Abstract:

[Purpose] In response to the problem that the severity of voltage exceeding the limit has a significant impact on the accuracy of quantifying the risk of knife switch operation, this paper proposes a knife switch operation risk quantification evaluation algorithm based on entropy weight grey analytic hierarchy process. [Methods] Use data mining techniques to obtain the device output signals when the knife switch behavior occurs. Define the risk status of knife switch operation and calculate the severity of voltage exceeding the limit. Extract the risk characteristics of knife switch operation by combining the sample discretization function. Introducing a state transition matrix to decompose the risk characteristics and trends of knife switch operations, in order to grasp the risk trends of knife switch operations. Using entropy weight grey analytic hierarchy process to calculate the combined weights of each decomposition trend item, clarify the risk assessment level of knife switch operation, and thus achieve quantitative evaluation of knife switch operation risk. [Results] The experimental results show that under different voltage limit probability conditions, the relative error of the risk assessment of the proposed method is always controlled below 0.4. [Conclusions] The quantitative assessment of the risk of knife switch operation is accurate and can accurately determine the risk of knife switch operation.

Key words: entropy weight grey analytic hierarchy process, operational risk of knife switch, quantitative evaluation, risk indicators