EVs in Distribution Networks—Optimal Scheduling and Real-Time Management

Abstract

The high penetration of Renewable Energy Sources (RES) and Electric Vehicles (EVs) into the grid introduces new challenges for Distribution Systems (DSs). The uncertainties related to these assets necessitate the development of real-time methodologies to optimize the operation of Low Voltage (LV) and Medium Voltage (MV) DSs. This paper aims to fill the gap in the literature by proposing a holistic real-time DS optimization model that considers the coupling of MV and LV DSs. Specifically, the methodology adopts a bottom-up three-layer approach. At the first layer an optimal EV Smart Charging Scheduling (SCS) methodology is applied for power losses minimization at the LV DSs, considering the characteristics of individual households (maximum rated power of the electrical installation, Photovoltaic generation, and load and EV charging demand). The second layer introduces a residential controller that fully exploits the flexibility of EVs, minimizing the impact of forecasting errors while satisfying limitations regarding households’ overloading protection. The third layer involves a real-time Network Reconfiguration (NR) methodology, considering real-time power transactions between MV and LV DSs, and determining the optimal topology through a cost-worth analysis of power loss reduction and switch operation costs. The overall design of the proposed methodology ensures broader adoption, repeatability, adaptability, and scalability across diverse DSs, including various types of LV DSs (residential, commercial, etc.) and different MV DS configurations. The proposed methodology can reduce DS power losses by up to 34.41% compared to the base scenario, which involves the operation of the DS without employing either EV SCS or NR.

Keywords

• Distribution system
• electric vehicle charging
• vehicle-to-grid
• forecast uncertainty
• real-time energy management