scholarly journals Evaluation and Analysis of Wind Resources in Jin-Jing-Ji Region of China

2011 ◽  
Vol 11 ◽  
pp. 836-842 ◽  
Author(s):  
Yang Hua ◽  
Yan Binghong ◽  
Qi Chengying ◽  
Chen Dan
Keyword(s):  
2014 ◽  
Author(s):  
J. Roberts ◽  
A. Warren

2014 ◽  
Vol 660 ◽  
pp. 745-749
Author(s):  
Rosly Nurhayati ◽  
Mohd Sofian

ASEAN (Association of Southeast Asian Nations) countries may have a huge potential for utilizing wind energy as it requires little in the way of land. Land in these countries is very fertile and is used by other alternatives, therefore reducing its conduciveness for developing solar energy. The wind resources map is widely available for Laos, Vietnam, Thailand, Cambodia and Philippines but there is not much information about other ASEAN countries. Based on meteorological data, Tioman Island was selected as the area that had the best potential for installing wind turbines in Malaysia. A more detailed study was conducted using a CFD model for unsteady flow, known as the Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain (RIAM-COMPACT®) which is based on the Large-Eddy Simulation (LES) technique. Micro-siting technique is used as a tool for selecting appropriate point and an inappropriate point for locating wind turbine generators (WTGs) at Tioman Island, Malaysia. The suggested points for locating WTGs were shown based on the numerical results obtained from the calculation.


2015 ◽  
Vol 27 (1) ◽  
pp. 29-39
Author(s):  
Viktorija Bobinaite

Abstract The paper aims to analyse the development of the financial leverage and its determinants in companies producing electricity from wind resources in Latvia during 2005-2012. The financial ratio technique is used to compute the financial leverage in the companies and the regression analysis method is employed to determine the relationships between variables. The results of the analysis revealed that wind electricity generating companies use substantial share of debt and the financial leverage is increasing. Statistically significant relationships were found between the financial leverage and profitability of companies, their growth opportunities, collateral value of assets, size of the company and an effective tax rate. Results will be used to construct weighted average cost of capital (WACC) for the economic assessment of investment into wind electricity sector in Latvia.


2018 ◽  
pp. 246-253
Author(s):  
N. G. Mortensen ◽  
E. L. Petersen ◽  
L. Landberg
Keyword(s):  

Author(s):  
Toshiaki Kanemoto

For the next leap in power-generating technologies, the world is obligated to not only cope with the warming global environment but also to conserve the natural ecosystem. This chapter discusses the advances in technology designed to successfully exploit offshore marine and wind resources. (1) The Counter-Rotating Type Hydro/Tide Power Unit, which is composed of the tandem runners and the peculiar generator with double rotational armatures, is applicable to both rising and falling tides at the power station with the embankment, in place of the traditional bulb type turbines. (2) The Floating Type Ocean Wave Power Station, where a pair of floats lines up at the wavelength spacing, can get the superabundant velocity energy. (3) The Intelligent Wind/Tide Power Unit, which is composed of the tandem wind/tide rotors and the double rotational armatures, is suitable for offshore wind and the tidal stream.


Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 863
Author(s):  
Mingcan Li ◽  
Hanbin Xiao ◽  
Lin Pan ◽  
Chengjun Xu

This paper reports a novel frandsen generalized wake model and its variation model-frandsen generalized normal distribution wake model for off-shore wind farms. Two different new wake models in off-shore wind farms have been studied comparatively. Their characteristics have been analyzed through mathematical modeling and derivation. Meanwhile, simulation experiments show that the proposed two new wake models have different properties. Furthermore, the distributions of wind speed and wind direction are modeled by the statistical methods and Extreme Learning Machine through the off-shore wind farms of Yangshan Deepwater Harbor in the Port of Shanghai, China. In addition, the data of wind energy are provided to verify and test the correctness and effectiveness of the proposed two models. Wind power has been demonstrated by wind rose and wind resources with real-time data. These techniques contribute to enhance planning, utilization and exploitation for wind power of off-shore wind farms.


Sign in / Sign up

Export Citation Format

Share Document