scholarly journals Wind Energy Assessment of the Sidi Daoud Wind Farm - Tunisia

Author(s):  
Fathi Ben ◽  
Mustapha Elamouri
2020 ◽  
Author(s):  
Radian Belu

Wind energy usage is increasing at fast rates due to significant technical advances, energy supply security and environmental concerns. Research is focusing among others areas on the development of reliable and accurate wind energy assessment methods. Offshore wind energy resources are usually larger than at geographically nearby onshore sites, which may offset in part higher installation, operation, and maintenance costs. Successful offshore wind energy development relies on accurate analysis and assessment of wind energy resource potential. Offshore wind assessment challenges are related to the wind turbine size, offshore installation challenges, lack of adequate and long-term wind and meteorological measurements, etc. Wind, a highly intermittent phenomenon has large spatiotemporal variability, being subject to sub-hourly, hourly, diurnal, seasonal, yearly, and climate variations in addition to their dependence on the geography and environment. Wind regime characteristics are critical to all aspect of a wind energy project, e.g. potential site identification, economic viability, equipment design, operation, management, or wind farm impacts on the electric grid. For a reliable wind energy assessment, measurements at rotor heights are required at least for one year. If such measurements are not available needs to be substituted by alternative approaches, e.g. measure-correlate-predict or numerical methods. Chapter objectives are to provide the reader with comprehensive reviews of the wind energy assessment and analysis methods.


Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2635 ◽  
Author(s):  
Alain Ulazia ◽  
Ander Nafarrate ◽  
Gabriel Ibarra-Berastegi ◽  
Jon Sáenz ◽  
Sheila Carreno-Madinabeitia

Hywind-Scotland is a wind farm in Scotland that for many reasons is at the leading edge of technology and is located at a paradigmatic study area for offshore wind energy assessment. The objective of this paper is to compute the Capacity Factor ( C F ) changes and instantaneous power generation changes due to seasonal and hourly fluctuations in air density. For that reason, the novel ERA5 reanalysis is used as a source of temperature, pressure, and wind speed data. Seasonal results for winter show that C F values increase by 3% due to low temperatures and denser air, with economical profit consequences of tens of thousands (US$). Hourly results show variations of 7% in air density and of 26% in power generation via FAST simulations, emphasizing the need to include air density in short-term wind energy studying.


Author(s):  
Md Nahid Pervez ◽  
Mehmet Sözen

In conducting the siting analysis of a possible on-shore or off-shore wind farm, computational tools are required to analyze the extensive wind data collected over long periods of time in order to estimate the energy that can be harnessed at that particular location. The major parameters that play a crucial role in this are the wind speed, wind direction, and presence of turbulence in the upcoming wind. However, estimation of the potential for electrical energy generation from wind at a particular site is quite complex and prone to error due to the uncertain nature of the wind. The yaw error, which is the difference between the direction of wind and the normal to the face of the rotor, can reduce the power output of a wind turbine significantly. Zero inertia assumption for the turbine rotor used by multiple assessment tools result in overestimation of the power output. For an accurate estimation of the energy that can be harnessed, the effect of directional change of the wind should be incorporated along with the other obvious parameters such as the wind speed, the effect of landscape and altitude. Most modern utility-scale wind turbines are equipped with yaw motion controller and direction measuring sensors that help change the yaw angle of the wind turbine to adjust for the wind direction. A dynamic control model and the corresponding scheme have to be incorporated in the energy estimation process. A wind energy assessment analysis for a potential off-shore wind farm in Lake Michigan is currently under way. An unmanned marine buoy, equipped with LIDAR-based data acquisition system, is deployed in Lake Michigan and data are measured at six different altitudes starting from 55 m and up to 175 m. As project participants, the authors have been working on developing a versatile, flexible and precise model and software tool to evaluate the potential for electrical energy generation. A MATLAB based program has been developed for this purpose, equipped with the capability of working with different data formats and different time averaged data sets. A dynamic model capable of considering the change in wind direction and adjusting the yaw angle has been developed as a part of the MATLAB program. The dynamic model evaluates the yaw error and implements a scheme for the adjustment of the orientation of the wind turbine in order to provide an accurate estimate of the amount of wind energy that can be converted into electrical energy. The algorithm for this dynamic model and the results obtained are discussed in this paper.


2010 ◽  
Vol 35 (12) ◽  
pp. 2705-2713 ◽  
Author(s):  
Laerte de Araujo Lima ◽  
Celso Rosendo Bezerra Filho

2019 ◽  
Vol 21 (2) ◽  
pp. 745-754
Author(s):  
Otávio Augusto de Oliveira Lima Barra ◽  
Fábio Perdigão Vasconcelos ◽  
Danilo Vieira dos Santos ◽  
Adely Pereira Silveira

