EV Charging Load Management for Site Power Threshold Control
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Solution Overview
Problem
The increasing demand for electric vehicle charging poses a challenge in managing power distribution efficiently, as multiple EVs charging simultaneously can overload the electrical capacity of a site, leading to potential power outages and the need for costly infrastructure upgrades.
Innovation Solution
A dynamic load management system that uses a load manager to monitor and control the power consumption of EV charging stations in real-time, predicting peak demand and adjusting power delivery to prevent overload by curtailment through wireless communication with EVSEs, employing machine learning algorithms and bi-directional power support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple EVs charge simultaneously at high power rates, then charging speed and user satisfaction improve, but electrical capacity overload and power outage risk increase
Solution Approach 1:
The patent implements dynamic load management that continuously monitors and adjusts power distribution to EV charging stations in real-time based on available electrical capacity. The system dynamically scales charging rates up or down depending on grid conditions, transforming the static power distribution into a flexible, adaptive system that prevents overload while maximizing charging efficiency when capacity is available.
Solution Approach 2:
The system employs feedback mechanisms where the load manager continuously receives data about power consumption, electrical capacity, and charging status from multiple EVSEs. Based on this feedback, the system automatically adjusts power allocation to prevent capacity overload, creating a closed-loop control system that maintains reliability while optimizing charging performance.
2Reliability
If electrical capacity is increased to support more simultaneous chargers, then power supply reliability improves, but infrastructure cost increases
Solution Approach 1:
The load management system enables the existing electrical infrastructure to serve itself by automatically monitoring capacity limits and regulating power distribution. This self-service capability allows the system to support multiple EVSEs with existing capacity without requiring infrastructure upgrades, as the load manager intelligently allocates available power to prevent overload conditions.
Solution Approach 2:
The system changes operational parameters by adjusting power delivery rates dynamically based on real-time capacity assessment. Instead of increasing physical infrastructure capacity, the system optimizes the utilization of existing capacity through parameter adjustment, allowing more EVSEs to operate simultaneously within safe electrical limits without costly upgrades.
3Reliability
If power delivery is reduced to prevent overload, then infrastructure safety improves, but charging efficiency decreases
Solution Approach 1:
The load manager implements periodic monitoring and adjustment cycles, continuously assessing electrical capacity and modulating power delivery in controlled intervals. This periodic action allows the system to maintain safety thresholds while maximizing charging efficiency during periods when capacity is available, creating a rhythm of optimization that balances both concerns.
Solution Approach 2:
The system applies partial power delivery adjustments rather than uniform reductions, allocating power selectively to EVSEs based on priority, charge state, and available capacity. This partial action approach ensures infrastructure safety while maintaining optimal charging efficiency for individual vehicles, avoiding unnecessary reduction of power to all chargers.
Data Source
AI summary
Systems and techniques are provided for wireless dynamic load management for electric vehicle (EV) charging stations. An example process includes receiving load usage data indicative of electric power consumed by EV charging station(s) on a site. Each of the EV charging station(s) may be simultaneously charging a respective EV. The example process includes determining a total electric power that has been consumed by an entire set of EV charging station(s) on the site based on the load usage data, comparing the total electric power that has been consumed by the entire set of EV charging station(s) on the site and a power threshold for the site, and based on the comparison of the total electric power that has been consumed by the entire set of EV charging station(s) and the power threshold, transmitting, to the EV charging station(s), a signal to control the electric power consumed by the EV charging station(s).