Highlights
• Application of Mesoscale atmospheric modelling in China.
• Development of Aeolian maps with varying resolution covering promising windy areas.
• Investigation of offshore development prospects.
• Hourly wind velocity timeseries database available for simulations of Chinese power system.
Abstract
A mesoscale atmospheric modelling is applied in China aiming at the development and representation of Aeolian maps. The understanding of wind resource characteristics in the country with the highest wind installed capacity and the largest prospects for further wind energy development is an essential step for the further analysis of important issues related with large scale wind integration. In this connection, the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) developed at the US Naval Research Laboratory was used. Systematic application of COAMPS, with appropriate adjustment of numerical parameters for one year was carried out for China providing simultaneous information of wind statistics over every potential area for wind farm development. Analysis and processing of this information lead to the creation of mesoscale Aeolian maps over the country. Additionally, analytical wind data time-series have been reproduced providing simultaneous information of wind speed for one year. These data are essential inputs for computational tools to analyse large scale wind integration issues, simulate the whole power system of China or one of the subsystems, estimate wind energy curtailment and wind capacity credit, analyse storage solutions like hydro pumped storage and smart grids.
%0 Journal Article
%1 Caralis2015Development
%A Caralis, George
%A Gao, Zhiqiu
%A Yang, Peijin
%A Huang, Meng
%A Zervos, Arthouros
%A Rados, Kostas
%D 2015
%J Renewable Energy
%K wind energy renewables China
%P 60--69
%R 10.1016/j.renene.2014.07.055
%T Development of Aeolian map of China using mesoscale atmospheric modelling
%U http://dx.doi.org/10.1016/j.renene.2014.07.055
%V 74
%X Highlights
• Application of Mesoscale atmospheric modelling in China.
• Development of Aeolian maps with varying resolution covering promising windy areas.
• Investigation of offshore development prospects.
• Hourly wind velocity timeseries database available for simulations of Chinese power system.
Abstract
A mesoscale atmospheric modelling is applied in China aiming at the development and representation of Aeolian maps. The understanding of wind resource characteristics in the country with the highest wind installed capacity and the largest prospects for further wind energy development is an essential step for the further analysis of important issues related with large scale wind integration. In this connection, the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) developed at the US Naval Research Laboratory was used. Systematic application of COAMPS, with appropriate adjustment of numerical parameters for one year was carried out for China providing simultaneous information of wind statistics over every potential area for wind farm development. Analysis and processing of this information lead to the creation of mesoscale Aeolian maps over the country. Additionally, analytical wind data time-series have been reproduced providing simultaneous information of wind speed for one year. These data are essential inputs for computational tools to analyse large scale wind integration issues, simulate the whole power system of China or one of the subsystems, estimate wind energy curtailment and wind capacity credit, analyse storage solutions like hydro pumped storage and smart grids.
@article{Caralis2015Development,
abstract = {Highlights
• Application of Mesoscale atmospheric modelling in China.
• Development of Aeolian maps with varying resolution covering promising windy areas.
• Investigation of offshore development prospects.
• Hourly wind velocity timeseries database available for simulations of Chinese power system.
Abstract
A mesoscale atmospheric modelling is applied in China aiming at the development and representation of Aeolian maps. The understanding of wind resource characteristics in the country with the highest wind installed capacity and the largest prospects for further wind energy development is an essential step for the further analysis of important issues related with large scale wind integration. In this connection, the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) developed at the US Naval Research Laboratory was used. Systematic application of COAMPS, with appropriate adjustment of numerical parameters for one year was carried out for China providing simultaneous information of wind statistics over every potential area for wind farm development. Analysis and processing of this information lead to the creation of mesoscale Aeolian maps over the country. Additionally, analytical wind data time-series have been reproduced providing simultaneous information of wind speed for one year. These data are essential inputs for computational tools to analyse large scale wind integration issues, simulate the whole power system of China or one of the subsystems, estimate wind energy curtailment and wind capacity credit, analyse storage solutions like hydro pumped storage and smart grids.},
added-at = {2018-06-18T21:23:34.000+0200},
author = {Caralis, George and Gao, Zhiqiu and Yang, Peijin and Huang, Meng and Zervos, Arthouros and Rados, Kostas},
biburl = {https://www.bibsonomy.org/bibtex/21c31ff20b0106b4d4d00478fd28bd09a/pbett},
citeulike-article-id = {13379098},
citeulike-attachment-1 = {caralis_15_development_1008545.pdf; /pdf/user/pbett/article/13379098/1008545/caralis_15_development_1008545.pdf; 0706e6715714d23f666b02766c4e9de6ff52253d},
citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.renene.2014.07.055},
doi = {10.1016/j.renene.2014.07.055},
file = {caralis_15_development_1008545.pdf},
interhash = {562555a8dfa6382d0abd39df6a5bda32},
intrahash = {1c31ff20b0106b4d4d00478fd28bd09a},
issn = {09601481},
journal = {Renewable Energy},
keywords = {wind energy renewables China},
month = feb,
pages = {60--69},
posted-at = {2014-10-01 07:21:15},
priority = {2},
timestamp = {2018-08-22T09:32:01.000+0200},
title = {Development of Aeolian map of China using mesoscale atmospheric modelling},
url = {http://dx.doi.org/10.1016/j.renene.2014.07.055},
volume = 74,
year = 2015
}