电力系统自动化2017，Vol.41Issue(11)：33-38,6.
风速时间序列的符号化描述
Symbolizing for Wind Speed Time Series
摘要
Abstract
By using statistical analysis technique, the difficulty of lacking causality in short-term wind speed prediction can be overcome by extrapolating the known time series.However, because of the fuzziness of subjective cognition, challenges exist in the choice of extrapolation models, parameters and training samples.To reduce the influences of fuzziness of subjective cognition on the performance of classification prediction and improve the efficiency of sample classification, the concept of coarseness of wind speed time series (WSTS) is proposed.Symbols defined according to tendency features are used to describe WSTS.Based on this, a two-layer symbolizing method using unit window feature and variation trend feature is proposed to improve WSTS symbolization.Finally, a case study based one year data collected from a wind farm at Jiuquan wind power base in Gansu Province is presented to validate the effectiveness of the proposed coarseness method.关键词
风速预测/有条件的相关性/时间序列符号化/离线分类建模/在线特征匹配Key words
wind speed prediction/conditional spatial correlation/symbolizing for time series/offline modeling by classification/online feature matching引用本文复制引用
陈宁,薛禹胜,丁杰,马进,董朝阳,刘玮..风速时间序列的符号化描述[J].电力系统自动化,2017,41(11):33-38,6.基金项目
国家自然科学基金重点项目(61533010) （61533010）
NSFC-NRCT(中泰)合作研究项目(51561145011) （中泰）
国家电网公司科技项目 （）
This work is supported by the State Key Program of National Natural Science Foundation of China (No.61533010), NSFC-NRCT (Sino-Thai) Cooperation Research Project (No.51561145011) and State Grid Corporation of China. （No.61533010）
