EVSE Load Balancing With Cloud-Edge Dynamic Charging Control
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Solution Overview
Problem
The increasing adoption of electric vehicles (EVs) has created a need for efficient energy demand management at electric vehicle charging stations, where effectively balancing EV supply equipment (EVSE) loads within available capacity and reducing peak demand to prevent system overloads is critical.
Innovation Solution
A method and system that utilize a cloud controller and an edge controller to manage the charging of EVs at an electric vehicle charging station. The system performs a normal charging procedure initially, and when the total load reaches a trigger threshold, dynamic load management (DLM) is activated. The edge controller then adjusts the charging capacity of each EVSE based on the available EV charging capacity, optimizing power allocation in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If normal charging procedure is performed on EVSEs to charge EVs, then EV charging service is provided, but total load may reach or exceed trigger threshold causing system overload
Solution Approach 1:
The system dynamically switches between normal charging procedure and dynamic load management mode based on real-time total load conditions. When total load reaches the trigger threshold, the system transitions to DLM mode where edge controller adjusts EVSE charging capacities dynamically, ensuring system reliability while maintaining charging service
Solution Approach 2:
The system continuously monitors total load and uses this feedback to control the charging process. When total load reaches the trigger threshold, feedback triggers the activation of dynamic load management mode, and the edge controller adjusts EVSE capacities based on real-time load conditions, creating a closed-loop control system that prevents overload while maintaining service
2Reliability
If dynamic load management is activated to prevent system overload, then system reliability is improved, but real-time control responsiveness may be delayed
Solution Approach 1:
The control system is segmented into two independent controllers: cloud controller for high-level charging management and edge controller for real-time load management. This segmentation allows the edge controller to handle time-critical load adjustments locally without waiting for cloud controller responses, improving control responsiveness while maintaining system reliability
Solution Approach 2:
The edge controller acts as an intermediary between the cloud controller and EVSEs, receiving charging requests from the cloud controller and translating them into real-time control commands for EVSE capacity adjustment. This intermediary role enables fast local responses to load changes while maintaining coordination with the overall charging management system
3Ease of operation
If cloud controller manages all charging operations, then centralized control is maintained, but real-time load adjustment capability is insufficient
Solution Approach 1:
Control functions are segmented between cloud controller and edge controller. The cloud controller maintains centralized control for charging requests and coordination, while the edge controller handles real-time load management and EVSE capacity adjustment. This segmentation enables both centralized oversight and rapid local response to load conditions
Solution Approach 2:
The system merges centralized cloud-based charging management with distributed edge-based real-time control. The cloud controller and edge controller work together in a hierarchical structure, combining the advantages of centralized coordination with decentralized rapid response capability for load management
Data Source
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Figure 2A
AI summary
A method for charging electric vehicle (EV) at an electric vehicle charging station equipped with electric vehicle supply equipments (EVSEs) is provided. A normal charging procedure is performed on the EVSEs to charge EV under control of a cloud controller. Dynamic load management (DLM) is inactive during the normal charging procedure. A first time point, referred to whether a total load is equal to or larger than a trigger threshold during the normal charging procedure, is determined. If the determination is yes, DLM is activated to charge the at least one EV by the EVSEs under control of an edge controller. A second time point, referred to whether a gradient of the total load reaches a gradient threshold during activated DLM, is determined. If the determination is yes, the charging capacity of each EVSE is adjusted based on an available EV charging capacity by the edge controller.