scholarly journals Potencia aprovechable y variabilidad del viento caso típico distrito de Pimentel

2018 ◽  
Vol 27 (2) ◽  
pp. 63
Author(s):  
José C. Pérez S. ◽  
José L. Arriola P. ◽  
Max L. Espinal M.

El presente artículo inicia dando a conocer las variables meteorológicas de un parque eólico. Posteriormente se analizan las ecuaciones que determinan la ley de Betz y la distribución Weibull esto con el fin de comprender la cantidad de energía y horas aprovechadas por un aerogenerador, se continúa con el factor de carga de un parque eólico. Finalmente se muestra la influencia de la rugosidad del terreno en la variación del viento y la selección de la zona de emplazamiento. Palabras clave.- Potencial eólico, Ley de Betz, Distribución de Weibull, factor de carga, rugosidad. ABSTRACT The present work begins by describing the meteorological variables of a wind farm. Subsequently, the equations defining Betz's law and the Weibull distribution are analyzed, in order to understand the amount of power and time of operation available from a wind turbine, as well as the load factor of a wind farm. Finally, the influence of surface roughness on wind variation and the selection of a proper location are discussed. Keywords.- wind power, Betz's law, Weibull distribution, load factor, surface roughness.

2017 ◽  
Vol 17 (23) ◽  
pp. 14239-14252 ◽  
Author(s):  
Jingyue Mo ◽  
Tao Huang ◽  
Xiaodong Zhang ◽  
Yuan Zhao ◽  
Xiao Liu ◽  
...  

Abstract. As a renewable and clean energy source, wind power has become the most rapidly growing energy resource worldwide in the past decades. Wind power has been thought not to exert any negative impacts on the environment. However, since a wind farm can alter the local meteorological conditions and increase the surface roughness lengths, it may affect air pollutants passing through and over the wind farm after released from their sources and delivered to the wind farm. In the present study, we simulated the nitrogen dioxide (NO2) air concentration within and around the world's largest wind farm (Jiuquan wind farm in Gansu Province, China) using a coupled meteorology and atmospheric chemistry model WRF-Chem. The results revealed an edge effect, which featured higher NO2 levels at the immediate upwind and border region of the wind farm and lower NO2 concentration within the wind farm and the immediate downwind transition area of the wind farm. A surface roughness length scheme and a wind turbine drag force scheme were employed to parameterize the wind farm in this model investigation. Modeling results show that both parameterization schemes yield higher concentration in the immediate upstream of the wind farm and lower concentration within the wind farm compared to the case without the wind farm. We infer this edge effect and the spatial distribution of air pollutants to be the result of the internal boundary layer induced by the changes in wind speed and turbulence intensity driven by the rotation of the wind turbine rotor blades and the enhancement of surface roughness length over the wind farm. The step change in the roughness length from the smooth to rough surfaces (overshooting) in the upstream of the wind farm decelerates the atmospheric transport of air pollutants, leading to their accumulation. The rough to the smooth surface (undershooting) in the downstream of the wind farm accelerates the atmospheric transport of air pollutants, resulting in lower concentration level.


2017 ◽  
Author(s):  
Jingyue Mo ◽  
Tao Huang ◽  
Xiaodong Zhang ◽  
Yuan Zhao ◽  
Xiao Liu ◽  
...  

Abstract. As a renewable and clean energy, wind power has become the most rapidly growing energy resource worldwide in the past decades. Wind power has been thought not to exert any negative impacts on the environment. However, since a wind farm can alter the local meteorological conditions and increase the surface roughness lengths, it may affect air pollutants passing through and over the wind farm after released from their sources and delivered to the wind farm. In the present study, we simulated the nitrogen dioxide (NO2) air concentration within and around a world’s largest wind farm (Jiuquan wind farm in Gansu Province, China) using a coupled meteorology and atmospheric chemistry model WRF-Chem. The results revealed an "edge effect", which was featured by higher NO2 levels at the immediate upwind and border region of the wind farm and lower NO2 concentration within the wind farm and the immediate downwind transition area of the wind farm. A surface roughness length scheme and a wind turbine drag force scheme were employed to parameterize the wind farm in this model investigation. Modeling results show that the both parameterization schemes yield higher concentration up to 34 % in the immediate upstream of the wind farm and lower concentration within the wind farm compared to the case without the wind farm. We infer this edge effect and the spatial distribution of air pollutants to be a result of the internal boundary layer induced by the changes in wind speed and turbulence intensity driven by the rotation of the wind turbine rotor blades and the enhancement of surface roughness length over the wind farm. The step change in the roughness length from the smooth to rough surfaces (overshooting) in the upstream of the wind farm decelerates the atmospheric transport of air pollutants, leading to their accumulation. The rough to the smooth surface (undershooting) in the downstream of the wind farm accelerates the atmospheric transport of air pollutants, resulting in lower concentration level.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Zahid Hussain Hulio

