Relevant bibliographies by topics / Wind power Wind power Wind power

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Wind power Wind power Wind power'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Wind power Wind power Wind power"

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Carroll, Paula, Lucy Cradden, and Mícheál Ó hÉigeartaigh. "High Resolution Wind Power and Wind Drought Models." International Journal of Thermal and Environmental Engineering 16, no. 1 (August 9, 2018): 27–36. http://dx.doi.org/10.5383/ijtee.16.01.004.

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Nah, Do-Baek, Hyo-Soon Shin, and Duck-Joo Nah. "Offshore Wind Power, Review." Journal of Energy Engineering 20, no. 2 (June 30, 2011): 143–53. http://dx.doi.org/10.5855/energy.2011.20.2.143.

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Obukhov, S. G. "DYNAMIC WIND SPEED MODEL FOR SOLVING WIND POWER PROBLEMS." Eurasian Physical Technical Journal 17, no. 1 (June 2020): 77–84. http://dx.doi.org/10.31489/2020no1/77-84.

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Prajapati, Urvashi, Deepika Chauhan, and Md Asif Iqbal. "Hybrid Solar Wind Power Generation." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1533–37. http://dx.doi.org/10.31142/ijtsrd11359.

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Trejos–Grisales, Luz, Cristian Guarnizo–Lemus, and Sergio Serna. "Overall Description of Wind Power." Ingeniería y Ciencia 10, no. 19 (January 2014): 99–126. http://dx.doi.org/10.17230/ingciencia.10.19.5.

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This paper presents a general overview of the main characteristics of the wind power systems, also considerations about the simulation models andthe most used Maximum Power Point Tracker (MPPT) techniques are made. Some simulation results are shown and conclusions about the workare given.
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Green, K. H. "Wind power." IEE Review 39, no. 1 (1993): 29. http://dx.doi.org/10.1049/ir:19930011.

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ARAKAWA, Chuichi. "Wind Power." Journal of the Society of Mechanical Engineers 109, no. 1052 (2006): 549–52. http://dx.doi.org/10.1299/jsmemag.109.1052_549.

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Gipe, Paul. "“Wind Power”." Wind Engineering 28, no. 5 (September 2004): 629–31. http://dx.doi.org/10.1260/0309524043028145.

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Carlman, Inga. "Wind power in Denmark! Wind power in Sweden?" Journal of Wind Engineering and Industrial Aerodynamics 27, no. 1-3 (January 1988): 337–45. http://dx.doi.org/10.1016/0167-6105(88)90048-7.

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Kennedy, J., B. Fox, and J. Morrow. "Working with wind - wind power." Engineering & Technology 3, no. 3 (February 23, 2008): 52–55. http://dx.doi.org/10.1049/et:20080313.

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Dissertations / Theses on the topic "Wind power Wind power Wind power"

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Makhalas, Kharsan Al, and Faisal Alsehlli. "Wind Power." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4336.

