The electric vehicle mobile energy storage technology has drawn widespread attention nationally as well as internationally. The electric vehicle mobile energy storage system is modeled as an optimization problem considering power system constraints， battery constraints and vehicle owners constraints. The particle swarm optimization（PSO） algorithm is adopted to solve the optimization problem of the proposed model. Since the standard particle swarm optimization（SPSO） algorithm is more likely to get premature convergence when it comes to high-dimension problems， based on the ideas of the bionic algorithm， an improvement is made to the SPSO. A control strategy of electric vehicle mobile energy storage system is proposed based on the collision avoidance particle swarm optimization（CAPSO）. The testing results of several benchmark functions show that the improved algorithm has better performance than SPSO. The quantitative simulation results of various cases including the load-smoothing， the renewable energy output fluctuation smoothing and the load-smoothing considering renewable energy generation validate the efficacy of the proposed model and the control strategy.