Risk Assessment of Cascading Failures in Power System Based on Fuzzy Theory

2014 ◽  
Vol 496-500 ◽  
pp. 2733-2736
Author(s):  
Fu Chao Zhang ◽  
Jia Dong Huang
Keyword(s):  
Risk Assessment ◽  
Power System ◽  
Fuzzy Theory ◽  
Power Grid ◽  
Cascading Failures ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Level Of Risk

This paper makes a grading of the probability of cascading failures using the theory of fuzzy C-means clustering to implement the level of risk assessment. Then from the perspective of power system transient security, use the specific severity functions to grade the probability of cascading failures, and the synthetical severity is graded by fuzzy theory. Finally, synthesizing the probability of cascading failures with the severity of failure, and the level of risk assessment is determined according to the principle of the maximum membership. Finally, taking IEEE 39 system for example, to assess the level of the risk of cascading failures in power grid, thus the rationality and effectiveness of the proposed algorithm are verified.

scholarly journals Pythagorean fuzzy time series model based on Pythagorean fuzzy c-means and improved Markov weighted in the prediction of the new COVID-19 cases

2021 ◽  
Author(s):  
Sidong Xian ◽  
Yue Cheng
Keyword(s):  
Time Series ◽  
Fuzzy Theory ◽  
Prediction Method ◽  
Time Series Model ◽  
Fuzzy Time Series ◽  
University Of Alabama ◽  
Fuzzy C Means ◽  
Forecasting Method ◽  
Fuzzy C Means Clustering ◽  
Realistic Prediction

Abstract Time series is an extremely important branch of prediction and the research on it plays an important guiding role in production and life. To get more realistic prediction results, scholars have explored the combination of fuzzy theory and time series. Although some results have been achieved so far, there are still gaps in the combination of n-Pythagorean fuzzy sets and time series. In this paper, a pioneering n-Pythagorean fuzzy time series model (n-PFTS) and its forecasting method (n-IMWPFCM) is proposed to employ a n-Pythagorean fuzzy c-means clustering method (n-PFCM) to overcome the subjectivity of directly assigning membership and non-membership values, thus improving the accuracy of the partition the universe of discoure. A novel improved Markov prediction method is exploited to enhance the prediction accuracy of the model. The proposed prediction method is applied to the yearly University of Alabama enrollments data and the new COVID-19 cases data. The results show that compared with the traditional fuzzy time series forecasting method, the proposed method has better forecasting accuracy. Meanwhile, it has the characteristics of low computational complexity and high interpretability and demonstrates the superiority of this model from a realistic perspective.

Novel Indexes and Method for Power Grid Blackout Risk Assessment

2014 ◽  
Vol 556-562 ◽  
pp. 6665-6668
Author(s):  
Xiao Jun Lu ◽  
Kai Wen Zeng ◽  
Shi Wu Liao ◽  
Jin Yu Wen ◽  
En Lu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Power System ◽  
Risk Evaluation ◽  
Power Grid ◽  
Assessment Method ◽  
Actual System ◽  
Term Operation ◽  
Incident Investigation ◽  
Risk Assessment Method

A set of blackout risk assessment indexes is established according to Electricity Accident (Incident) Investigation Procedures of China Southern Power Grid (CSPG) (pilot) and Guide on Operational Risk Evaluation of CSPG, which can calculate risk values of electricity accidents (incidents). The calculation process is discussed in detail. Based on the proposed indexes and OPA blackout model, a blackout risk assessment method for power system is put forward, with which blackout risk for all 500kV buses in Guangdong Power Grid are evaluated. Weak areas in power system are identified and their inducements are analyzed. The identification results accord with actual system long-term operation experience, which verifies the correctness of the indexes and method.

Sign in / Sign up

Export Citation Format

Share Document