AI-based intelligent diagnosis method, system and device

Abstract

The invention relates to the field of intelligent power grids, in particular to an AI-based intelligent diagnosis method, a system and a device. The core of the method is AI + IoT. The method is composed of standardized and industrialized IoT edge computing hardware equipment and a customized AI module, and comprises the following steps: an acquisition unit of IoT equipment acquires power consumption data; the cloud platform trains an AI model according to historical data, the AI model is continuously and dynamically perfected according to new data, and an edge computing unit of the IoT equipment inputs acquired power consumption data into the trained artificial intelligence AI model to obtain related data. Real-time prediction of governance is achieved, the real-time monitoring level of abnormal standard exceeding of energy indexes is practically improved, and a previous working mode of semi-manual system detection and manual verification is changed into a full-automatic intelligent AI analysis mode. Finally, a brand-new software and hardware form of a cloud platform, edge computing equipment, an intelligent field terminal and an intelligent IoT chipset module is realized. A user-side energy system and a power distribution management system are redefined, and the age of software-defined energy is started.

Description

technical field [0001] The invention relates to the field of smart grids, in particular to an AI-based intelligent diagnosis method, system and device. Background technique [0002] At present, the construction of the ubiquitous electric power Internet of Things is progressing steadily, and tasks in six major fields, including basic support, data sharing, and internal and external business, have been carried out successively. As one of the core economic and technical indicators of power grid enterprises, line loss reflects the operating costs and economic benefits of the enterprise. Strengthening line loss management is a long-term strategic task and systematic project for power grid enterprises. The smart grid is a multi-objective function constrained by balance. Its factors are numerous, the conditions are random, the line loss is changeable, and the causes are complex. Factors change dynamically, making physical modeling difficult. Manual experience and existing methods ...

AI Technical Summary

Problems solved by technology

[0008] 1. "Energy index management is not predictable" - the current energy index management system is mainly based on monitoring and data storage, a large amount of data does not play a role, and it is impossible to predict energy indexes in real time, so that it is impossible to accurately judge the abnormal situation of energy indexes;

[0009] 2. "Difficulty in diagnosing the cause of abnormal energy indicators" - most of the energy indicator management systems currently in use are based on data calculation, with weak analysis capabilities, and cannot accurately locate the real-time abnormalities of each station, equipment, line, station area, and user It is very difficult to manage energy indicators, and the diagnosis of abnormal energy indicators depends heavily on the professional level of personnel, and there are risks of misjudgment and missed judgment;

[0010] 3. "Governance decisions rely on manual work" - the current energy index management is at a semi-automated level, heavily dependent on manual experience and manual decision-making, and lacks effective technical and data support

[0011] 4. "Insufficient utilization of data value" - most of the current analysis work of energy index management relies on the linkage of major business systems. Insufficient value mining

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