using Ward's method obtained 3 types of clusters. Cluster 1 covers the central part of Sumatra Island, northern Kalimantan, northern Sulawesi, and northern Maluku with the climatological pattern of wind speed that does not have an annual cycle and a weak speed throughout the year with a low-speed ranging from 0 to 1,5 m/s虏. Cluster 2 covers the northern part of Sumatra Island, South Sulawesi, Bali, northern Papua with the climatological pattern conditions of wind speed that have annual cycle variations with low speeds ranging from 1 to 3 m/s虏. Cluster 3 covers the eastern part of Java Island, the Southeast Nusa Islands, and the southern Maluku Islands with the climatological pattern of wind speed conditions that have annual cycle variations with high speeds ranging from 1 to 4.5 m/s虏. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PCA" title="PCA">PCA</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster" title=" cluster"> cluster</a>, <a href="https://publications.waset.org/abstracts/search?q=Ward%27s%20method" title=" Ward's method"> Ward's method</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a> </p> <a href="https://publications.waset.org/abstracts/132942/wind-velocity-climate-zonation-based-on-observation-data-in-indonesia-using-cluster-and-principal-component-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132942.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">195</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30343</span> Wind Power Density and Energy Conversion in Al-Adwas Ras-Huwirah Area, Hadhramout, Yemen</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bawadi%20M.%20A.">Bawadi M. A.</a>, <a href="https://publications.waset.org/abstracts/search?q=Abbad%20J.%20A."> Abbad J. A.</a>, <a href="https://publications.waset.org/abstracts/search?q=Baras%20E.%20A."> Baras E. A.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was conducted to assess wind energy resources in the area of Al-Adwas Ras-Huwirah Hadhramout Governorate, Yemen, through using statistical calculations, the Weibull model and SPSS program were used in the monthly and the annual to analyze the wind energy resource; the convergence of wind energy; turbine efficiency in the selected area. Wind speed data was obtained from NASA over a period of ten years (2010-2019) and at heights of 50 m above ground level. Probability distributions derived from wind data and their distribution parameters are determined. The density probability function is fitted to the measured probability distributions on an annual basis. This study also involves locating preliminary sites for wind farms using Geographic Information System (GIS) technology. This further leads to maximizing the output energy from the most suitable wind turbines in the proposed site. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20speed%20analysis" title="wind speed analysis">wind speed analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=Yemen%20wind%20energy" title=" Yemen wind energy"> Yemen wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20power%20density" title=" wind power density"> wind power density</a>, <a href="https://publications.waset.org/abstracts/search?q=Weibull%20distribution%20model" title=" Weibull distribution model"> Weibull distribution model</a> </p> <a href="https://publications.waset.org/abstracts/165480/wind-power-density-and-energy-conversion-in-al-adwas-ras-huwirah-area-hadhramout-yemen" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165480.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">83</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30342</span> Exploring the Influence of Wind on Wildfire Behavior in China: A Data-Driven Study Using Machine Learning and Remote Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rida%20Kanwal">Rida Kanwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang%20Yuhui"> Wang Yuhui</a>, <a href="https://publications.waset.org/abstracts/search?q=Song%20Weiguo"> Song Weiguo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities, with wind acting as a critical driving factor. This study combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. Landsat 8 satellite images were used to estimate the difference normalized burn ratio (dNBR), representing prefire and postfire vegetation conditions. Wind data was analyzed through geographic information system (GIS) mapping. Correlation analysis between wind speed and fire radiative power (FRP) revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was applied to determine the effect of wind speed on FRP. The results identified high wind speed as a key factor contributing to the surge in FRP. Wind-rose plots showed winds blowing to the northwest (NW), aligning with the wildfire spread. This model was further validated with data from other provinces across China. This study integrated ML, RS, and GIS to analyze wildfire behavior, providing effective strategies for prediction and management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wildfires" title="wildfires">wildfires</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20behavior" title=" wildfire behavior"> wildfire behavior</a> </p> <a href="https://publications.waset.org/abstracts/192554/exploring-the-influence-of-wind-on-wildfire-behavior-in-china-a-data-driven-study-using-machine-learning-and-remote-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192554.