The integration of renewable energy and electric vehicles presents both opportunity and complexity for grid operators. While EVs offer substantial benefits as distributed storage assets, their charging patterns and vehicle availability introduce new uncertainties alongside existing renewable forecast errors. A new dispatch model addresses these dual challenges by treating EV fleets as controllable, bidirectional energy resources that can absorb excess generation or discharge power during peak periods.
The electric vehicle-integrated chance-constrained economic dispatch (EV-Integrated CCED) model employs distributionally robust optimisation to hedge against worst-case forecast deviations without requiring precise probability distributions. Rather than assuming known uncertainty sets, this approach guarantees feasibility across a family of possible distributions, protecting system reliability when actual renewable output or demand differs from predictions. The model dynamically schedules charging and discharging windows based on real-time conditions, EV state-of-charge levels and grid requirements.
Numerical validation on the eight-zone ISO New England test system revealed that the framework substantially outperforms traditional economic dispatch methods. Benefits include lower total operating costs, better utilisation of renewable generation, reduced curtailment and improved frequency stability margins. The chance-constraint formulation ensures that load-serving reliability requirements are met with high probability, even during high-renewable-penetration scenarios.
Key to the model's effectiveness is its treatment of EV flexibility as a tunable resource. During periods of high renewable availability, vehicles can charge efficiently, storing surplus wind or solar energy. Conversely, during peak demand or low renewable periods, aggregated EV batteries discharge to reduce reliance on expensive conventional generation. This two-way flexibility creates a natural shock absorber for grid imbalances caused by forecast errors.
As transportation electrification accelerates and renewable targets rise, dispatch algorithms must evolve to capture EV flexibility while maintaining operational certainty. This work demonstrates that robust optimisation frameworks paired with vehicle-grid integration can deliver both cost efficiency and reliability in increasingly dynamic power systems.
