Adaptive EV Charging Power Allocation for Building Load Limits
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Solution Overview
Problem
The challenge in multi-unit residential buildings is to provide electric vehicle (EV) charging infrastructure without overloading the existing power infrastructure, which is often inadequate and costly to expand, and may lead to grid overload issues due to sudden increased power demand.
Innovation Solution
A system that dynamically adjusts power distribution to EVs based on real-time measurements of residential loads, using sensors and processors to ensure that the combined load of EVs and residential devices does not exceed a predetermined threshold, allowing for flexible and scalable integration without significant alterations to the existing power infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard level 2 charging units are installed in multi-unit residential buildings, then EV charging capability is improved, but power demand increases significantly risking grid overload
Solution Approach 1:
The system dynamically adjusts the power output of EVSEs based on real-time monitoring of total building power consumption. The controller modulates charging rates to ensure the sum of EV charging power and existing building loads never exceeds the service entrance capacity, transforming static fixed-power chargers into dynamic adaptive chargers that respond to changing load conditions
Solution Approach 2:
The system implements continuous feedback by monitoring power consumption from both the EVSEs and existing building loads through sensors and meters. This feedback loop enables the controller to real-time adjust EV charging power levels, preventing grid overload while maximizing available charging capacity based on current building conditions
2Power
If power infrastructure is expanded to accommodate EVSEs, then power capacity is improved, but installation time and cost increase
Solution Approach 1:
Instead of physically expanding the power infrastructure, the system changes the operational parameters of existing EVSEs by dynamically adjusting their power output levels. This software-based parameter control allows the building to accommodate EV charging within existing electrical capacity, eliminating the need for costly and time-consuming infrastructure upgrades
Solution Approach 2:
The system creates a virtual power capacity model that represents the available power headroom in the building's electrical system. This virtual model allows the controller to allocate and manage EV charging power without physical infrastructure changes, effectively copying the function of expanded capacity through intelligent control rather than physical expansion
3Power
If power infrastructure is expanded to accommodate EVSEs, then power capacity is improved, but installation cost increases
Solution Approach 1:
The system achieves increased power capacity for EV charging by changing the operational parameters of existing EVSEs rather than installing new infrastructure. The controller adjusts power delivery parameters based on available capacity, providing a low-cost software-based solution that eliminates expensive electrical upgrades, circuit breaker installations, and panel modifications
Data Source
AI summary
Flexible and scalable systems and methods for charging electric vehicles (EVs) are disclosed. For example, a system may be configured to dynamically adjust the amount of power available to one or more EVs based on real-time measurements of a residential load. In some implementations, the system may be configured to ensure that the combined load of the EVs and the residential load does not exceed a predetermined threshold. The predetermined threshold may be based on the power capacity and electrical specifications of an existing building. As a result, the system can be added to an existing building without overloading the grid and/or without significantly altering the power infrastructure of the building.