EV Charging Schedule Control for Grid Code and V2G Tariffs
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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 power grid codes and fee rate policies, leading to inefficiencies and increased costs.
Innovation Solution
A method that involves receiving power grid codes and corresponding fee rate policies, determining a charging/discharging schedule, and performing charging/discharging operations with a charging station, while also considering the current location, system parameters, and travel patterns of the electric vehicle, dynamically updating the fee rate policy based on power consumption statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If charging/discharging operations are performed without optimizing schedules based on regional power grid codes and fee rate policies, then operational simplicity is maintained, but charging costs increase and system efficiency deteriorates
Solution Approach 1:
The charging/discharging management system automatically receives power grid codes and fee rate policies, determines optimal schedules, and executes charging/discharging operations without requiring manual intervention. The system self-adjusts based on regional policies and real-time power consumption statistics, enabling autonomous optimization of charging efficiency while maintaining operational simplicity for users.
Solution Approach 2:
The charging schedule is dynamically determined based on regional power grid codes, fee rate policies, and real-time power consumption statistics. The system adapts charging/discharging timing and parameters according to changing conditions, optimizing efficiency while responding to dynamic environmental factors rather than using fixed static schedules.
2Reliability
If charging/discharging operations are performed without considering real-time power consumption statistics and regional policies, then system complexity is reduced, but charging costs increase and power system stability deteriorates
Solution Approach 1:
The system receives and processes real-time power consumption statistics from the power grid, using this feedback information to adjust charging/discharging schedules. By continuously monitoring power consumption patterns and regional policy changes, the system optimizes operations to maintain power system stability while reducing peak load fluctuations, with the complexity managed through automated feedback loops.
Solution Approach 2:
The system preliminarily determines optimal charging/discharging schedules based on anticipated fee rate policies and power consumption patterns before executing operations. By pre-planning charging strategies according to expected conditions and regional policies, the system proactively maintains power system stability and optimizes costs, rather than reactively responding to fluctuations.
3Duration of action of stationary object
If charging/discharging operations do not optimize for battery life through strategic scheduling, then operational flexibility is maintained, but battery durability and longevity deteriorate
Solution Approach 1:
The system preliminarily determines optimal charging/discharging schedules that consider battery health requirements, strategically planning charge cycles to minimize stress on the battery. By pre-calculating schedules that optimize both battery longevity and operational needs, the system extends battery life while maintaining sufficient flexibility for user requirements through automated adjustment.
Solution Approach 2:
The system changes charging parameters such as rate, timing, and duration based on battery state and operational requirements. By dynamically adjusting these parameters to match optimal charging conditions and battery health needs, the system prolongs battery life while adapting to different operational scenarios, effectively balancing durability with operational flexibility.
4Loss of energy
If charging/discharging operations are performed without automated schedule determination based on fee rate policies, then system simplicity is maintained, but charging costs increase
Solution Approach 1:
The system automatically receives fee rate policies, determines optimal charging schedules, and executes charging/discharging operations without manual intervention. This self-service automation minimizes charging costs by strategically timing operations according to fee rate variations and power consumption patterns, while keeping the user interface simple and requiring no manual schedule management from operators.
Solution Approach 2:
The charging schedule is dynamically determined based on real-time fee rate policies and power consumption statistics rather than using fixed static schedules. The system adapts charging timing and parameters to exploit low-cost periods and avoid peak pricing, automatically optimizing charging costs through dynamic adjustment to changing economic and operational conditions.
Data Source
AI summary
A method for charging/discharging an electric vehicle includes receiving one or more power grid codes and information on a charging/discharging fee rate policy corresponding to each of the one or more power grid codes, determining a charging/discharging schedule based on the received charging/discharging fee rate policy, and performing a charging/discharging for the elective vehicle with a charging station based on the determined charging/discharging schedule.