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">20</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30341</span> Effect of Drag Coefficient Models concerning Global Air-Sea Momentum Flux in Broad Wind Range including Extreme Wind Speeds</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takeshi%20Takemoto">Takeshi Takemoto</a>, <a href="https://publications.waset.org/abstracts/search?q=Naoya%20Suzuki"> Naoya Suzuki</a>, <a href="https://publications.waset.org/abstracts/search?q=Naohisa%20Takagaki"> Naohisa Takagaki</a>, <a href="https://publications.waset.org/abstracts/search?q=Satoru%20Komori"> Satoru Komori</a>, <a href="https://publications.waset.org/abstracts/search?q=Masako%20Terui"> Masako Terui</a>, <a href="https://publications.waset.org/abstracts/search?q=George%20Truscott"> George Truscott</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn鈥檛 been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven鈥檛 discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn鈥檛 discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=air-sea%20interaction" title="air-sea interaction">air-sea interaction</a>, <a href="https://publications.waset.org/abstracts/search?q=drag%20coefficient" title=" drag coefficient"> drag coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=air-sea%20momentum%20flux" title=" air-sea momentum flux"> air-sea momentum flux</a>, <a href="https://publications.waset.org/abstracts/search?q=CFD%20%28Computational%20Fluid%20Dynamics%29" title=" CFD (Computational Fluid Dynamics)"> CFD (Computational Fluid Dynamics)</a> </p> <a href="https://publications.waset.org/abstracts/41397/effect-of-drag-coefficient-models-concerning-global-air-sea-momentum-flux-in-broad-wind-range-including-extreme-wind-speeds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41397.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">371</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30340</span> Experimental and Computational Fluid Dynamics Analysis of Horizontal Axis Wind Turbine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saim%20Iftikhar%20Awan">Saim Iftikhar Awan</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhan%20Ali"> Farhan Ali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wind power has now become one of the most important resources of renewable energy. The machine which extracts kinetic energy from wind is wind turbine. This work is all about the electrical power analysis of horizontal axis wind turbine to check the efficiency of different configurations of wind turbines to get maximum output and comparison of experimental and Computational Fluid Dynamics (CFD) results. Different experiments have been performed to obtain that configuration with the help of which we can get the maximum electrical power output by changing the different parameters like the number of blades, blade shape, wind speed, etc. in first step experimentation is done, and then the similar configuration is designed in 3D CAD software. After a series of experiments, it has been found that the turbine with four blades at an angle of 75掳 gives maximum power output and increase in wind speed increases the power output. The models designed on CAD software are imported on ANSYS-FLUENT to predict mechanical power. This mechanical power is then converted into electrical power, and the results were approximately the same in both cases. In the end, a comparison has been done to compare the results of experiments and ANSYS-FLUENT. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computational%20analysis" title="computational analysis">computational analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20efficiency" title=" power efficiency"> power efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title=" wind energy"> wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine" title=" wind turbine"> wind turbine</a> </p> <a href="https://publications.waset.org/abstracts/110867/experimental-and-computational-fluid-dynamics-analysis-of-horizontal-axis-wind-turbine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110867.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">159</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30339</span> A Hybrid Genetic Algorithm and Neural Network for Wind Profile Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Saiful%20Islam">M. Saiful Islam</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Mohandes"> M. Mohandes</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rehman"> S. Rehman</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Badran"> S. Badran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20profile" title="wind profile">wind profile</a>, <a href="https://publications.waset.org/abstracts/search?q=vertical%20extrapolation%20of%20wind" title=" vertical extrapolation of wind"> vertical extrapolation of wind</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title=" artificial neural network"> artificial neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20machine%20learning" title=" hybrid machine learning "> hybrid machine learning </a> </p> <a href="https://publications.waset.org/abstracts/27766/a-hybrid-genetic-algorithm-and-neural-network-for-wind-profile-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27766.