Electric Vehicle Charging Profiles for Grid Load Management
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Solution Overview
Problem
The increasing demand for electric vehicle charging poses challenges in managing peak charging times and limited charging infrastructure, requiring effective planning and operation of power grids to accommodate growing electric vehicle adoption.
Innovation Solution
Implementing electric vehicle profiling and grid operation systems that collect and analyze charging and usage data to create usage profiles, which help electricity providers plan power allocation, predict peak charging times, and schedule maintenance, by integrating controllers in electric vehicles and charging stations with computing devices to communicate and process data for grid operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If electric vehicle charging infrastructure is expanded to meet growing demand, then charging availability improves, but infrastructure cost and complexity increase
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing charging data in advance to create usage profiles that predict future charging needs. This allows power providers to proactively plan infrastructure expansion and resource allocation before peak demand occurs, reducing the need for excessive infrastructure complexity while ensuring charging availability.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring charging patterns, battery states, and grid conditions, then using this information to dynamically adjust charging recommendations and infrastructure utilization. This feedback loop optimizes existing infrastructure usage, improving charging availability without proportionally increasing infrastructure complexity.
2Productivity
If more charging stations are deployed to handle peak demand, then charging access improves, but operational complexity and cost increase
Solution Approach 1:
The system enables self-service by allowing electric vehicles to automatically communicate their charging needs, battery states, and preferences to the power provider system. The system then autonomously generates charging recommendations and schedules, eliminating the need for complex manual operational management while increasing charging capacity through optimized resource allocation.
3Productivity
If charging recommendations are provided based on usage profiles, then charging efficiency improves, but data processing requirements increase
Solution Approach 1:
The system performs preliminary data processing by continuously collecting and analyzing charging data to pre-generate usage profiles that capture typical charging patterns for different vehicles and locations. When charging recommendations are needed, the system simply queries these pre-analyzed profiles rather than processing raw data in real-time, improving charging efficiency while minimizing data processing complexity at the moment of recommendation.
Data Source
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AI summary
Electrical vehicle (102) profiles for power grid operation. Embodiments of the invention can provide systems and methods for collecting and storing electrical vehicle (102) usage and charging information, which may enable the generation of usage and charging profiles. Additionally, these usage and charging profiles may be usable to operate electricity grids in areas where electrical vehicles (102) are prevalent. Grid maintenance, as well as power allocation, may be controlled based at least in part on the usage and charging profiles.