The Recurrence Interval Difference of Power Load in Heavy/Light Industries of China

被引:4
|
作者
Zhang, Chi [1 ]
Pu, Zhengning [1 ]
Fu, Jiasha [2 ,3 ]
机构
[1] Southeast Univ, Sch Econ & Management, Nanjing 211102, Jiangsu, Peoples R China
[2] Southwestern Univ Finance & Econ, Res Inst Econ & Management, 55 Guanghuacun St, Chengdu 610074, Sichuan, Peoples R China
[3] Southwestern Univ Finance & Econ, Survey & Res Ctr China Household Finance, 55 Guanghuacun St, Chengdu 610074, Sichuan, Peoples R China
来源
ENERGIES | 2018年 / 11卷 / 01期
关键词
electricity fluctuation; recurrence interval analysis; risk estimation; STRETCHED EXPONENTIAL FUNCTION; ARTIFICIAL NEURAL-NETWORKS; ELECTRICITY DEMAND; TIME-SERIES; GENETIC ALGORITHM; RETURN INTERVALS; HYBRID MODEL; ENERGY; VOLATILITY; BEHAVIOR;
D O I
10.3390/en11010106
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The significant fluctuation of industrial electricity consumption has a high impact on power load, which makes the research on recurrence intervals between extreme events of theoretical and practical significance. The study uses a high-frequency data of heavy and light industries and employs recurrence interval analysis in different thresholds. We find that the reoccurrence interval of volatility can fit with the stretched exponential function and the probability density functions of recurrence intervals in various thresholds shows a scaling behavior. Then, the conditional probability density function and the multifractal detrended fluctuation analysis demonstrate the existence of short-range correlation, long-range correlation, and multifractal properties, respectively. We further construct a hazard function, introduce recurrence intervals into VaR calculation and establish a functional relationship between average recurrence interval and threshold. Following this result, we also shed light on policy discussion for multi-industrial electricity supply management.
引用
收藏
页数:20
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