A new optimization framework shows how coordinated electric vehicle charging can simultaneously reduce distribution grid losses and lower costs for EV owners, particularly when renewable energy sources are integrated into the system.
The framework uses a bi-level approach: grid operators optimize network performance at the upper level by minimizing feeder losses, while EV owners minimize their charging expenses at the lower level through time-of-use pricing signals. This dual-objective structure encourages collaboration between utilities and customers without requiring centralized control of individual vehicles.
Testing on a 28-bus distribution network revealed substantial benefits across seasonal conditions. In baseline operation without coordination, system losses reached 6.5 MW. Winter coordinated charging without vehicle-to-grid capability reduced losses to 5.7 MW, while summer improvements reached 6.1 MW. When bidirectional power flow was enabled—allowing vehicles to discharge back to the grid during peak demand—losses fell further to 4.9 MW in winter and 5.4 MW in summer, representing total reductions of 24% and 17% respectively.
Customer savings were equally compelling. Without coordination, average winter charging costs reached $196.35, dropping to $166.59 with the optimized framework—a 15% reduction. Summer results showed similar gains, declining from $205.17 to $191.33.
The model incorporates realistic constraints including variable wind and solar generation, seasonal operating conditions, and vehicle availability patterns. By reformulating the lower-level optimization problem using Karush–Kuhn–Tucker conditions, researchers created a mathematical structure solvable using standard optimization solvers.
These findings suggest that coordinated EV charging represents an untapped opportunity for distribution networks transitioning to high renewable penetration. The framework is flexible enough to accommodate different tariff structures and vehicle technologies, making it applicable across diverse utility markets and geographic regions.
