Intelligent diagnosis system and method for abnormal information in electric information acquiring system

Abstract

The invention discloses an intelligent diagnosis system and method for abnormal information in an electric information acquiring system. The system comprises an anomaly analysis expert database, a self-learning module and a GIS fault location module which cooperate with one another to enhance a capability of monitoring the operation of the electric information acquiring system. The system and method use the data acquired by the electric information acquiring system as a basis, count, analyze and diagnose t various kinds of electric data acquired by the abnormally analysis expert database and the self-learning module, determines an abnormity type and a serious degree, lock the specific location of a fault by the GIS fault location module quickly and accurately, and improve fault monitoring accuracy and fault processing efficiency to a great extent.

Description

technical field [0001] The invention relates to the technical field of abnormal information diagnosis, in particular to an intelligent diagnosis method for abnormal information in an electricity consumption information collection system. Background technique [0002] The construction of the electricity consumption information collection system is helpful to the implementation of the national energy conservation and emission reduction policy, and conforms to the development direction of the national electric power system reform. The National Development and Reform Commission’s “Ruoga Opinions on Further Deepening the Reform of the Electric Power System” pointed out that “actively carry out power demand side management and energy efficiency management, and promote supply and demand balance and energy conservation and emission reduction through the use of modern information technology, cultivation of electric energy services, and implementation of demand response. "In the "Dist...

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Problems solved by technology

First, the efficiency of system operation and maintenance needs to be improved, and on-site debugging, system monitoring, and fault elimination require a lot of manpower and material resources; second, the system data is scattered, the integration degree and accuracy rate are low, the abnormal directionality is poor, and the rich collection data is not enough. The third is that the system has a low level of intelligence, and the support for business applications of power companies is not comprehensive enough, and the monitoring and abnormal alarm capabilities of various collection equipment need to be strengthened

The above problems restrict the further development and application of the electricity consumption information collection system, and urgently need to be solved

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