A Smart Energy Meter for Short-term Prediction of Consumer Power Consumption

Abstract

The invention relates to the technical field of power grid dispatching, in particular to an intelligent electric energy meter for short-term prediction of user electricity consumption, which includes an electric energy meter, a programmable controller, a storage module, a communication module and several terminal modules. The terminal module includes a connection Body, electronic switch and communication unit, the connecting body is connected in series with the electric appliance, the control end of the electronic switch is connected to the connecting body, the electronic switch conducts when there is current passing through the connecting body, the communication unit is connected to the connecting body through the electronic switch, and the communication unit After the power is turned on, the preset message is sent to the communication module; the programmable controller judges the electrical appliances currently turned on by the user according to the information received by the communication module. The substantive effect of the present invention is: through the connection of the terminal module with the user's electrical appliance, reporting the electrical equipment that the user is currently turning on, and counting the power consumption rules of the electrical equipment, the user's short-term load can be more accurately calculated. Forecasting provides a basis for the scheduling of generating units.

Description

technical field [0001] The invention relates to the technical field of power grid dispatching, in particular to an intelligent electric energy meter for short-term prediction of user electricity consumption. Background technique [0002] In the dispatching work of the power grid, the most important thing is to predict the load, so as to formulate the generator set plan in a targeted manner, reduce the standby set, and achieve the purpose of reducing the operating capacity and reducing the cost. At present, the accuracy of short-term prediction of users is still insufficient. As a result, generator sets still need to prepare sufficient reserve capacity to deal with short-term changes in electricity consumption. The spare capacity is not used, and the cost of it needs to be borne by the power plant itself. It increases the operating cost of the power plant and ultimately increases the power consumption burden of the user. Accurately realizing short-term forecasting of elect...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: the technical problem that the accuracy of the user's short-term power consumption prediction is low at present

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