Electricity metering is more and more widely used in social life, and the traditional mode of manual detection methods have a large number of shortcomings, which is difficult to meet people’s needs for electricity consumption. In order to improve the level of intelligence and automation, this paper introduces the goal and significance of combining artificial intelligence technology and electric energy flow monitoring system to realize unattended management, analyzes and compares the advantages and disadvantages of several mainstream intelligent algorithms in power operation status monitoring, finally proposes a method to build an artificial grid load prediction model based on genetic algorithm, neural network and other computational models, and applies it to the traditional mode for simulation experimental research.