EV Charging Power Setpoint Control Under Grid Overload Constraints
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Solution Overview
Problem
Power distribution systems, particularly those with electrical vehicle charging stations, face challenges in managing power supply within desirable time windows due to power limitations, leading to overload conditions, especially when integrating renewable resources and vehicle-to-grid power transmission.
Innovation Solution
A method and system that determine and adjust EV power setpoints based on received data, power constraints, and overload conditions to control the power distribution system, involving distributed and central architecture, converters, and processors to manage power flow and prioritize charging/discharging processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple EVs are recharged simultaneously at distributed charging stations, then the productivity and user satisfaction improve, but the power distribution system may experience overload conditions due to power limitations at charging equipment and grid interface
Solution Approach 1:
The patent implements dynamic power setpoint adjustment for EV charging stations based on real-time system conditions. The controller continuously monitors power availability and adjusts charging power levels dynamically, allowing the system to maximize productivity when power is abundant while preventing overload when power is limited, thus resolving the contradiction between recharging throughput and system stability
Solution Approach 2:
The patent employs feedback mechanisms where the controller receives information about grid power availability, charging station capacity, and EV charging status. Based on this feedback, the controller adjusts power distribution decisions to maintain system reliability while optimizing productivity. The feedback loop enables the system to respond to changing conditions and prevent overload scenarios
2Reliability
If power constraints are enforced to prevent overload conditions, then the reliability is maintained, but the productivity and charging speed are reduced
Solution Approach 1:
The patent applies partial action by providing full charging power only when system conditions permit, and reducing power delivery when constraints are detected. Rather than consistently limiting power to ensure reliability, the system delivers full power when possible and applies constraints only when necessary, thus maintaining high productivity while preserving reliability
3Adaptability or versatility
If the system integrates renewable resources and vehicle-to-grid power transmission, then the adaptability and energy efficiency improve, but the device complexity and control difficulty increase
Solution Approach 1:
The patent implements a universal controller that manages multiple power flow directions and modes: grid-to-charging station, charging station-to-EV, EV-to-grid, and renewable integration. This multi-functional controller handles all power transmission scenarios through a unified control architecture, enabling the system to integrate diverse resources and functions without proportionally increasing complexity
Solution Approach 2:
The patent combines multiple control functions into a centralized control system that simultaneously manages power distribution, monitors system status, adjusts power setpoints, and coordinates V2G operations. By merging these functions into a single integrated controller, the system achieves high adaptability while managing complexity through consolidation rather than proliferation of separate control systems
4Ease of operation
If priority-based sorting is implemented for multiple EVs, then the fairness and user satisfaction improve, but the control complexity and processing time increase
Solution Approach 1:
The patent implements preliminary assignment of priority levels to EVs based on predefined criteria such as battery state of charge, time of arrival, or user preferences. By determining priorities in advance rather than making complex real-time decisions about power allocation, the system achieves fair charging allocation while minimizing control complexity and processing time during actual power distribution
Data Source
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AI summary
The present disclosure relates to a method for controlling a power distribution system comprising at least one distributed charging station for coupling to at least one electrical vehicle, EV, and a grid interface for coupling the at least one distributed charging station to a power grid. The method comprises determining an EV power setpoint of the at least one EV based on received data (S101); determining a first overload condition based on the EV power setpoint and a first power constraint of the at least one distributed charging station (S102); updating the EV power setpoint based on the first overload condition (S103); determining a second overload condition based on the updated EV power setpoint and a second power constraint of the grid interface (S104); redetermining the EV power setpoint based on the updated EV power setpoint and the second overload condition (S105); and controlling the power distribution system based on the redetermined EV power setpoint (S106). The present disclosure also relates to a respective system and a power distribution system.