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This Bachelor thesis has been written at the Blekinge Institute of Technology. This thesis concentrates on the wind power and their components, also the large wind farm is studied. The electrical power is generated by using the power in wind to drive a wind turbine to produce mechanical power. This mechanical power can be converted into electrical power by using electrical induction generators. There are two types of the wind turbines, the horizontal axis and vertical axis wind turbine, where the horizontal axis wind turbine is mostly used and was studied in this thesis. The rotor can be placed in two directions: an upwind rotor where the blade of turbine faces to the wind, so it operates more smoothly and transmit more power. The other type is a downwind rotor which orients itself with respect for the wind direction. Moreover, the tower shadow makes the blade to flex, consequently resulting in fatigue, noise, and reduces output of the power. The modern wind turbine has been built with an odd number of blades which is important for the stability of the turbine. The rotor with an odd number of blades can be considered to be similar to a disc when calculating the dynamic properties of the machine. The main idea of this thesis is to study the wind power in general and large wind parks specifically. The Horns Rev wind park was taken as an example of a wind park in Denmark and the Gotland wind park as an example of a wind park in Sweden too. Into account, the distance between wind turbine in the wind direction cannot be too small. If the wind turbines are located to close to each other, the wind will be more and more turbulent after it passes through each single wind turbine. This would lead to that wind turbines downstream in the wind park, and it might even have to shut down due to that mechanical loading gets to high during strong conditions. This is due to the fact that when wind passes through the rotor of the wind turbine it gets very turbulent and the wind speed is decreased. The minimum length of the rotor should be approximately 5-7 rotor diameters to avoid that issue. Gotland Energy AB (GEAB) considered, that high voltage direct current light would be the only realistic way to solve the technical problems for the high amount of wind power in-feed. One result is that The stability of voltage during transient events, has become much better by using the high voltage direct current light so that the output current stability from the asynchronous generators have been improved, which reduces the stresses on the AC grid and on the mechanical construction of the windmills.
In general the wind turbines with three blades accommodated a thicker root are used. It is obvious that, the less number of blades on the wind turbine, the cost of material and manufacturing will be lower. It is worthy to mentioned that, the modern wind turbine has been built with an odd number of blades. When the length of the blade increases the deflection of blade tip due to axial wind force also increase as well. So without consider the increase in length of blade may lead to dangerous situation of collision of tower and blade. Moreover, by increasing the number of blades cost of the system would increased as well. The limit of transfer for the AC transmission system depends on the distance from shore and is therefore physically limited by this. AC large wind parks that are placed at a long distance from the shore, which means AC long transmission line, and more drop voltage A solution to AC long transmission line, it could be to decrease the offshore frequency and use a low frequency AC networks. There is a suggestion by for instance (Schütte, Gustavsson and Ström 2011). The usages of a low frequency system are in electrified railway systems, where the frequency ranges from 16.67 Hz to 25 Hz. However, the network of a low frequency would allow a simpler design of the offshore WTs and The aerodynamic rotor of a large WT operates at maximum revolutions at 15-20 rpm. The lower frequency would then allow a smaller gear ratio for turbines with a gearbox, or decrease the poles number for WTs with direct driven generators. This would lead to lighter and cheaper turbines. One of the disadvantages by using a low frequency system is the size of transformer would be increased, and hence, the costs of transformer will increased too. The operator of the grid, Gotland Energy AB (GEAB) considered, that HVDC light would be the only realistic way to solve the technical problems for the high amount of wind power in-feed. The experiences have supported expected improvements in the characteristics for example: - Stability in the system arose. - Reactive demands, power flows, as well as voltage level in the harmonic and system were reduced. - Flicker problems were eliminated with the installation of HVDC light and transient phenomena disappeared. Moreover, Overall experiences of Gotland Energy AB (GEAB) are that the control of power flow from the converters makes the AC grid easier to observe than a conventional AC network and the power variations do not stress the AC grid as much as in normal network. Voltage quality has been better with the increased wind power production. A topic to study in the future is the consequences of blackouts in power supply with many wind power farm.
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Ülker, Muhammed Akif. "Balancing of Wind Power : Optimization of power systems which include wind power systems." Thesis, Högskolan på Gotland, Institutionen för kultur, energi och miljö, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hgo:diva-1335.

