Non-invasive energy consumption monitoring system and method based on deep learning

Abstract

The embodiment of the invention provides a non-intrusive energy consumption monitoring system and method based on deep learning. The system comprises a non-intrusive sensor, edge computing equipment and a cloud management platform. The non-invasive sensor is used for collecting electrical parameters of a load electric appliance in real time, wherein the electrical parameters comprise voltage dataand current data, and the electrical parameters are transmitted to the edge computing equipment. The edge computing equipment is used for obtaining an energy consumption analysis result of the load electric appliance through a preset analysis model according to the overall analysis of the electrical parameters, and sending the energy consumption analysis result to the cloud management platform; and the cloud management platform is used for integrating data uploaded by the edge computing equipment, realizing energy consumption statistics and energy audit and supporting management and upgradingof the edge computing equipment. The scheme can be used for effectively monitoring energy consumption, is convenient to deploy and can be used for carrying out deep analysis.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of power grids, and in particular to a non-intrusive energy consumption monitoring system and method based on deep learning. Background technique [0002] At present, the energy consumption monitoring system can be used for real-time monitoring of the power usage of enterprises, factories, schools, public buildings, etc., and through energy consumption statistics, energy audit, energy efficiency publicity and other means to promote their units or individuals to improve energy-saving operation management level. There are usually two methods for monitoring power consumption: intrusive and non-intrusive. The intrusive method reads energy consumption data directly by installing devices such as smart meters in the power network. For the non-intrusive method, the existing technical solutions include: 1. Meter reading equipment: by installing additional equipment on the non-intelligent device...

AI Technical Summary

Problems solved by technology

[0003] However, the existing technical solutions have their own shortcomings, 1. Intrusive: the method is suitable for new projects, but in the completed construction projects, there are problems such as difficult transformation, high cost, and affecting normal operation, so it is difficult to apply

2. Meter reading equipment: reading traditional equipment information through cameras and other equipment, on the one hand, only coarse-grained overall energy consumption can be obtained, and in-depth analysis is impossible; on the other hand, continuous monitoring and alarming are difficult

3. Pattern matching method: On the one hand, traditional sensors require wired connections, and the deployment is complicated; on the other hand, this method needs to collect a large amount of electrical characteristic data of equipment in advance as a support, the recognition accuracy is limited, and the implementation cost is high

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