Dynamic EV Charging Scheduling with Grid and Battery Power
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Solution Overview
Problem
The challenge lies in dynamically scheduling the charging of Electric Vehicles (EVs) at charging stations, where the limited power from the grid and varying arrival and departure times of EVs necessitate a fair distribution of energy, considering the power availability from both the grid and stationary batteries, while ensuring that all EVs are charged efficiently and within their departure times.
Innovation Solution
A charging scheduling system that includes a prediction database for EV arrivals, a power database, and a scheduling unit that calculates available energy and distributes it among waiting EVs based on their energy requirements, using a fair use policy to adjust charging rates and times, ensuring that EVs with higher requirements receive proportionally more energy, thereby optimizing the use of available power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If rapid charging mode is used, then charging time is reduced, but power requirement increases significantly
Solution Approach 1:
The charging rate is made dynamic rather than fixed. The system adjusts the charging rate in real-time based on grid power availability, stationary battery status, and EV queue conditions. This allows the system to switch between rapid charging (when power is abundant) and ordinary charging (when power is limited), optimizing both charging time and power requirement dynamically
Solution Approach 2:
The system changes the charging parameter (charging rate) based on varying conditions. By monitoring power availability and adjusting the charging rate parameter accordingly, the system can achieve rapid charging when possible while reducing power consumption when grid capacity is limited, thus resolving the contradiction between charging speed and power requirement
2Ease of operation
If fair use policy is applied to distribute energy equally among EVs, then equity is improved, but total energy utilization decreases when EV arrivals are probabilistic
Solution Approach 1:
The charging distribution policy transitions from static equal distribution to dynamic allocation. The system continuously adjusts energy distribution based on predicted EV arrivals, current queue status, and power availability, maintaining fairness while optimizing total energy utilization
Solution Approach 2:
The system performs preliminary prediction of future EV arrivals and charging demands. By anticipating future conditions, the system can proactively allocate energy resources more efficiently, ensuring that energy is distributed fairly to current EVs while reserving appropriate capacity for anticipated arrivals, thus improving overall energy utilization
3Productivity
If dynamic scheduling is implemented to predict future power requirements, then charging efficiency is improved, but system complexity increases
Solution Approach 1:
The scheduling system is segmented into distinct functional modules: prediction module (for forecasting EV arrivals and power requirements), optimization module (for calculating optimal charging schedules), and control module (for executing charging commands). This modular segmentation improves charging efficiency through coordinated operation while managing system complexity through clear separation of concerns
Solution Approach 2:
The system introduces an energy management control device as an intermediary between the grid/station and EVs. This intermediary handles the complex prediction and optimization calculations, simplifying the overall system architecture by centralizing the intelligent scheduling function in a dedicated component rather than distributing complexity across multiple elements
Data Source
AI summary
A charging prediction database stores information on electric vehicles expected to arrive for charging. A profile/charging information database stores information on electric vehicles that have arrived and been waiting for charging. A power database stores information on a power source including at least one of a power grid and a stationary battery. An energy calculating unit calculates energy available from the power source based on the power database. A scheduling unit schedule charging of the electric vehicles waiting for charging in consideration of the electric vehicles expected to arrive.