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In the future, renewable energy share, especially wind power share, in electricity generation is expected to increase. Due to nature of the wind, wind power generation pattern includes uncertainties which affects the energy prices in the electricity markets. New simulations are needed for efficient planning process for the resources in the power systems to address the uncertainties in demand, generation, legal, economical and technical limitations. In this study, the aspects of planning process for wind power generation is described and some example scenarios are implemented with the help of MATLAB software.
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SILVA, ILITCH VITALI GOMES DA. "THE WIND FORECAST FOR WIND POWER GENERATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2010. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16824@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
A energia eólica é uma das alternativas mais promissoras para geração de energia elétrica, pois assegura a diversidade e segurança no fornecimento de energia e atende à necessidade premente de reduzir os níveis de emissão de gases poluentes. Na operação de sistemas elétricos com forte presença de geração eólica é fundamental prever com pelo menos um dia de antecedência os valores futuros (pelo menos horários) da veloci-dade do vento, pois assim pode-se avaliar a disponibilidade de energia para o próximo dia, uma informação útil no despacho das unidades geradoras e no controle do sistema elétrico. A proposta dessa dissertação objetiva especificamente desenvolver modelos de previsão de curto prazo da velocidade do vento, baseado em técnicas de inteligência artificial, modelo da rede neural artificial e neuro-fuzzy adaptativa (ANFIS) e um mode-lo Estatístico composto por um modelo de regressão harmônica e Box-Jenkins. Para aplicação da metodologia considerou-se o município de São João do Cariri (Estado de Paraíba), onde está localizada uma das estações de referência do projeto SONDA (Sis-tema Nacional de Dados Ambientais para o setor de energia). O desempenho dos mode-los rede neural, neuro-fuzzy (ANFIS) e modelo Estatístico são comparados nas previ-sões de 6 horas, 12 horas, 18 h e 24horas a frente. Os resultados obtidos mostram o me-lhor desempenho da modelagem ANFIS e encorajam novos estudos no tema.
Wind power is one of the most promising options for power generation. It ensures the diversity and security of energy supply and meets the pressing need to reduce the levels of emission of polluting gases. In the operation of electrical systems with a strong presence of wind generation, it is essential to provide at least one day in advance the future values (at least hourly) of wind speed, so that we can assess the availability of energy for the next day, a useful information in the order of the generating units and electrical control system. The purpose of this dissertation aims to develop models spe-cifically to develop models to forecast short-term wind speed, based on artificial intelligence techniques, artificial neural network model and adaptive neuro-fuzzy Systems (ANFIS) and a statistical model composed of a harmonic regression model and Box-Jenkins. For application of the methodology, the city of São João do Cariri (State of Paraíba), where a reference station of SONDA project (National Environmental Data for the energy sector) is located, was considered.To apply the methodology was consi-dered the city of the ray tracing model (State of Paraíba), which is located a station ref-erence design (National Environmental Data for the energy sector). The performance of artificial neural network model and adaptive neuro-fuzzy Systems (ANFIS) and a statis-tical model are compared mixed forecasts of 6 hours, 12 hours, 18hours and 24 hours ahead. The results show the best performance of the ANFIS model and encourage fur-ther studies on the subject.
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Andersson, Niklas, and Pontus Heijdenberg. "Wind Power Desalination System." Thesis, Halmstad University, School of Business and Engineering (SET), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-2769.

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Elin, Karlsson. "Wind power in Brazil." Thesis, Halmstad University, School of Business and Engineering (SET), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-2965.

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As welfare and industry production gets higher the demand for electricity increases. Almost 90 % of the electricity generated in Brazil is from renewable sources, 85 % of the renewable energy comes from hydropower. Even if Latin America has a lot of potential for wind power their installed capacity in only 1 % of the worlds total installed capacity. Lately more and more wind turbines and wind farms are appearing along Brazil’s over 7500 kilometer long coastline.

Osorio wind farm is the largest wind farm in Latin America with a total installed effect of 150 MW. In the same state, Rio Grande du Sul, a farmer has shown interest for using his property for wind power. The purpose of this project is to lay the foundation for a deeper investigation about using Aguapé farm’s property for wind power and to show the future possibilities for Brazilian wind power.

The study is made on set in Brazil, divided into two parts, one theoretical research part and one practical part with a field trip to Aguapé farm.

In 2002 The Brazilian Government launched the PROINFA program, Alternative Sources for Energy Incentive. This year, 2009, the first wind power projects auctions are held to increase the generation from renewable electricity sources. Wind power in Brazil has the highest production when the level in the hydropower dams are at the lowest, which by integrating the electrical generating wiht wind power makes it possible to save water and avoiding lack of electricity.

Aguapé farm is located between one of the worlds biggest fresh water lakes, Lagao dos Patos, and the Atlantic Ocean. The location has very good wind potential, almost like offshore because of the closeness to large areas of water. Road connections to the farm are functional in good and dry weather conditions and not far away a 138kV power line passes through.

Surrounding neighbors are positive to wind power which makes it easier with problem caused by wind turbines, for example noise. About 40 kilometers from the farm Lagoa do Peixe National Park is located. Suggestion from the Aguapé owner is to stop with the rice production, which is disturbing the park’s natural hydrological system, to use the property for wind turbines instead.

