EV Charger Load Scheduling for Outage-Resilient Site Charging
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Solution Overview
Problem
The installation and management of EV chargers in large-scale settings like apartment buildings and shopping centers face challenges due to power constraints, complex billing, and infrastructure updates, leading to potential power outages when multiple EVs charge simultaneously.
Innovation Solution
A management server collects datasets on EV user charging properties, EV charging site electrical properties, and regional electricity prices to generate an optimal EV charging plan, scheduling EV charger operations efficiently and updating plans in real-time to prevent power outages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple EV chargers are installed and operated simultaneously at a charging site, then the charging capacity and service coverage are improved, but the risk of power outages increases due to exceeding electrical infrastructure limits
Solution Approach 1:
The management server performs predictive load management by analyzing historical charging data, user behavior patterns, and electricity price information in advance to generate optimized charging schedules. This preliminary planning prevents power overload before it occurs by distributing charging loads across different time periods, ensuring that the total power demand never exceeds the electrical infrastructure's capacity limits while still meeting user charging needs.
2Speed
If EV chargers operate at high power levels to reduce charging time, then the charging speed is improved, but the electrical load on the infrastructure increases, risking power outages
Solution Approach 1:
The system dynamically adjusts charging power levels in real-time based on the number of active chargers, current electrical load conditions, and predicted future demand. The management server continuously monitors the charging state and infrastructure capacity, automatically modulating power distribution to maintain optimal charging speeds while preventing total load from exceeding safety thresholds, thus avoiding power outages.
3Device complexity
If EV chargers are managed without predictive scheduling, then the system complexity is reduced, but electricity costs increase due to unoptimized charging timing
Solution Approach 1:
The management server implements a feedback mechanism that continuously collects data on charging patterns, electricity prices, and infrastructure load conditions. This information feeds into machine learning models that predict future charging demands and optimize scheduling decisions. The system automatically adjusts charging schedules based on real-time and historical data, achieving cost-effective energy utilization through load shifting to off-peak hours while maintaining relatively simple operational interfaces for users.
Data Source
AI summary
Apparatus, systems, and methods for charging electric vehicles (EVs) at an EV charging site having a plurality of EV chargers, controlling by a management server the charging performed by a plurality of EV chargers at a charging site when connectivity quality between the management server and any of the EV chargers may be unstable, and electrical load reserve for use by an EV charging system of a site.