Method for evaluating risk influence degree of substation equipment in power grid safety early warning

Abstract

The invention discloses a method for evaluating the risk influence degree of substation equipment in power grid safety early warning, and the method comprises the steps: carrying out the calculation according to monitoring data, equipment defect and fault information and equipment ledger information, obtaining the equipment importance degree and hidden danger of equipment, and obtaining the risk influence degree of the substation equipment through calculation; when the method is used, comparing the risk influence degree obtained through calculation by adopting the evaluation method with a setthreshold value; when the risk influence degree is smaller than the threshold value, indicating that the substation equipment is in a safe operation state, and when the risk influence degree is greater than the threshold value, indicating that the substation equipment is in a high-risk state, equipment maintenance and safety early warning need to be carried out, so that the purposes of being precautious beforehand are achieved, the failure rate of the equipment can be reduced, and the active sensing capability of monitoring personnel on the real-time operation state of the power grid is improved.

Description

technical field [0001] The invention discloses the technical field of electric network security early warning, and in particular relates to a method for evaluating risk influence degree of substation equipment in electric network security early warning. Background technique [0002] Grid monitoring data has the characteristics of multi-source, high-dimensional, a priori, and heterogeneous. The existing smart grid dispatching control system (D5000) that supports grid monitoring business has completed the construction of multiple sets of monitoring business application systems such as monitoring information collection and comprehensive intelligent alarm. , which realizes the collection and sharing of global data and the effective support for a single business. However, with the continuous expansion of the scale of the power grid, the traditional power grid monitoring operation analysis method involves a limited range of relevant data, business data is stored in a multi-source,...

AI Technical Summary

Problems solved by technology

However, with the continuous expansion of the scale of the power grid, the traditional power grid monitoring operation analysis method involves a limited range of relevant data, business data is stored in multiple sources, multiple locations, and multiple time sequences, and is heterogeneous and heterogeneous, and lacks a breakthrough in the theoretical level of monitoring professional analysis. It is difficult to process massive alarm information and cannot support the development requirements of power grid collaborative control and integration. It is necessary to realize the efficient collection and intelligent mining and analysis of the whole process information of power grid monitoring and operation, so as to improve the monitoring personnel's active perception of the real-time operating status of the power grid

[0003] With the rapid development of social economy, my country's power market also presents new characteristics. Major changes have taken place in the grid pattern and power structure, and profound changes have taken place in the operating characteristics of the grid, which are concentrated in three aspects. First, the fault form has undergone fundamental changes. The vulnerability of the power grid has increased; second, the structure of the power supply has undergone profound changes, and the regulation capacity of the power grid has seriously declined; third, the characteristics of power electronics have become prominent, and the stable form of the power grid has become more complicated

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