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School of Economics and Management, North China Electric Power University, Beijing 102206, China



These authors contributed equally to this work.





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Academic Editor: Giuseppe Ioppolo

Abstract The Qinghai–Tibet power grid interconnection project is the first power transmission project with the highest altitude, longest transmission lines, longest distance running across the plateau frozen ground, and highest iron tower in the world. The risk evaluation on it can identify the overall risk level and key risk factors, which can reduce risk-induced loss and promote sustainable construction. In this paper, the risk of the Qinghai–Tibet power grid interconnection project was evaluated by employing a matter-element extension model under a fuzzy environment. After building the risk evaluation index system, the performances and weights of criteria were qualitatively judged by three groups of experts in different fields, and then the risk of the Qinghai–Tibet power grid interconnection project was rated by employing matter-element extension model. Meanwhile, the sensitivity analysis was performed to identify key risk criteria. The empirical results indicate the risk of the Qinghai–Tibet power grid interconnection project belongs to the -stronger- grade, tending to the -strongest- grade. -Social stability risk- -altitude sickness seizure risk- -permafrost-induced risk- -severe weather-induced risk-, and -ecological destruction risk- are key sub-criteria, which should be paid more attention to when taking risk management measures. Finally, some countermeasures for key risks of the Qinghai–Tibet power grid interconnection project were given. The findings in this paper can provide references for engineering managers and related stakeholders. View Full-Text

Keywords: risk evaluation; Qinghai–Tibet power grid interconnection project; matter-element extension model; fuzzy theory; sensitivity analysis; sustainability risk evaluation; Qinghai–Tibet power grid interconnection project; matter-element extension model; fuzzy theory; sensitivity analysis; sustainability





Autor: Cunbin Li †, Yunqi Liu † and Shuke Li †,*

Fuente: http://mdpi.com/



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