An early warning method for power grid information system equipment status based on reverse fuzzy hierarchy analysis

Abstract

The invention discloses a method for early warning of the operating state of power grid system equipment based on reverse fuzzy hierarchical analysis, and belongs to the technical field of early warning of the state of hardware equipment of the power grid information system. The method includes: constructing a differentiated index system reflecting the operating status of power grid information system equipment; fitting the daily operation curve of a certain index of the equipment; obtaining the cumulative deviation, and comparing the cumulative deviation obtained by each index with the 1 of the corresponding index ‑9 scale mapping to obtain the fuzzy consistent judgment matrix; then calculate the weights of each indicator from the fuzzy consistent judgment matrix, sum the weights of the indicators belonging to a single device and average the number of indicators contained in the device, and reversely obtain the single The weight of each device; make a graded early warning for the operating status of the equipment and the information system. The method can fully deal with problems such as equipment aging or updating, business volume fluctuations, equipment additions, etc., and can reflect equipment state changes in real time to realize dynamic early warning.

Description

technical field [0001] The invention belongs to the technical field of early warning of the status of hardware equipment of a power grid information system, and in particular relates to a method for early warning of the status of equipment of a power grid information system based on reverse fuzzy hierarchical analysis. Background technique [0002] The power grid information system is an important part of supporting the production and operation of power grid enterprises. The real-time evaluation and early warning of the operation status of the hardware equipment of the power grid enterprise information system will help the power grid enterprises to operate stably and reliably, and continue to provide citizens with high-quality power services . The power grid information system covers all aspects of enterprise production and operation, including I6000 system, ERP system, PMS system, etc. Each system is composed of different types and a large number of devices through a certai...

AI Technical Summary

Problems solved by technology

[0003] Traditional early warning methods usually use data abnormal point mutation or abnormal trend as the basis for early warning, but the basis for judging data sudden change and abnormal trend is usually the detection information base and database formed by users' long-term monitoring and accumulation. These information come from the long-term operation of the system. Historical information, the update rate is slow, unable to cope with equipment aging or updating, business volume fluctuations, emergencies, etc.

At the same time, the traditional early warning method evaluates the status of a single device, and finally integrates it to describe the system status. This early warning method strips the connection between devices and cannot accurately and comprehensively reflect the status of the entire system.

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