EV Charging Station Power Demand Leveling via Connection Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Power demand leveling in electric vehicle-based virtual power plants is challenging due to the unpredictable usage patterns of electric vehicles in public spaces like stores, where vehicles are frequently used and disconnected, leading to insufficient charging and discharging power.
Innovation Solution
A power management system that uses a server to adjust electric power exchange between a power grid and charging/discharging stations by predicting the connection period of electric vehicles based on user behavior information, such as position and payment data, to ensure continuous power demand leveling without reducing the number of participating vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electric vehicles are continuously connected to charging stations for power demand leveling, then power demand can be effectively leveled, but users may take their vehicles away for personal use, reducing the number of available vehicles
Solution Approach 1:
The server predicts future vehicle connection status before the power demand leveling period begins, using user behavior information to determine which vehicles will be available. This allows the system to pre-select suitable vehicles and plan power exchange strategies in advance, ensuring reliable power demand leveling while accounting for potential vehicle removals.
Solution Approach 2:
The system continuously monitors user behavior information and vehicle connection status, using this feedback to dynamically adjust power demand leveling strategies. The server compares predicted connection status with actual status and modifies control instructions to maintain effective power demand leveling despite vehicles being taken away for user needs.
2Reliability
If the system excludes vehicles that may be used during power demand leveling, then power demand can be leveled reliably, but the number of available vehicles for power exchange decreases
Solution Approach 1:
The server performs preliminary prediction of vehicle connection status before the power demand leveling period. By using user behavior information to forecast which vehicles will remain connected, the system can pre-identify suitable participants without unnecessarily excluding vehicles, thus maintaining both reliability and maximizing the number of participating vehicles.
Solution Approach 2:
The system predicts connection status with a margin of safety, potentially excluding a few vehicles that might remain connected. This partial exclusion ensures that the selected vehicles will definitely be available during the power demand leveling period, maintaining reliability while minimizing the reduction in participating vehicle count.
Data Source
AI summary
The server executes a process that includes receiving predetermined information from each terminal in a facility, if it is determined that the electric vehicle is connected to a charging/discharging station, associating a user or a user terminal with the charging/discharging station, scheduling a power demand and supply adjustment, receiving behavior information of the user, if it is determined that it is necessary to reschedule the power demand and supply adjustment, predicting a connection period, rescheduling the power demand and supply adjustment, and if the current time has reached the start time of a power supply and supply adjustment period, executing the power demand and supply adjustment.