method and system for evaluating the running state of an intelligent electric energy meter based on a Bayesian network and a genetic algorithm

Abstract

The invention provides a method and system for evaluating the operation state of an intelligent electric energy meter based on a Bayesian network and a genetic algorithm. The method comprises the following steps: firstly, discretizing attribute indexes with continuous values in the attribute indexes for evaluating the running state of the electric energy meter; based on historical data based then,for the discretized attribute index, obtaining a discretized attribute index; determining a set of optimal attribute indexes by adopting a genetic algorithm; based on historical data, training a plurality of Bayesian nets; adopting a genetic algorithm to select an optimal Bayesian network according to the fitness function; and finally, observing the attribute index value of the intelligent electric energy meter. the operation state of the intelligent electric energy meter is determined through a Bayesian network reasoning algorithm; According to the method and the system, the state evaluationof the intelligent electric energy meter is accurately realized, great convenience is provided for the work of safe operation, state monitoring, data reading, electricity price issuing and the like of a power grid, the huge cost of periodically recovering and detecting the electric energy meter is effectively saved, and a powerful technical guarantee is provided for replacing the intelligent electric energy meter.

Description

technical field [0001] The invention relates to the field of electric energy metering, and more specifically, relates to a method and system for evaluating the operating state of a smart electric energy meter based on a Bayesian network and a genetic algorithm. Background technique [0002] Smart energy meters are gradually entering every household to achieve complete coverage of electricity consumption information collection, and its important role in the construction of smart grids is being highlighted. The service life of smart energy meters is limited, and the verification cycle of class 1 and level 2 active energy meters is generally less than 8 years, which means that each energy meter will be taken back for testing after 8 years of use. If it can still be used, it will also go through the cumbersome process of "two dismantling and two reinstalling", and it will not exceed 2 years to be used again. Therefore, the current recycled smart energy meters are all scrapped, r...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the technical problem in the prior art that the state of the smart energy meter cannot be accurately evaluated, causing a large number of energy meters that can still be used to be scrapped, the present invention provides a method for evaluating the operating state of the smart energy meter based on Bayesian networks and genetic algorithms. method, said method comprising:

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