Optimization of Economic Dispatch for AC-DC Hybrid Microgrid with Electric Vehicle Participation

Under the dual-carbon background, the sudden increase in the number of electric vehicles (EVs) entering the grid poses a challenge to the safe and economic operation of microgrids. In this paper, the dispatchable capacity models of private electric vehicle cluster (PEVC) connected to the grid at night and network-connected electric vehicle cluster (NEVC) connected to the grid during daytime are developed based on Monte Carlo sampling, Minkowski summation method and LSTM neural network algorithm. On this basis, a mixed-integer second-order cone planning (MISOCP) model for AC-DC microgrids is constructed with the objective of cost optimization and taking into account the solution efficiency and accuracy. The example results demonstrate that implementing time-of-day tariffs leads to a 15.05% reduction in the cost of microgrid operation compared to disordered charging. This is achieved through an orderly charging and discharging strategy that considers the load and storage characteristics of electric vehicles (EVs).