Conclusions of the study shows that the potential for wind power at Aguapé farm is excellent and that wind power at Aguapé farm will help both the owner, Lagoa do Peixe National Park and Brazil to a better future.

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Zhou, Yun, and Quanfeng Wang. "Wind power in China." Thesis, University of Gävle, Department of Technology and Built Environment, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-4879.

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n today's complex environment, clear and sustainable energy is needed to support society development. How to develop the sustainable energy is a core issue in China. Compared with traditional energy, Wind energy has many advantages such as non-fuel cost, less pollution. And wind energy has the absolute advantage that it is worldwide  available. In many courtiers, wind energy has become a major part of their plans for sustainable development. The primary goal of this paper is to analysis advantages and disadvantages of wind power in China and the development potential of wind power in China. In this paper the main methodology is using the information about wind power in China, which is including current situation, development stage, industry development stage, and combining the real case to analysis wind power development potential in China. There are six parts of this paper which are the overview of wind power in china; case description, analysis, conclusions, suggestion, development perspectives and imagination In the first part, the overview of wind power in china, the history of wind power in china, wind resource distribution, wind power development stages, the situation of some key regions, wind  power industry develop stage and also some policies about wind power of Chinese government are discussed. The goal of this part is giving some fundamental information about wind power in China. In the second part, a real case has been described, and according to this case, the construction cost of a wind power plant in China has been discussed. The advantages and disadvantages of wind power are also analyzed based on this case study, such as long-team return, environmental impact, and also some other problem analysis. After the analysis parts, there are the conclusion parts, those parts are about the development perspectives and imagination of wind power in China.

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Ndzukuma, Sibusiso. "Statistical tools for wind energy generation." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1020627.

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In this study we conduct wind resource assessment to evaluate the annual energy production of a wind turbine. To estimate energy production of a wind turbine over a period of time, the power characteristics of the wind turbine are integrated with the probabilities of the wind speed expected at a chosen site. The first data set was obtained from a wind farm in Denmark. We propose several probability density functions to model the distribution of the wind speed. We use techniques from nonlinear regression analysis to model the power curve of a wind turbine. The best fit distribution model is assessed by performing numeric goodness–of–fit measures and graphical analyses. Johnson’s bounded (SB) distribution provides the best fit model with the smallest Kolmogorov–Smirnov (K-S) test statistic . 15. The four parameter logistic nonlinear regression (4PL) model is determined to provide the best fit to the power curve data, according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The estimated annual energy yield is compared to the actual production of the wind turbine. Our models underestimate the actual energy production by a 1 difference. In Chapter Six we conduct data processing, analyses and comparison of wind speed distributions using a data set obtained from a measuring wind mast mounted in Humansdorp, Eastern Cape. The expected annual energy production is estimated by using the certified power curve as provided by the manufacturer of the wind turbine under study. The commonly used Weibull distribution is determined to provide the best fit distribution model to our selected models. The annual energy yield is estimated at 7.33 GWh, with a capacity factor of 41.8 percent.
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Navarrete, Pablo-Romero Javier. "Power Quality for Distributed Wind Power Generation." Thesis, KTH, Elektroteknisk teori och konstruktion, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105221.

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Wind power often is a source of voltage fluctuations and possible voltage issues are raised when considering interconnecting wind turbines to an electric grid. Also, the power electronics introduced in the wind turbines might insert more fluctuations and different PQ problems. Distributed generation seems to be a good option in order to try to mitigate these problems. The first goal of the work is to create a model of a small electric grid, using MATLAB/Simulink. The models aims to simulate various DFIG wind turbines coupled to the grid in different conditions of location and wind. Then, the main objective is to analyze the PQ in the grid with this type of turbine. For this, once the simulations have been done, the results obtained have allowed calculating different indices to study PQ in the model. Afterwards, a comparison of those indices in the different conditions is made.
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Pesoti, Paulo Murinelli. "Power system restorations assisted by wind power." Thesis, University of Strathclyde, 2018. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=30465.

