Distribution parameter-determining method comparison for airborne wind energy potential assessment in the eastern coastal area of China

被引:4
|
作者
Wang, Jianzhou [1 ]
Li, Qiwei [1 ]
Ma, Xuejiao [2 ]
Lu, Haiyan [3 ]
机构
[1] Dongbei Univ Finance & Econ, Sch Stat, Dalian, Peoples R China
[2] Dalian Univ Technol, Sch Econ & Management, Dalian, Peoples R China
[3] Univ Technol, Fac Engn & Informat Technol, Sch Software, Sydney, NSW, Australia
基金
中国国家自然科学基金;
关键词
Wind speed distribution; Whale optimization algorithm; Flower pollination algorithm; Genetic algorithm; Parameter estimation; INNER-MONGOLIA; DISTRIBUTION MODELS; RESOURCE ASSESSMENT; POWER; SPEED; FEASIBILITY; LOCATIONS; ISLANDS; DENSITY; ECONOMY;
D O I
10.1016/j.seta.2022.102161
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In recent years, airborne wind energy generation (AWEG) has increasingly been discussed as a better alternative to traditional wind turbine generation owing to less expensive raw materials, higher electricity capacity, and being more friendly to the surrounding environment. Thus, the planning of AWEG-based wind farms is necessary. To control the risk and ensure the future investment revenue to guarantee the ultimate success of this planning, airborne wind energy potential assessment (AWEPA) is essential; however, it has rarely been done so far. In this study, an AWEPA for the eastern coastal area of China was implemented. As wind speed distribution is an essential factor in AWEPA, to guarantee a reliable assessment, selecting a suitable distribution parameter determining method is critical. In this paper, two conventional numerical parameter-determining methods and three intelligent parameter-determining methods were compared, and the intelligent parameter-determining method embedding the whale optimization algorithm that showed outstanding performance in the comparison was finally selected to be used in the AWEPA. The assessment results show that developing AWEG in the study area is highly likely feasible, and the results also provide some other valuable information for planning.
引用
收藏
页数:14
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