EV Charging Schedule Control Using Fee Maps and Power Feedback
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Solution Overview
Problem
The challenge lies in efficiently managing the charging and discharging of electric vehicles, particularly in vehicle-to-grid (V2G) systems, where existing technologies struggle to optimize charging schedules based on regional fee rates and system parameters, leading to inefficiencies and safety concerns.
Innovation Solution
A method is introduced that generates map information for charging stations, identifies optimal stations, determines charging/discharging schedules based on fee rates, and corrects system parameters using real-time power signal measurements, integrating with a navigation system and server communication to dynamically update fee policies and schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If charging/discharging operations are performed without optimizing for regional fee rates and system parameters, then operational simplicity is maintained, but charging costs increase and system protection is compromised
Solution Approach 1:
The system performs preliminary actions by pre-obtaining fee rate information and system parameters before charging/discharging operations. The charging schedule is optimized in advance based on these parameters, allowing the system to make informed decisions about when to charge or discharge to minimize costs while ensuring system protection requirements are met.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual power signals during charging/discharging operations and comparing them with expected values. Based on this feedback, the system corrects system parameters and adjusts the charging schedule to maintain optimal operation while ensuring system protection.
2Measurement precision
If real-time power signal measurements and parameter corrections are implemented, then measurement precision and system protection improve, but system complexity and computational requirements increase
Solution Approach 1:
The system performs self-service by automatically measuring actual power signals, comparing them with expected values, and correcting system parameters without external intervention. The charging/discharging control system independently adjusts parameters based on measured deviations, reducing the need for manual calibration and external control systems.
3Productivity
If charging stations are selected based on comprehensive fee rate policies and multiple parameters, then charging costs are optimized, but the time and computational resources required for station identification and selection increase
Solution Approach 1:
The system performs preliminary actions by pre-obtaining fee rate information and system parameters before charging/discharging operations. The charging schedule is optimized in advance based on these parameters, allowing the system to make informed decisions about when to charge or discharge to minimize costs while ensuring system protection requirements are met.
Data Source
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AI summary
A method for charging/discharging an electric vehicle (250) includes generating map information including a charging/discharging fee rate policy for mapped charging stations and registering the generated map information in the electric vehicle (250), identifying one or more charging stations (240) capable of performing a charging/discharging of the electric vehicle (250) based on the generated map information, selecting an optimal charging station (240) for the charging/discharging among the identified charging stations (240), determining a charging/discharging schedule based on a charging/discharging fee rate policy of the selected charging station (240), and performing the charging/discharging based on the determined charging/discharging schedule at the selected charging station (240).