Grid Scheduling Strategy Considering Electric Vehicles Participating in Multi-microgrid Interaction

With the expansion of the scale of power grid and the increase of the number of microgrids, the energy interaction between microgrids using contact lines will greatly increase the computation of the superior dispatching center. Therefore, the contact lines between microgrids are cancelled, so that the microgrids can realize energy interaction through the distribution network. However, this method may lead to overload of distribution network connections while reducing the computation. Due to its good transfer characteristics, the addition of electric vehicles (EVs) can alleviate the contact line pressure and realize the load transfer of microgrids. On this basis, a grid dispatching model based on the participation of EVs in microgrid interaction is proposed. Contact lines between microgrids are replaced by EVs and 100% transmission through the distribution network. The grid load is optimized with the goal of minimizing total cost, maximizing renewable energy utilization, and maximizing profit of each integrator. In the process of model optimization, aiming at the problem that the speed factor in the particle swarm optimization algorithm cannot take into account the optimal direction and the optimal step size, the adaptive time factor is added to establish a two-layer improved particle swarm optimization algorithm, which realizes the cooperative optimization of load and electricity price. The simulation results show that the total cost and underutilization of renewable energy of IEEE33-node system are reduced by 13.79% and 67.85%, compared with the traditional interaction mode, while they are reduced by 0.425% and 6.11% in IEEE43-node system.