Optimization of active distribution network based on SaDE-BBO algorithm in V2G mode

Abstract

In order to solve the problem of difficulty in achieving individual scheduling for large-scale electric vehicles entering the grid and the existence of "dimensionality disaster" in cluster scheduling, a hierarchical and partitioned optimization operation model for active distribution network based on vehicle-to-grid(V2G) mode is established. The upper level optimization model schedules the electric vehicle agent (EVA) of electric vehicles, optimizes the charging and discharging power of EVA in each region, and serves as input for the lower level optimization model. Lower level optimization model adjusts various voltage regulation methods. In terms of optimization algorithm, a self adaptive differential evolution biogeography based optimization (SaDE-BBO) algorithm is proposed and simulated in the improved IEEE 33-node distribution system. The results show that under different charging control strategies, the coordinated interaction between V2G mode and various voltage regulation methods has significant advantages in reducing EVA operating costs in various regions, suppressing load fluctuations, and ensuring the safe and economic operation of active distribution networks. Compared with other optimization algorithms, the SaDE-BBO algorithm has better solutions and convergence.

Keywords

• vehicle-to-grid (v2g)
• distributed generation
• active distribution network
• hierarchical partition
• optimized operation
• self-adaptive differential evolution-biogeography-based optimization (sade-bbo) algorithm