On-Off Scheduling for Electric Vehicle Charging in Two-Links Charging Stations Using Binary Optimization Approaches

Area of Science:

• Electrical Engineering
• Operations Research
• Computer Science

Background:

• Managing electric vehicle (EV) charging is crucial for grid stability and user satisfaction.
• Existing charging strategies often struggle to balance energy demand, grid load, and operational efficiency.
• Three-phase EV charging stations with dual, non-simultaneous ports present unique scheduling challenges.

Purpose of the Study:

• To develop an optimized on-off scheduling scheme for EV charging stations.
• To ensure user energy demands are met while utilizing available power efficiently.
• To minimize load peaks and reduce the number of port switching operations.

Main Methods:

• Formulation of an on-off scheduling scheme as a binary linear programming problem.
• Extension to a binary quadratic programming problem to include charging smoothness constraints.
• Application of algorithmic approaches like the Frank-Wolfe algorithm and successive linear approximations.

Main Results:

• The successive linear approximations method proved scalable, efficient, and flexible for EV charging.
• The proposed scheme effectively shaved peak energy consumption loads.
• Smooth charging profiles were maintained while satisfying EV energy demands.

Conclusions:

• The developed on-off scheduling scheme offers an effective solution for managing EV charging stations.
• Successive linear approximations provide a robust method for optimizing charging schedules.
• This approach contributes to efficient grid integration of electric vehicles.