The objective of this research work is to assess the wind characteristics and wind power potential of Gharo site. The wind parameters of the site have been used to calculate the wind power density, annual energy yield, and capacity factors at 10, 30, and 50 m. The wind frequency distribution including seasonal as well as percentage of seasonal frequency distribution has been investigated to determine accurately the wind power of the site. The coefficient of variation is calculated at three different heights. Also, economic assessment per kWh of energy has been carried out. The site-specific annual mean wind speeds were 6.89, 5.85, and 3.85 m/s at 50, 30, and 10 m heights with corresponding standard deviations of 2.946, 2.489, and 2.040. The mean values of the Weibull k parameter are estimated as 2.946, 2.489, and 2.040 while those of scale parameter are estimated as 7.634, 6.465, and 4.180 m/s at 50, 30, and 10 m, respectively. The respective mean wind power and energy density values are found to be 118.3, 92.20, and 46.10 W/m2 and 1036.6, 807.90, and 402.60 kWh/m2. As per cost estimation of wind turbines, the wind turbine WT-C has the lowest cost of US$ Cents 0.0346/kWh and highest capacity factors of 0.3278 (32.78%). Wind turbine WT-C is recommended for this site for the wind farm deployment due to high energy generation and minimum price of energy. The results show the appropriateness of the methodology for assessing the wind speed and economic assessment at the lowest price of energy.


2013 ◽  
Vol 14 (3) ◽  
pp. 207-218 ◽  
Author(s):  
Kazuki Ogimi ◽  
Shota Kamiyama ◽  
Michael Palmer ◽  
Atsushi Yona ◽  
Tomonobu Senju ◽  
...  

Abstract In order to solve the problems of global warming and depletion of energy resource, renewable energy systems such as wind generation are getting attention. However, wind power fluctuates due to variation of wind speed, and it is difficult to perfectly forecast wind power. This paper describes a method to use power forecast data of wind turbine generators considering wind power forecast error for optimal operation. The purpose in this paper is to smooth the output power fluctuation of a wind farm and to obtain more beneficial electrical power for selling.


2020 ◽  
Author(s):  
Shafiqur Rehman ◽  
Salman A. Khan ◽  
Luai M. Alhems

Abstract The recent revolution in the use of renewable energy worldwide has opened many dimensions of research and development for sustainable energy. In this context, the use of wind energy has received notable attention. One critical decision in the development of a wind farm is the selection of the most appropriate turbine compatible with the characteristics of the geographical location under consideration in order to harness maximum energy. This selection process considers multiple decision criteria which are often in conflict with each other, as improving one criterion negatively affects one or more other criteria. Therefore, it is desired to find a tradeoff solution where all selection criteria are simultaneously optimized to the best possible level. This paper proposes a TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) based approach for multi-criteria selection of wind turbine. Three decision criteria, namely, hub height, wind speed, and net capacity factor are used in the decision process. A case study is shown on real data collected from the Aljouf region located at an altitude of 753 meters above sea level in the northern part of Saudi Arabia. Seventeen turbines with rated capacities ranging from 1.5 GW to 3 GW from various manufacturers are evaluated. Results indicate that Vestas V110 turned out to be the most appropriate turbine for the underlying site.


