Optimal Interaction Strategy for Vehicle-to-grid Based on Interval Uncertainty Model

Uncertainty of behaviors of EV users brings difficulties to resource scheduling and electricity price setting in a distribution network. In this regard, this paper proposes an optimal interaction strategy for distribution network to EV users based on interval constraints of electricity costs and user behaviors to minimize peak-to-valley load difference and charging cost. An interval participation model for EV users is also proposed to consider baseline participation under base electricity price, as well as multiple influence factors of user participation under variable charging prices. The non-dominated sorted genetic algorithm Ⅱ (NSGA-Ⅱ) is adopted to solve the two proposed interval models. Simulation results based on real-world EV models verify the proposed optimal scheduling based on interval models can effectively reduce peak-valley difference of distribution networks and electricity costs of EV users. Peak-valley difference rate of loads can be reduced from 33% to 28% under 1000 EVs.