Simulation study on optimal placement and sizing of Battery Switching Station units using Artificial Bee Colony algorithm

Abstract

The improvements on DC electrical motor and battery technologies have increased the industries' and users' interest in Electrical Vehicle (EV). In line with this, multiple types of Charging Stations (CS) have also been introduced to support the EV's growth in the vehicle market. Three types of CS units that are available nowadays are Levels 1, 2 and 3 (DC Charging type). However, there are some drawbacks on these CS types either in terms of charging time (for Levels 1 and 2) or the impact to the system performance (Level 3). Thus, the Battery Switching Station (BSS) is used to tackle all these problems. In the BSS, the customers' current batteries are swapped with fully charged batteries by the automated system and the charging process of those batteries will be done at a later time by the BSS. Therefore, the long charging time issue can be evaded. However, inappropriate placement of BSS in the distribution network will give enormous impact to the distribution network due to the lower voltage level in distribution system. Two methods have been used to place the BSS in this study, which are, analytical and meta-heuristic (Artificial Bee Colony (ABC)) methods. The ABC is chosen due to the simplicity of the algorithm in finding the optimal location of BSS. For further improvement, the ABC is employed to find the optimal size of BSS and DG output. The results show that the analytical and optimization methods gave similar results in finding the optimal location of BSS, which is better than randomization of BSS placement. Furthermore, the analysis on optimal size of BSS and DG output (simultaneously) gives the lowest power loss compared to other analyses.