Charging and energy supply optimization method and device for charging management system

Abstract

The invention relates to the technical field of charging management, and discloses a charging and energy supply optimization method and device for a charging management system. The method comprises the steps that charging station electric energy supply transformation and distribution information, charging facility capability information, charging terminal output information, and electric vehicle charging demand information are acquired; the charging capacity, the power supply capacity and the actual charging capacity of a charging station charging facility system are determined, a model output result is obtained according to a pre-trained deep learning time sequence prediction algorithm model, the actual charging capacity of the charging station charging facility system and the charging demand quantity of a to-be-charged electric vehicle are combined, and a charging power distribution instruction is generated, and electric energy distribution is carried out on each charging facility. According to the charging and energy supply optimization method and device for the charging management system provided by the invention, a continuously optimized management control model is established by using deep learning, the energy supply and charging capability resources of charging facilities are optimized, and the utilization efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of charging management, in particular to a charging and energy supply optimization method and device for a charging management system. Background technique [0002] As an important infrastructure, electric vehicle charging piles are related to the car experience of vehicles. With the increase in the number of new energy vehicles and the improvement of cruising range, the demand for charging piles is gradually increasing, and people are increasingly paying attention to charging. Infrastructure construction and development. There are a large number of existing charging facilities and a large charging capacity, but once the charging facilities are built, the charging output interface and parking space are relatively fixed, and are also affected by the connected power supply capacity. Due to the mobility of charged electric vehicles, the number of charged electric vehicles connected to charging facilities, the ...

AI Technical Summary

Problems solved by technology

There are a large number of existing charging facilities and a large charging capacity, but once the charging facilities are built, the charging output interface and parking space are relatively fixed, and are also affected by the power supply capacity of the connection

Due to the mobility of charged electric vehicles, the number of charged electric vehicles connected to charging facilities, the time required for charging, and the required charging capacity are uncertain, it is often difficult to find a parking lot during peak hours, and vehicles need to line up for charging and wait For a long time, the charging facilities will be idle and the utilization rate is not high during low peak hours; sometimes, even if the charging facilities are fully charged and output, due to the factors of the power demand curve in the charging process, the charging gun and the parking space will be affected. During peak hours, there will be a phenomenon that the charging facilities are rich and forced to wait for a seat.

[0003] The existing charging facility management system does not have the ability to predict charging supply and demand. It only relies on manual adjustments combined with actual charging usage. The efficiency is low and the contradictions in the vehicle charging process are prominent. It is impossible to maximize the charging output of charging facilities and the efficiency of power supply.

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