A systematic approach to accommodate plug-in electric vehicles in distribution networks with optimal integration of distributed generation

• Main Authors: Memon, Zeeshan Anjum, Hassan, Mohammad Yusri, Mat Said, Dalila, Leghari, Zohaib Hussain, Shaikh, Pervez Hameed
• Format: Conference or Workshop Item
• Published: 2022
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/98592/; http://dx.doi.org/10.1007/978-981-16-8690-0_31

The recent increase in plug in electric vehicles (PEVs) load has posed severe accommodation issues for the power grids that were not primarily designed to serve PEVs’ charging load. Therefore, the unplanned PEVs’ integration into the distribution networks will deteriorate the system performance by increasing the power loss and voltage deviation at nodes. In this context, this study proposes a methodology to enhance the distribution networks’ PEVs hosting capacity, without degrading the system performance, by optimally allocating the distributed generation (DG). Initially, aiming to minimize the power losses in the distribution network, the optimal siting, sizing and number of the DG units were determined using the particle swarm optimization (PSO) algorithm. Later, the best network bus for PEV accommodation was selected on the criteria of maximum hosting capacity and loss reduction in the distribution network. Then, considering the accessible power output from the grid and the mounted DGs, the PEVs accommodation in the network is evaluated based on different battery capacities (BCs) and state-of-charge (SoC) as decisive factors. The test results on the IEEE 33-bus demonstrate that in the presence of DGs, the distribution network carries a PEV load of 4.418 MW with 48.82% reduction is losses (compared to case without optimal DG allocation) and voltage improvement of 6.98%. It was also examined that the PEVs accommodation in the distribution network varied from 2492 units to 61,446 units, depending on the size of battery pack and its SoC. The proposed research will enable the distribution companies to handle the large number of PEVs in the long-term planning paradigm.