Author(s):  
E. Muljadi ◽  
C. P. Butterfield

Wind power generation has increased very rapidly in the past few years. The total U.S. wind power capacity by the end of 2001 was 4,260 megawatts. As wind power capacity increases, it becomes increasingly important to study the impact of wind farm output on the surrounding power networks. In this paper, we attempt to simulate a wind farm by including the properties of the wind turbine, the wind speed time series, the characteristics of surrounding power network, and reactive power compensation. Mechanical stress and fatigue load of the wind turbine components are beyond the scope this paper. The paper emphasizes the impact of the wind farms on the electrical side of the power network. A typical wind farm with variable speed wind turbines connected to an existing power grid is investigated. Different control strategies for feeding wind energy into the power network are investigated, and the advantages and disadvantages are presented.


2009 ◽  
Vol 11 (01) ◽  
pp. 69-95 ◽  
Author(s):  
ALASTOR M. COLEBY ◽  
DAVID R. MILLER ◽  
PETER A. ASPINALL

Research for this paper was undertaken into the relationship between public opinion on wind power and public participation in turbine site planning and design. The research focussed on the contribution of environmental attitude studies to participatory environmental impact assessment of renewable energy policy and land use. A questionnaire survey was undertaken at wind farm sites at three stages in the site planning process and at three public events where the application of wind power was a topic of discussion. The attitudinal data produced was subjected to a series of statistical tests to determine which of the attitudes revealed could be quantified significantly in terms of public opinion. The most significant responses related to the proximity of wind turbines to respondents' homes with the proposition that wind turbine designers should seek community input of the highest significance. Respondents also indicated a preference for traditional turbine structures that blended in with the landscape and remained out of sight. Respondents' personal perception of land use change regarding wind power near them was mostly significant relative to respondent age with younger respondents tending to be more accepting of wind turbine land use whilst older respondents objected. Living place was also found to be significant with urban respondents more accepting of wind power than rural ones. Fundamentally respondents although polarised for or against on certain issues, all shared a wish for more public input and participation in local land use for wind power.


2003 ◽  
Vol 27 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Niels Raben ◽  
Martin Heyman Donovan ◽  
Erik Jørgensen ◽  
Jan Thisted ◽  
Vladislav Akhmatov

An experiment with tripping and re-connecting a MW wind turbine generator was carried out at the Nøjsomheds Odde wind farm in Denmark. The experimental results are used primarily to validate the shaft system representation of a dynamic wind turbine model. The dynamic wind turbine model is applied in investigations of power system stability with relation to incorporation of large amounts of wind power into the Danish power grid. The simulations and the measurements are found to agree. The experiment was part of a large R&D program started in Denmark to investigate the impact of the increasing capacity of wind power fed into the Danish power grid.


2020 ◽  
Author(s):  
Mads M. Pedersen ◽  
Gunner C. Larsen

Abstract. Design of an optimal wind farm topology and wind farm control scheduling depends on the chosen metric. The objective of this paper is to investigate the influence of optimal wind farm control on the optimal wind farm layout in terms of power production. A successful fulfilment of this goal requires: 1) an accurate and fast flow model; 2) selection of the minimum set of design parameters that rules the problem; and 3) selection of an optimization algorithm with good scaling properties. For control of the individual wind farm turbines, the two most obvious strategies are wake steering based on active wind turbine yaw control and wind turbine derating. The present investigation is a priori limited to wind turbine derating. A high-speed linearized CFD RANS solver models the flow field and the crucial wind turbine wake interactions inside the wind farm. The actuator disk method is used to model the wind turbines, and utilizing an aerodynamic model, the design space of the optimization problem is reduced to only three variables per turbine – two geometric and one carefully selected variable specifying the individual wind turbine derating setting for each mean wind speed and direction. The full design space spanned by these (2N + Nd Ns N) parameters, where N is the number of wind farm turbines, Nd is the number of direction bins, and Ns is the number of mean wind speed bins. This design space is decomposed in two subsets, which in turn define a nested set of optimization problems to achieve the fastest possible optimization procedure. Following a simplistic sanity check of the platform functionality regarding wind farm layout and control optimization, the capabilities of the developed optimization platform is demonstrated on the Swedish offshore wind farm. For this particular wind farm, the analysis demonstrates that the expected annual energy production can be increased by 4 % by integrating the wind farm control in the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.


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