A New Two-Stage Approach to Coordinate Electrical Vehicles for Satisfaction of Grid and Customer Requirements

• Main Authors: Trinnapop Boonseng, Anawach Sangswang, Sumate Naetiladdanon, Samundra Gurung
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: Applied Sciences
• Subjects: battery degradation; environment-friendly; meta-heuristics; optimization; V2G; VUF
• Online Access: https://www.mdpi.com/2076-3417/11/9/3904

Recently due to air pollution concerns, a large number of electric vehicles have been integrated into the electric distribution system. However, the uncoordinated charging of this technology can cause different voltage issues. This paper proposes a two-stage optimization approach with active and reactive power control to coordinate electric vehicles with both grid-to-vehicle and vehicle-to-grid capabilities to satisfy both grid requirements and electric vehicle prosumer requirements. The system requirements considered are voltage deviation and unbalance and the electric vehicle prosumer requirements considered are minimization of charging and battery degradation costs. The coordination problem is formulated as an optimization problem, where the first stage objectives are: minimization of voltage unbalance, customer charging and battery degradation costs. The first stage optimization problem is solved using the meta-heuristic optimization algorithm known as particle swarm optimization to obtain an optimized real power schedule for the electric vehicles. The second stage is then solved of which the objective is to minimize the bus voltage deviation and provides the reactive power schedule for electric vehicles. All the analyses were carried out on the IEEE 34 bus distribution system and the study results show that the proposed method allows prosumers to charge at a minimum cost without any grid voltage unbalance factors and under/over voltage problems under different scenarios. Thus, this work can be beneficial for system operators or electric vehicle aggregators to create a day-ahead schedule.