Smart Charging System for Flexible Power Flow Management
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Solution Overview
Problem
Current power flow management systems for electric vehicles lack flexibility and control, failing to address unpredictable operational demands and provide satisfactory convenience to vehicle owners, as they rely on simple timer-based charging that does not account for varying usage patterns.
Innovation Solution
A smart charging system that includes a method for managing electric resources by determining a guaranteed charging schedule and transmitting it to electric resources, allowing for flexible power flow management through a centralized power aggregation system, which communicates with electric vehicles and the grid to optimize charging based on user preferences and grid conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple timer-based charging systems are used, then device complexity is reduced, but adaptability to varying usage patterns and operational demands deteriorates
Solution Approach 1:
The charging system transitions from static timer-based scheduling to dynamic adaptive charging that responds to real-time grid conditions, user preferences, and vehicle operational needs. The system continuously adjusts charging parameters based on changing conditions, enabling it to adapt to varying usage patterns while managing complexity through automated decision-making algorithms.
Solution Approach 2:
The system implements feedback mechanisms that monitor grid conditions, user preferences, and charging progress to continuously optimize charging schedules. This feedback loop enables the system to adapt to varying usage patterns by learning from historical data and responding to real-time conditions, resolving the contradiction between simplicity and adaptability.
2Loss of time
If fixed off-peak charging schedules are implemented, then loss of time is reduced through efficient scheduling, but ease of operation deteriorates due to lack of flexibility
Solution Approach 1:
The system performs preliminary actions by pre-scheduling charging during off-peak hours based on predicted user needs and historical patterns. It proactively prepares charging schedules that optimize time efficiency while incorporating user preferences, thereby reducing charging time loss without compromising ease of operation through rigid fixed schedules.
Solution Approach 2:
The system dynamically changes charging parameters such as start time, duration, and power level based on user preferences and grid conditions. This allows the system to maintain time efficiency through off-peak scheduling while providing operational flexibility by adjusting parameters according to real-time user needs, resolving the contradiction between time optimization and ease of operation.
3Device complexity
If purely schedule-based charging systems are used, then device complexity is minimized, but reliability in addressing unpredictable operational demands deteriorates
Solution Approach 1:
The charging system performs self-service by automatically adjusting its operation based on real-time conditions without requiring complex user intervention. It monitors grid conditions, user preferences, and vehicle needs independently, making autonomous decisions to maintain reliability for unpredictable demands while keeping the system structure relatively simple through automated self-management.
Solution Approach 2:
The system uses feedback mechanisms to monitor operational demands and grid conditions, automatically adjusting charging schedules to respond to unpredictable requirements. This feedback-driven approach enhances reliability by enabling the system to adapt to changing conditions while maintaining a relatively simple structure through automated response protocols.
4Adaptability or versatility
If smart charging systems with flexible scheduling are implemented, then adaptability to user preferences is improved, but device complexity increases
Solution Approach 1:
The smart charging system achieves multi-functionality by integrating multiple capabilities including adaptive scheduling, grid condition monitoring, user preference management, and automated decision-making into a single unified platform. This universal approach enables flexible charging patterns while managing complexity through integrated architecture that performs multiple functions through coordinated subsystems.
Data Source
AI summary
A system and methods that enables smart charging for electric resources. A smart charging method may include smart charging customer guarantees. The charging behavior guarantee may comprise a guaranteed charging schedule that matches a regular charging schedule of an electric resource and provides power flow flexibility. In addition, a smart charging method may manage electric resources via a smart charging benefit analysis. A smart charging benefit may include an impact resulting from the energy management system which is beneficial to an electric resource. A smart charging method may manage the charging behavior of the electric resources on a grid based on the smart charging benefit. Further, a smart charging method may manage electric resources via a smart charging benefit analysis and smart charging customer guarantees.