O Brasil é um país com uma extensa linha de costa, são cerca de 7.367 km de extensão do seu litoral, com um potencial natural para a geração de energia eólica. O estado do Ceará é um dos maiores produtores de energia eólica para o país, obtendo notoriedade e a necessidade de manutenção dos seus parques eólicos, especialmente se instalados em zonas de costa, onde há uma grande dinâmica natural. O presente trabalho, busca o acompanhamento das dinâmicas morfológicas na praia de Volta do Rio, localizada em Acaraú/CE, que fica a cerca de 238 km de Fortaleza/CE. Os dados coletados em idas à campo, constataram que há um forte processo erosivo atuante na praia de Volta do Rio, o que alerta para a contenção do avanço marinho sob o parque eólico presente no local. A erosão é um fenômeno natural que trabalha na modelação de demasiadas formas terrestres. No litoral, isso não é diferente, por ser um ambiente altamente dinâmico onde há a interação entre continente, atmosfera e oceano, sendo possível encontrar diversos atuantes que podem intensificar os processos erosivos, sejam eles o vento, maré, ou por intervenções humanas, como construções e ocupações indevidas ao longo da linha de costa.Palavras Chave: Volta do Rio; Energia Eólica; Erosão. ABSTRACTBrazil is a country with an extensive coastline, about 7,367 km of coastline, with a natural potential for wind power generation. The state of Ceará is one of the largest producers of wind energy for the country, obtaining notoriety and required maintenance of its wind farms, especially if located in coastal areas, where there is a great natural dynamic. The present work seeks the movement of morphological dynamics in the beach of Volta do Rio, located in Acaraú/CE, which is about 238 km from Fortaleza/CE. The data collected in the field found that there is a strong erosive process on the Beach of Volta do Rio, which warns about the expansion of advanced marine on the wind farm present on site. Erosion is a natural phenomenon that works in the modeling of many hearth forms. On the coast, this is not different, considering a highly dynamic environment in which there is an interaction between continent, atmosphere and ocean, being possible to find many factors that can intensify the erosive processes, such as wind, tide, or human intervention, as constructions and improper occupations along the coast line.Key words: Volta do Rio; Wind Energy; Erosion. RESUMENBrasil es un país con una extensa costa, cerca de 7.367 km de costa, con un potencial natural para la generación de energía eólica. El estado del Ceará es uno de los mayores productores de energía eólica del país, ganando notoriedad y la necesidad de mantener sus parques eólicos, especialmente si está instalado en zonas costeras, donde existe una gran dinámica natural. La presente investigación tiene como objetivo monitorear la dinámica morfológica en la playa de Vuelta del Rio, ubicada en Acaraú / CE, que está a unos 238 km de Fortaleza / CE. Los datos recopilados en los viajes de campo, encontraron que hay un fuerte proceso erosivo en la playa de Vuelta del Rio, que advierte sobre la contención del avance marino bajo el parque eólico presente en el sitio. La erosión es un fenómeno natural que funciona en el modelado de muchas formas terrestres. En la costa, esto no es diferente, ya que es un entorno altamente dinámico donde existe la interacción entre el continente, la atmósfera y el océano, permitiendo encontrar varios actores que pueden intensificar los procesos erosivos, ya sea viento, marea o intervenciones humanas, como edificios y ocupaciones inadecuadas a lo largo de la costa.Palabras clave: Vuelta del Río; Energía Eólica; Erosión.


Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 338
Author(s):  
Lorenzo Donadio ◽  
Jiannong Fang ◽  
Fernando Porté-Agel

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real-time forecasts of wind farm power outputs can help to mitigate the problem. Among the various techniques developed for wind power forecasting, the hybridization of numerical weather prediction (NWP) and machine learning (ML) techniques such as artificial neural networks (ANNs) are attracting many researchers world-wide nowadays, because it has the potential to yield more accurate forecasts. In this paper, two hybrid NWP and ANN models for wind power forecasting over a highly complex terrain are proposed. The developed models have a fine temporal resolution and a sufficiently large prediction horizon (>6 h ahead). Model 1 directly forecasts the energy production of each wind turbine. Model 2 forecasts first the wind speed, then converts it to the power using a fitted power curve. Effects of various modeling options (selection of inputs, network structures, etc.) on the model performance are investigated. Performances of different models are evaluated based on four normalized error measures. Statistical results of model predictions are presented with discussions. Python was utilized for task automation and machine learning. The end result is a fully working library for wind power predictions and a set of tools for running the models in forecast mode. It is shown that the proposed models are able to yield accurate wind farm power forecasts at a site with high terrain and flow complexities. Especially, for Model 2, the normalized Mean Absolute Error and Root Mean Squared Error are obtained as 8.76% and 13.03%, respectively, lower than the errors reported by other models in the same category.


Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 693
Author(s):  
Anna Dóra Sæþórsdóttir ◽  
Margrét Wendt ◽  
Edita Tverijonaite

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


2012 ◽  
Vol 6 (6) ◽  
pp. 446-454 ◽  
Author(s):  
J.J. Melero ◽  
J. Beltrán ◽  
C. Pueyo ◽  
J.J. Guerrero

2021 ◽  
Vol 301 ◽  
pp. 117378
Author(s):  
Paola Crippa ◽  
Mariana Alifa ◽  
Diogo Bolster ◽  
Marc G. Genton ◽  
Stefano Castruccio

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