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This thesis investigates power systems restoration procedure and the possibility of using wind power to assist restorations. Three main factors motivate this approach: the sharp growth on wind power production during recent years, the absence of wind power on restoration procedures, and recent blackouts cases which stability issues delayed the restoration procedure. Stability studies are the base of this investigation, where a series of tools are proposed and developed due to the disparate condition of a restoration procedure. The first tool is a power flow routine, where stochastic simulations address wind speed's randomness. This computational program calculates indexes of collapse for voltage stability. This computational routine also encompasses a methodology built from an energy function tool for visualizing power systems' vulnerable and robust areas. This thesis applies the tool for restoration analysis, where its validation has been published on an academic journal. This thesis also proposes a novel methodology for visualizing the robustness areas, which uses the energy function output to form a graphical representation as the system diagram's background. This thesis designs procedures and controllers for the dynamic simulation analysis. The first is the definition of a procedure used to simulate the synchronization of wind farms during restorations. This procedure aims to mitigate impacts caused by wind farms on power systems, where two loop controls achieve the desired response. Finally, one can find an initialization procedure for wind turbines, regarding restoration conditions. The robustness areas tool validation shows that one can achieve positive results on angular stability by reinforcing vulnerable areas. The guidelines proposed by the robustness areas tool test the Brazilian system operator's restoration procedure. A number of analysis and simulations assess the proposed approach efficiency. The IEEE 30 bus system, which is a benchmark for stability studies, shows the impact of wind power on restorations. Part of the Brazilian power system addresses the proposed methodology on a real case scenario. Finally, this thesis presents a list of recommendations, which intends to guide future works to include wind power on restorations and to extend the proposed approach to other power systems.
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Solhall, Axel, and Edvin Guéry. "Coordination of Wind Power and Hydro Power." Thesis, KTH, Industriell ekologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210740.

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The goal of this project was to calculate how much wind power could be balanced with hydro power in our designated area consisting of five hydro power stations, four villages which consume power, possible locations for wind power and one connection to the national grid. To achieve this a simulation model was constructed in the GAMS software with the goal of achieving the maximum profit from the hydro power plants by considering electricity prices, inflow of water, the physical construction of the power plants and the time of year. When this was achieved, restriction for the maximum transmission load on the power grid was added as well as local wind power production as to simulate the implementation of new power sources on an old system and power grid. This would result in a maximum income in SEK as well as the most wind power which could be maintained and balanced by the designated system. This project shows how to find the optimal way to use hydro power and wind power as well as how the integration between different sources of electricity production could work, which is vital for a future powered by renewable energy and will help towards lowering emissions.
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Books on the topic "Wind power Wind power Wind power"

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Fitzgerald, Stephanie. Wind power. New York, NY: Chelsea Clubhouse, 2010.

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Fitzgerald, Stephanie. Wind power. New York, NY: Chelsea Clubhouse, 2010.

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Gipe, Paul. Wind power. London: James & James, 2004.

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Parks, Peggy J. Wind power. San Diego, CA: Daniel A. Leone, Publisher, 2009.

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Richards, Julie. Wind power. North Mankato, Minn: Smart Apple Media, 2003.

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Pipe, Jim. Wind power. Mankato, Minn: Stargazer Books, 2009.

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Wind power. Ann Arbor, Mich: Cherry Lake Pub., 2013.

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Saunders, N. Wind power. Milwaukee, WI, USA: Gareth Stevens Pub., 2008.

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Morris, Neil. Wind power. North Mankato, MN: Smart Apple Media, 2006.

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Cross, Mike. Wind power. New York: Gloucester Press, 1985.

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Book chapters on the topic "Wind power Wind power Wind power"

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Söder, Lennart. "Wind Power wind power , Introduction." In Encyclopedia of Sustainability Science and Technology, 12213–17. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_75.

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Söder, Lennart. "Wind Power wind power , Introduction." In Renewable Energy Systems, 1780–84. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5820-3_75.

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Ackermann, Thomas, and Rena Kuwahata. "Global Wind Power wind power Installations wind power installations." In Encyclopedia of Sustainability Science and Technology, 4474–92. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_76.

