Dynamic Reconfiguration of Multiobjective Distribution Networks Considering DG and EVs Based on a Novel LDBAS Algorithm

Aiming to improve the operation economy and power quality of distribution systems subject to the fluctuating and stochastic power outputs of distributed generation (DG) units and electric vehicles (EVs), a multiobjective optimization model for network reconfiguration and its corresponding solution method are proposed. First, a dynamic reconfiguration model is constructed based on the power loss rate (PLR) as well as the active power loss, the load balancing index and the maximum node voltage deviation, which serve as the optimization indexes. Second, the Lévy flight and chaos disturbed beetle antennae search (LDBAS) algorithm is presented based on the grey target decision-making technique, which can not only improve the computational efficiency but also find the most satisfactory solution for the proposed dynamic reconfiguration model. Considering the uncertainties of loads and DG outputs, the influence on the load curve of EV connecting to the distribution network at different penetration rates and under different charging/discharging modes is analysed. Additionally, the modified IEEE 33-bus and 118-bus test radial distribution networks are simulated to verify the effectiveness and superiority of the presented reconfiguration model and the improved LDBAS method, and the results illustrate that the proposed reconfiguration method can improve the operation economy and power quality of the distribution system and encourage the penetration of EVs.