A study of causality structure and dynamics in industrial electricity consumption based on Granger network

Can-Zhong Yao, Ji-Nan Lin, Qing-Wen Lin, Xu-Zhou Zheng and Xiao-Feng Liu

Physica A: Statistical Mechanics and its Applications, 2016, vol. 462, issue C, 297-320

Abstract: Based on industrial electricity consumption, we model industrial networks by Granger causality method and MST (minimum spanning tree), and then further stick onto an industrial coupling mechanism from energy-consumption perspective.

Keywords: Granger causality networks; Minimum spanning tree; Industrial electricity consumption; Industrial feedback mechanism; Local industry regulation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116303752
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:462:y:2016:i:c:p:297-320

DOI: 10.1016/j.physa.2016.06.100

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().