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Ackermann, Thomas, and Rena Kuwahata. "Global Wind Power wind power Installations wind power installations." In Renewable Energy Systems, 1020–38. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5820-3_76.

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Dalén, Göran. "Offshore Wind Power offshore wind power." In Encyclopedia of Sustainability Science and Technology, 7425–45. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_81.

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Söder, Lennart, and Hannele Holttinen. "Wind Power Balancing wind power balancing." In Encyclopedia of Sustainability Science and Technology, 12097–134. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_85.

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Söder, Lennart, and Hannele Holttinen. "Wind Power Balancing wind power balancing." In Renewable Energy Systems, 1663–99. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5820-3_85.

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Francois, Bruno, and Benoît Robyns. "Wind Power." In Electricity Production from Renewable Energies, 75–147. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118562611.ch3.

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Bigelow, Philip. "Wind Power." In Encyclopedia of Quality of Life and Well-Being Research, 7137–41. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3670.

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(Stathis) Michaelides, Efstathios E. "Wind Power." In Green Energy and Technology, 231–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-20951-2_8.

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Conference papers on the topic "Wind power Wind power Wind power"

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Plet, C. "Power frequency optimisation." In Offshore Wind Technology. Institution of Engineering and Technology, 2015. http://dx.doi.org/10.1049/ic.2015.0069.

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Parker, Ryan S. "Wind Effects on Air-Cooled Condensers: Wind-Tunnel 2-D Flow Fields for Base Case, Wind Screens, and Louvers." In ASME 2017 Power Conference Joint With ICOPE-17 collocated with the ASME 2017 11th International Conference on Energy Sustainability, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/power-icope2017-3646.

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Detailed 2-axis hot-wire anemometry measurements were conducted around a scale Air-Cooled Condenser (ACC) model within an atmospheric boundary layer wind-tunnel. The measurements were taken for the “standard” flow field, as well as the effects of using partial wind screens and louvers as mitigation measures. This provides a representation of the complex 2-D flow field present underneath an operating ACC when subjected to various speed cross winds. Optimal ACC operation is achieved when all fans generate a uniform flow pattern into the plenum chamber of the ACC, and this is dependent on the speed and direction of the air at the inlet. The wind-tunnel measurements support the assertion that wind screens reduce the horizontal wind speed directly downstream; however, this comes with a marked increase in turbulence. The results suggest a wind-screen covering a smaller portion (6% tested) of the ACC inlet may be more beneficial than the more common 50% coverage.
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Wan, Yih-Huei, Michael Milligan, and Brian Parsons. "Output Power Correlation Between Nearby Wind Power Plants." In ASME 2003 Wind Energy Symposium. ASMEDC, 2003. http://dx.doi.org/10.1115/wind2003-1342.

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The National Renewable Energy Laboratory (NREL) started a project in 2000 to record long-term, high-frequency (1-Hz) wind power output data from large commercial wind power plants. Outputs from about 330 MW of wind generating capacity from wind power plants in Buffalo Ridge, Minnesota, and Storm Lake, Iowa, are being recorded. Analysis of the collected data shows that although very short-term wind power fluctuations are stochastic, the persistent nature of wind and the large number of turbines in a wind power plant tend to limit the magnitudes and rates of changes in the levels of wind power. Analyses of power data confirm that spatial separation greatly reduces variations in the combined wind power output relative to output from a single wind power plant. Data show that high frequency variations of wind power from two wind power plants 200 km apart are independent of each other, but low frequency power changes can be highly correlated. This fact suggests that time-synchronized power data and meteorological data can aid in the development of statistical models for wind power forecasting.
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Wan, Yih-Huei, and Demy Bucaneg. "Short-Term Power Fluctuations of Large Wind Power Plants." In ASME 2002 Wind Energy Symposium. ASMEDC, 2002. http://dx.doi.org/10.1115/wind2002-58.