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">490</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30338</span> Expanding the Evaluation Criteria for a Wind Turbine Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ivan%20Balachin">Ivan Balachin</a>, <a href="https://publications.waset.org/abstracts/search?q=Geanette%20Polanco"> Geanette Polanco</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiang%20%20Xingliang"> Jiang Xingliang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hu%20Qin"> Hu Qin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=field%20data%20processing" title="field data processing">field data processing</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20determination" title=" regression determination"> regression determination</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine%20performance" title=" wind turbine performance"> wind turbine performance</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine%20placing" title=" wind turbine placing"> wind turbine placing</a>, <a href="https://publications.waset.org/abstracts/search?q=yaw%20system%20losses" title=" yaw system losses"> yaw system losses</a> </p> <a href="https://publications.waset.org/abstracts/81619/expanding-the-evaluation-criteria-for-a-wind-turbine-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81619.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">390</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30337</span> Wind Resource Estimation and Economic Analysis for Rakiraki, Fiji</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kaushal%20Kishore">Kaushal Kishore</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Immense amount of imported fuels are used in Fiji for electricity generation, transportation and for carrying out miscellaneous household work. To alleviate its dependency on fossil fuel, paramount importance has been given to instigate the utilization of renewable energy sources for power generation and to reduce the environmental dilapidation. Amongst the many renewable energy sources, wind has been considered as one of the best identified renewable sources that are comprehensively available in Fiji. In this study the wind resource assessment for three locations in Rakiraki, Fiji has been carried out. The wind resource estimation at Rokavukavu, Navolau and at Tuvavatu has been analyzed. The average wind speed at 55 m above ground level (a.g.l) at Rokavukavu, Navolau, and Tuvavatu sites are 5.91 m/s, 8.94 m/s and 8.13 m/s with the turbulence intensity of 14.9%, 17.1%, and 11.7% respectively. The moment fitting method has been used to estimate the Weibull parameter and the power density at each sites. A high resolution wind resource map for the three locations has been developed by using Wind Atlas Analysis and Application Program (WAsP). The results obtained from WAsP exhibited good wind potential at Navolau and Tuvavatu sites. A wind farm has been proposed at Navolau and Tuvavatu site that comprises six Vergnet 275 kW wind turbines at each site. The annual energy production (AEP) for each wind farm is estimated and an economic analysis is performed. The economic analysis for the proposed wind farms at Navolau and Tuvavatu sites showed a payback period of 5 and 6 years respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=annual%20energy%20production" title="annual energy production">annual energy production</a>, <a href="https://publications.waset.org/abstracts/search?q=Rakiraki%20Fiji" title=" Rakiraki Fiji"> Rakiraki Fiji</a>, <a href="https://publications.waset.org/abstracts/search?q=turbulence%20intensity" title=" turbulence intensity"> turbulence intensity</a>, <a href="https://publications.waset.org/abstracts/search?q=Weibull%20parameter" title=" Weibull parameter"> Weibull parameter</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a>, <a href="https://publications.waset.org/abstracts/search?q=Wind%20Atlas%20Analysis%20and%20Application%20Program" title=" Wind Atlas Analysis and Application Program"> Wind Atlas Analysis and Application Program</a> </p> <a href="https://publications.waset.org/abstracts/104322/wind-resource-estimation-and-economic-analysis-for-rakiraki-fiji" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/104322.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30336</span> Signal Processing Approach to Study Multifractality and Singularity of Solar Wind Speed Time Series</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tushnik%20Sarkar">Tushnik Sarkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mofazzal%20H.%20Khondekar"> Mofazzal H. Khondekar</a>, <a href="https://publications.waset.org/abstracts/search?q=Subrata%20Banerjee"> Subrata Banerjee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1<sup>st </sup>January, 1997 to 28<sup>th</sup> October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=detrended%20fluctuation%20analysis" title="detrended fluctuation analysis">detrended fluctuation analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20hurst%20exponent" title=" generalized hurst exponent"> generalized hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=holder%20exponents" title=" holder exponents"> holder exponents</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractal%20exponent" title=" multifractal exponent"> multifractal exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractal%20spectrum" title=" multifractal spectrum"> multifractal spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=singularity%20spectrum" title=" singularity spectrum"> singularity spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series%20analysis" title=" time series analysis"> time series analysis</a> </p> <a href="https://publications.waset.org/abstracts/62350/signal-processing-approach-to-study-multifractality-and-singularity-of-solar-wind-speed-time-series" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62350.