Big data, Cloud, IoT and mobile internet technologies based active maintenance panorama monitoring system of power distribution network

Abstract

The invention provides a Big data, Cloud, IoT and mobile internet technologies based active maintenance panorama monitoring system of power distribution network. The system comprises a monitoring center, personal handheld terminal and vehicle-mounted terminals of maintenance vehicles; the personal handheld terminal and the vehicle-mounted terminals of the maintenance vehicles realize data interaction with the control center via a wireless network, and upload position information and work order processing information. The monitoring center comprises a monitoring display screen, a real-time monitoring system, an early warning system, a work order distributing system, an information issuing system and databases, wherein the monitoring display screen displays image and character information; the real-time monitoring system generates real-time map information; the early warning system is used for calculation and generates early warning information; the information issuing system generates the character information; the work order distributing system generates a work order distributing scheme; and the databases store data information. The active maintenance panorama monitoring system can monitor all links in the whole maintenance process in real time, assign staff in real time, and realize early warning analysis on a power fault so that the fault can be eliminated in the very beginning.

Description

technical field [0001] The invention belongs to power grid maintenance, in particular to a distribution network proactive repair panorama monitoring system based on big cloud material movement technology. Background technique [0002] "Big cloud and material movement" is the abbreviation of emerging technologies such as "big data, cloud computing, Internet of Things, and mobile Internet". Its essence is the extension of big data collection, transmission, storage, and utilization technologies. The foundation and core are data assets Efficient mining and utilization. In recent years, big data has become an emerging productive force, and the technology of "big cloud and material movement" has developed rapidly. The power grid is the largest and most complex IoT system. Power flow is not only energy flow, business flow, but also information flow and data flow. With the continuous upgrading of strong smart grid and global energy Internet construction, the integration of electri...

AI Technical Summary

Problems solved by technology

[0004] 1. The construction of information platform and means is not perfect, and it is difficult to support the efficient coordination of emergency repair of distribution network

Distribution network emergency repair involves multiple professional systems such as marketing, production, and scheduling. However, in the past, information construction was disorderly and repetitive, and various business systems did not communicate with each other. Service information could not be shared and coordinated, forming an information "island"; Even the data of the same indicator in different business systems is inconsistent, the data quality is not high, and it is difficult to support the needs of service collaboration

[0005] 2. The support means of the service end is backward, it is difficult to short-circuit communication with customer demands, and the on-site tasks cannot be coordinated remotely

At present, the on-site work of emergency repair mainly relies on telephone communication, and the information technology is backward. First, after receiving the 95598 customer report for repair, it is necessary to confirm the address and repair content with the customer repeatedly, which affects customer satisfaction; second, the on-site information cannot be fully shared. Remote technical support The update of task information is relatively lagging, which affects the efficiency of service collaboration

[0006] 3. Lack of monitoring means, unable to realize collaborative early warning of operation monitoring

At present, the monitoring method for emergency repair work of the distribution network is still based on after-the-fact results, and it is impossible to realize pre-warning and process monitoring for the entire service process; in addition, the data analysis ability is not high enough to provide sufficient and accurate early warning

In particular, the time limit for emergency repair business is high, and there is a lack of problem warning and real-time correction means. The real-time situation of emergency repair cannot be grasped, and it is difficult to support the transformation of emergency repair business from passive to active.

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