Optimal placement of fast charging station in radial distribution networks through particle swarm optimization

• Main Authors: Wang, Xingye, Syed Nasir, Syed Norazizul, Afrouzi, Hadi Nabipour, Chen, Rui Geach, Mehranzamir, Kamyar, Dai, Xinyue
• Format: Conference or Workshop Item
• Published: 2023
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/107667/; http://dx.doi.org/10.1109/CENCON58932.2023.10369593

The demand for fossil fuels is steadily increasing, leading to higher carbon emissions and pollution, which contribute to global warming. The adoption of electric vehicles (EV) is growing each year, which necessitates an increase in the number of Fast Charging Stations (FCS) and their efficiency. FCS enables faster charging of EVs, but this also results in increased power loss and lower voltage profiles. This research focuses on strategically integrating 4 different sizes of FCSs in the optimal locations as the effects on the IEEE-33 radial distribution network. Additionally, power losses in the stated network are considered as a decision-making factor to optimize the placement of FCSs. The power flow analysis of the proposed network bus is conducted using the backward-forward sweep method. A particle swarm optimization (PSO) method is used to minimize power loss across the network and identify the optimal placement of FCSs. The results demonstrate that the higher sizes of FCSs, the higher the power loss after the PSO optimization. However, power loss reduction increases from 6.62% to 10.9%, which will further decrease the power loss to around 132kW to 134kW. Besides, the simulated result shows that the best three locations for the four FCSs are bus 2, bus 19, and bus 20. The final location depends on the FCS sizes, with bus 33 chosen for lower sizes and bus 21 selected for sizes beyond 100kW. These findings are significant for informing future FCS layout optimization efforts.