Title :
Offshore wind power outputs in multiple temporal and spatial scales
Author :
Yida Ye ; Ying Qiao ; Zongxiang Lu ; Jun Zhang ; Yingyi Li ; Feng Guo ; Jing Huang
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
Quantitative modeling and evaluation on offshore wind power output variation characteristics are basic research for large-scale offshore wind power accessing into power grid. This paper aims to provide statistical modeling methods for evaluating power variation and smoothing effect based on the index set for offshore wind farm. An index set is proposed in this paper, which includes core indexes and fitting errors measurement indexes on power output variation to evaluate offshore wind power variation in multiple temporal and spatial scales. One-dimensional Gaussian distribution model in three different number of components are implemented to fit the probability distribution of offshore wind power output variation ratio ΔP*. For quantifying the smoothing effects, this paper defines an evaluation index R for the curve of absolute value of offshore wind power output variation ratio |ΔP*|, which indicates offshore wind power output variations confidence interval. The modeling methods and index set proposed in this paper contribute to realize both offshore wind power variation natural features and the interaction between offshore wind power and power grid.
Keywords :
Gaussian distribution; offshore installations; power grids; smoothing methods; wind power plants; 1D Gaussian distribution model; core index; evaluation index; fitting errors measurement index; offshore wind farm; offshore wind power output variation characteristics; offshore wind power output variation ratio; offshore wind power output variations confidence interval; offshore wind power variation natural features; power grid; probability distribution; smoothing effect; spatial scale; statistical modeling method; temporal scale; Fitting; Generators; Indexes; Mathematical model; Wind farms; Wind power generation; Wind turbines; index set; offshore wind power; statistical modeling; temporal and spatial scales;
Conference_Titel :
Power System Technology (POWERCON), 2014 International Conference on
Conference_Location :
Chengdu
DOI :
10.1109/POWERCON.2014.6993761