The Impacts of Electric Charging Stations on Distribution Power Grids under Different Simulations using Jellyfish Swarm Algorithm

Abstract

This research presents different implementations for placing electric charging stations (ECSs) in distribution power networks (DPNs) to achieve the best total active power loss (TAPL). Solar generators (SGs) are also used to alleviate the adverse effects resulting from the presence of ECSs in the networks in terms of power loss and voltage profile. Artificial hummingbird algorithm (AHA), Jellyfish swarm algorithms (JS), and Northern goshawk optimization (NGO) are executed to determine the best placement of ECSs and SGs in an IEEE 33-node network for reaching a minimum loss and satisfying all the related constraints. There are four cases conducted in the whole research. In the first case, JS outperforms both AHA and NGO by providing the highest stability throughout all the trial runs and fastest convergence speed to the optimal solution in the best runs. Besides, the quantitative comparison also consolidates the robustness and reliability of JS compared to others. Based on the surprising performance, JS is continuously reapplied to solve another three cases of the considered problem. Through those three cases with the application of JS, the TAPL values of four scenarios with different numbers of ECSs are evaluated. Specifically, the results achieved by JS indicate that the higher number of ECSs leads to a higher value of TAPL and a higher voltage drop. On the other hand, the simultaneous placement of SGs and ECSs can result in smaller fluctuations of the voltage profile and smaller TAPL. Thus, the optimization placement of ECSs and SGs is crucial to DPNs for economic and technical purposes.