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30335</span> Design of 100 kW Induction Generator for Wind Power Plant at Tamanjaya Village-Sukabumi</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andri%20Setiyoso">Andri Setiyoso</a>, <a href="https://publications.waset.org/abstracts/search?q=Agus%20Purwadi"> Agus Purwadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Nanda%20Avianto%20Wicaksono"> Nanda Avianto Wicaksono</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper present about induction generator design for 100kW power output capacity. Induction machine had been chosen because of the capability for energy conversion from electric energy to mechanical energy and vise-versa with operation on variable speed condition. Stator Controlled Induction Generator (SCIG) was applied as wind power plant in Desa Taman Jaya, Sukabumi, Indonesia. Generator was designed to generate power 100 kW with wind speed at 12 m/s and survival condition at speed 21 m/s. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title="wind energy">wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=induction%20generator" title=" induction generator"> induction generator</a>, <a href="https://publications.waset.org/abstracts/search?q=Stator%20Controlled%20Induction%20Generator%20%28SCIG%29" title=" Stator Controlled Induction Generator (SCIG)"> Stator Controlled Induction Generator (SCIG)</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20speed%20generator" title=" variable speed generator"> variable speed generator</a> </p> <a href="https://publications.waset.org/abstracts/21929/design-of-100-kw-induction-generator-for-wind-power-plant-at-tamanjaya-village-sukabumi" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21929.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">504</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30334</span> Wind Speed Data Analysis in Colombia in 2013 and 2015</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harold%20P.%20Villota">Harold P. Villota</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandro%20Osorio%20B."> Alejandro Osorio B.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=complementarity" title="complementarity">complementarity</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a>, <a href="https://publications.waset.org/abstracts/search?q=renewable" title=" renewable"> renewable</a>, <a href="https://publications.waset.org/abstracts/search?q=colombia" title=" colombia"> colombia</a>, <a href="https://publications.waset.org/abstracts/search?q=characteri" title=" characteri"> characteri</a>, <a href="https://publications.waset.org/abstracts/search?q=characterization" title=" characterization"> characterization</a>, <a href="https://publications.waset.org/abstracts/search?q=imputation" title=" imputation"> imputation</a> </p> <a href="https://publications.waset.org/abstracts/148690/wind-speed-data-analysis-in-colombia-in-2013-and-2015" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148690.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">164</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30333</span> Artificial Neural Network Approach for Modeling Very Short-Term Wind Speed Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Joselito%20Medina-Marin">Joselito Medina-Marin</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20G.%20Serna-Diaz"> Maria G. Serna-Diaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Juan%20C.%20Seck-Tuoh-Mora"> Juan C. Seck-Tuoh-Mora</a>, <a href="https://publications.waset.org/abstracts/search?q=Norberto%20Hernandez-Romero"> Norberto Hernandez-Romero</a>, <a href="https://publications.waset.org/abstracts/search?q=Irving%20Barrag%C3%A1n-Vite"> Irving Barrag谩n-Vite</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, M茅xico, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r虏=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r虏 value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20power%20generation" title="wind power generation">wind power generation</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a>, <a href="https://publications.waset.org/abstracts/search?q=coefficient%20of%20determination" title=" coefficient of determination"> coefficient of determination</a> </p> <a href="https://publications.waset.org/abstracts/157836/artificial-neural-network-approach-for-modeling-very-short-term-wind-speed-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157836.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">124</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wind%20speed%20analysis&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wind%20speed%20analysis&page=3">3</a></li> <li class="page-item"><a class="page-link" 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