Research on Real Power Grid Security and Stability Based on Big Data Analysis Method and Online Data of Power Grid

Hou, Jie; Lv, Yiliang; Yu, Zhihong; Xie, Changjun; Shi, Dongcheng; Guangming, Lu

doi:10.1109/powercon.2018.8602084

Cited by 5 publications

(1 citation statement)

References 2 publications

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“…It can be ensured the safe, efficient, and reliable operation of the multistation integration by determining the importance of various risk indicators in different business scenarios. And it also can clarify the focus of decision-making on risk aversion through analysis by risk sources and risk indicators for the multistation integrated operation [6].…”

Section: Introductionmentioning

confidence: 99%

Operation Risk Structural Analysis and Evaluation System Construction for Multistation Integration Project

Cui

Liu

2022

Mathematical Problems in Engineering

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Digitalization in the power grid sector will become a strong support in the future for the upgrading of the power industry. And, multistation integration has become a leading project in the process. However, there are some hidden risks to its security with the boom of new technologies. Risk analysis and evolution of the multistation integration have an important role in safe operation. This paper analyzes the relationship among risk factors by using both the structural equation modeling (SEM) and the chi-squared automatic interaction detector (CHAID) approach, which is more objective than subjective judgment. The result shows the following: (1) The operational risks come from 10 risk-derived sources which therefore can be qualitatively divided into 2 risk categories with 11 risk indicators. (2) Concerning the structural analysis, the main risk source of multistation integration comes from endogenous risks. (3) In terms of procedural analysis, cultural risk, information risk, and accidental risk are the most critical external risks, while performance risk and location risk are the most critical internal ones. The results of models provide a reference for engineering management in digitalization in the power grid sector.

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Section: Introductionmentioning

confidence: 99%