EV Charging Load Management via Dynamic Power Adjustment
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Solution Overview
Problem
Fast charging of electric vehicles poses challenges for power grids due to high and stochastic power demands, leading to instability and reduced flexibility in charging options for both drivers and charging stations, with existing methods unable to effectively manage peak loads or utilize charging capacity efficiently.
Innovation Solution
A method and system that dynamically adjust charging power profiles at stations to match available power generation, predict and group electric vehicle charging needs based on technical and non-technical parameters, and facilitate communication between vehicles and stations to optimize load management and capacity utilization, thereby reducing peak demand and enhancing flexibility and comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If fast charging processes are implemented with high power levels to meet immediate power demand, then charging speed and user convenience are improved, but power grid stability and capacity utilization deteriorate due to highly stochastic and intermittent load patterns
Solution Approach 1:
The patent implements dynamic load management by continuously adjusting charging power levels based on real-time power generation availability and grid conditions. The system transitions from static high-power fast charging to adaptive power delivery that responds to changing grid conditions, thereby maintaining charging speed where possible while ensuring power grid stability through dynamic adjustment of charging parameters.
Solution Approach 2:
The system changes operating parameters by adjusting charging power levels, voltage, and current based on available power generation profiles. By modifying these electrical parameters dynamically according to grid conditions, the system achieves both fast charging performance and power grid stability, resolving the contradiction between high charging speed and reliable grid operation.
2Productivity
If conventional demand response methods are used to control normal charging processes, then capacity utilization and operational efficiency are improved, but flexibility and adaptability to stochastic loads deteriorate because fast charging cannot be influenced by load shifting or throttling
Solution Approach 1:
The system performs preliminary actions by predicting power generation profiles and pre-planning charging schedules before actual charging demands arise. By anticipating available power and user needs in advance, the system can optimally allocate charging capacity and adjust fast charging processes proactively, thereby improving both capacity utilization and flexibility without relying on reactive demand response methods.
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor power generation availability, charging station status, and user charging patterns. This real-time feedback enables the system to adaptively adjust fast charging processes, optimizing capacity utilization while maintaining flexibility to respond to stochastic loads, thus resolving the limitation of conventional demand response methods.
3Loss of energy
If solar or wind power is integrated into the power grid to provide sustainable energy, then environmental sustainability is improved, but power grid stability and predictability of charging options worsen due to increased variability in energy supply
Solution Approach 1:
The patent applies dynamic adaptation by continuously adjusting charging power delivery to match the variable output of solar and wind power generation. The system responds to real-time fluctuations in renewable energy supply by modulating charging rates, thereby maintaining power grid stability while fully utilizing sustainable energy sources, thus resolving the contradiction between sustainability and grid stability.
Solution Approach 2:
The system changes operational parameters by adjusting charging voltage, current, and power levels in response to variable renewable energy input. By dynamically modifying these electrical parameters to match sustainable power generation profiles, the system ensures both environmental sustainability and stable grid operation, eliminating the trade-off between green energy integration and power reliability.
4Reliability
If additional costly energy generation is deployed to compensate peak charging demands, then power supply reliability is improved, but economic efficiency and loss of energy worsen due to the need for expensive peak power plants like gas turbines
Solution Approach 1:
The system performs preliminary actions by predicting peak charging demands and power generation availability in advance. This enables proactive load management and optimal utilization of existing power generation capacity, eliminating the need for expensive peak power plants. By preparing charging schedules beforehand based on predicted conditions, the system ensures reliable power supply while avoiding the economic inefficiency of additional costly energy generation infrastructure.
Data Source
Figure 1
AI summary
The present invention relates to a method for charging electric vehicles by charging stations, comprising the steps of a) Assigning electric vehicles to different electric vehicle supply equipment of the charging stations, and b) Charging the electric vehicles according to electric vehicle charging information and provided charging power by the electric vehicle supply equipment of the charging stations, wherein a matching of electric vehicle charging information, preferably load profiles, of electric vehicles and charging power information, preferably provided charging power, of different charging stations is predicted based on electric vehicle information and a charging station parameter and wherein based on the predicted matching steps a) and b) are performed. The present invention relates also to a system for charging electric vehicles.