Grey relational analysis for Energy Storage Service Provider Influencing Factors

Grey relational analysis for Energy Storage Service Provider Influencing Factors

China faces the problems of abandoning wind and light and environmental pollution. Energy conservation and emission reduction as a new technology can effectively solve the above problems. In the process of building a Energy Storage Services project, the issue of Influencing Factors is the focus of a...

Full description

Bibliographic Details
Main Authors: Wang Qiang, Wang Jiaxin, Liu Haiying, Liu Xin, He Jiaoyu
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/33/e3sconf_aesee2021_01002.pdf
id doaj-a90e9c3232404c5092cde56ca1c3e9d8
record_format Article
spelling doaj-a90e9c3232404c5092cde56ca1c3e9d82021-05-28T12:41:58ZengEDP SciencesE3S Web of Conferences2267-12422021-01-012570100210.1051/e3sconf/202125701002e3sconf_aesee2021_01002Grey relational analysis for Energy Storage Service Provider Influencing FactorsWang Qiang0Wang Jiaxin1Liu Haiying2Liu Xin3He Jiaoyu4Affiliation: Department of Mechanical and Traffic Engineering, Ordos Institute of TechnologyAffiliation: School of Finance and taxation, Inner Mongolia University of Finance and EconomicsAffiliation: Department of Management, Ordos Institute of TechnologyAffiliation: School of Finance and taxation, Inner Mongolia University of Finance and EconomicsAffiliation: School of Finance and taxation, Inner Mongolia University of Finance and EconomicsChina faces the problems of abandoning wind and light and environmental pollution. Energy conservation and emission reduction as a new technology can effectively solve the above problems. In the process of building a Energy Storage Services project, the issue of Influencing Factors is the focus of attention. Aiming at the problem of Influencing Factors in Energy Storage Services systems, a Influencing Factors method based on gray correlation analysis is proposed. Adopting this method, one can avoid the influence of subjective factors on weight assignment through grey correlation analysis. Grey relational analysis can objectively analyze the proportion of each index in supplier’s production considerationhttps://www.e3s-conferences.org/articles/e3sconf/pdf/2021/33/e3sconf_aesee2021_01002.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Wang Qiang
Wang Jiaxin
Liu Haiying
Liu Xin
He Jiaoyu
spellingShingle Wang Qiang
Wang Jiaxin
Liu Haiying
Liu Xin
He Jiaoyu
Grey relational analysis for Energy Storage Service Provider Influencing Factors
E3S Web of Conferences
author_facet Wang Qiang
Wang Jiaxin
Liu Haiying
Liu Xin
He Jiaoyu
author_sort Wang Qiang
title Grey relational analysis for Energy Storage Service Provider Influencing Factors
title_short Grey relational analysis for Energy Storage Service Provider Influencing Factors
title_full Grey relational analysis for Energy Storage Service Provider Influencing Factors
title_fullStr Grey relational analysis for Energy Storage Service Provider Influencing Factors
title_full_unstemmed Grey relational analysis for Energy Storage Service Provider Influencing Factors
title_sort grey relational analysis for energy storage service provider influencing factors
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2021-01-01
description China faces the problems of abandoning wind and light and environmental pollution. Energy conservation and emission reduction as a new technology can effectively solve the above problems. In the process of building a Energy Storage Services project, the issue of Influencing Factors is the focus of attention. Aiming at the problem of Influencing Factors in Energy Storage Services systems, a Influencing Factors method based on gray correlation analysis is proposed. Adopting this method, one can avoid the influence of subjective factors on weight assignment through grey correlation analysis. Grey relational analysis can objectively analyze the proportion of each index in supplier’s production consideration
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/33/e3sconf_aesee2021_01002.pdf
work_keys_str_mv AT wangqiang greyrelationalanalysisforenergystorageserviceproviderinfluencingfactors
AT wangjiaxin greyrelationalanalysisforenergystorageserviceproviderinfluencingfactors
AT liuhaiying greyrelationalanalysisforenergystorageserviceproviderinfluencingfactors
AT liuxin greyrelationalanalysisforenergystorageserviceproviderinfluencingfactors
AT hejiaoyu greyrelationalanalysisforenergystorageserviceproviderinfluencingfactors
_version_ 1721423924982448128

Similar Items