Electric energy prediction distribution system based on LoRaWAN network cloud monitoring

Abstract

The invention provides an electric energy prediction distribution system based on LoRaWAN network cloud monitoring, which comprises an electric energy acquisition network, a LoRaWAN gateway, a cloud monitoring platform and a mobile terminal APP, and is characterized in that the electric energy acquisition network is used for acquiring electric parameters of electric equipment in real time, including voltage, current, active power and electric energy; the LoRaWAN gateway serves as a wireless communication base station and is used for receiving data of eight channels at the same time, packing the data into an Ethernet data protocol packet and immediately forwarding the Ethernet data protocol packet to the cloud monitoring platform. The cloud monitoring platform is used for acquiring electricity consumption data of residents, constructing an electricity consumption prediction model based on a K-Means + + clustering algorithm and a conditional generative adversarial neural network, and connecting the mobile terminal APP through an MQTT port; and the mobile terminal APP is used for checking the electric parameters of the electric energy meter in real time and obtaining the push of the optimal power utilization scheme from the cloud. According to the technical scheme of the invention, a stable data source can be obtained, and load prediction and orderly power utilization planning can be accurately carried out.

Description

technical field [0001] The invention relates to the technical field of data wireless transmission, in particular, to a power prediction and distribution system based on LoRaWAN network cloud monitoring. Background technique [0002] As the grid becomes smarter, a fully automated power transmission network becomes even more important. Different from the traditional power grid, the smart grid does not require manual meter reading and charging, but directly obtains power data through the collection network, thus greatly saving manpower and material resources on the premise of ensuring the data is complete and comprehensive. Traditional smart grids only store historical power data, and cannot predict future power consumption. Moreover, with the increase in the type and quantity of residential electrical equipment, the future power system will support a larger demand for electricity, so Prediction of electricity consumption becomes even more critical. Predicting the demand tren...

AI Technical Summary

Problems solved by technology

Among them, NB-IOT relies on the infrastructure of operators, and signal coverage cannot be achieved in remote areas, and NB-IOT data needs to be transmitted to operators first, so it is difficult to guarantee absolute security

RS-485 is limited by long-distance transmission, and data transmission requires on-site wiring, which makes the project complex

The power carrier is limited by the carrier signal can only be transmitted in one station area, and the anti-interference ability is weak

Micro-power wireless is limited by geographical environment, short transmission distance and high power consumption

GPRS / 4G / WIFI is limited by high operating costs

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