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With electric utilities and other power providers showing increased interest in wind power and with growing penetration of wind capacity into the market, questions about how wind power fluctuations affect power system operations and about wind power’s ancillary services requirements are receiving lots of attention. To evaluate short-term wind power fluctuations and the range of ancillary service of wind power plants, the National Renewable Energy Laboratory (NREL), in cooperation with Enron Wind, has started a project to record output power from several large commercial wind power plants at the 1-Hertz rate. The project’s purpose is to acquire actual, long-term wind power output data for analyzing wind power fluctuations, frequency distribution of the changes, the effects of spatial diversity, and wind power ancillary services. This paper presents statistical properties of the data collected so far and discusses the results of data analysis. Although the efforts to monitor wind power plants are ongoing, we can already conclude from the available data that despite the stochastic nature of wind power fluctuations, the magnitudes and rates of wind power changes caused by wind speed variations are seldom extreme, nor are they totally random. Their values are bounded in narrow ranges. Power output data also show significant spatial variations within a large wind power plant.
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Wan, Y. H., and D. Bucane. "Short-term power fluctuations of large wind power plants." In 2002 ASME Wind Energy Symposium. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-58.

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Yuhong Zhang, Ming Zhou, and Gengyin Li. "Wind power price regulation considering wind power fluctuation." In 2010 5th International Conference on Critical Infrastructure (CRIS). IEEE, 2010. http://dx.doi.org/10.1109/cris.2010.5617571.

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Exizidis, L., J. Kazempour, P. Pinson, Z. De Greve, and F. Vallee. "Strategic wind power trading considering rival wind power production." In 2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia). IEEE, 2016. http://dx.doi.org/10.1109/isgt-asia.2016.7796500.

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Choudhary, A. K., K. G. Upadhyay, and M. M. Tripathi. "Soft computing applications in wind speed and power prediction for wind energy." In 2012 IEEE Fifth Power India Conference. IEEE, 2012. http://dx.doi.org/10.1109/poweri.2012.6479588.

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Weimbs, M., W. Schellong, and O. Herrera Sánchez. "Wind Farm Planning Regarding Extreme Wind Conditions." In Power and Energy Systems. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.684-059.

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Singh, Ankita, K. Gurtej, Gourav Jain, Faraz Nayyar, and M. M. Tripathi. "Short term wind speed and power forecasting in Indian and UK wind power farms." In 2016 IEEE 7th Power India International Conference (PIICON). IEEE, 2016. http://dx.doi.org/10.1109/poweri.2016.8077339.

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Reports on the topic "Wind power Wind power Wind power"

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Wan, Y. H. Wind Power Plant Behaviors: Analyses of Long-Term Wind Power Data. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/15009608.

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Ackerman, Aidan, Robin Hoffman, Maren King, and Meaghan Keefe. Hardscrabble Wind Power Project. Landscape Architecture Foundation, 2019. http://dx.doi.org/10.31353/cs1540.

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Jose, Zayas, Derby Michael, Gilman Patrick, Shreyas Ananthan, Eric Lantz, Jason Cotrell, Fredic Beck, and Richard Tusing. Enabling Wind Power Nationwide. Office of Scientific and Technical Information (OSTI), May 2015. http://dx.doi.org/10.2172/1220457.

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none,. Wind Power Today - 2010. Office of Scientific and Technical Information (OSTI), May 2010. http://dx.doi.org/10.2172/1218483.

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Author, Not Given. Wind Power Career Chat. Office of Scientific and Technical Information (OSTI), January 2011. http://dx.doi.org/10.2172/1004491.

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anon. Wind Power Outlook 2004. Office of Scientific and Technical Information (OSTI), January 2004. http://dx.doi.org/10.2172/836722.

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anon. Wind power outlook 2006. Office of Scientific and Technical Information (OSTI), April 2006. http://dx.doi.org/10.2172/881759.

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David C. Morris and Dr. Will D. Swearingen. Wind Fins: Novel Lower-Cost Wind Power System. Office of Scientific and Technical Information (OSTI), October 2007. http://dx.doi.org/10.2172/917314.

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Singh, Mohit, and Surya Santoso. Dynamic Models for Wind Turbines and Wind Power Plants. Office of Scientific and Technical Information (OSTI), October 2011. http://dx.doi.org/10.2172/1028524.

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Rasson, Joseph E. Low-Maintenance Wind Power System. Office of Scientific and Technical Information (OSTI), September 2010. http://dx.doi.org/10.2172/1000354.

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