Multi-objective smart charging scheduling scheme for EV integration and energy loss minimization in active distribution networks using mixed integer programming

Abstract

Efficient scheduling of electric vehicles (EVs) within power distribution networks (PDNs) is crucial due to the conflicting interests of various stakeholders, such as EV owners, who seek cost savings, and distribution network operators (DNOs), who focus on minimizing peak demand and reducing losses. This issue becomes even more pronounced with vehicle-to-grid (V2G) operations. This paper proposes a multi-objective EV scheduling model to determine the optimal trade-off between the economic interests of EV owners and the technical needs of the grid, thereby offering benefits to both stakeholders. The proposed model minimizes the total charging cost of EV owners and flattens the load curve in the EV-integrated PDN simultaneously. This is achieved by optimally utilizing both the grid-to-vehicle (G2V) and V2G capabilities of EVs while also considering battery health. A weighted sum method is used to find a set of non-dominated solutions to the multi-objective EV scheduling problem. Additionally, to further enhance the network efficiency and complement the multi-objective EV scheduling, the model incorporates distribution network reconfiguration (DNR) that is carried out at each hour of the day. The efficacy of the proposed model is validated by implementing it on a modified 33-node and IEEE 123-node test networks.