By incorporating energy storage systems (ESSs), a distribution network's energy efficiency can be increased. These technologies can considerably improve the network's overall performance if they are placed and sized properly. A well-sized and well-positioned energy storage system can help manage power quality, optimize the choice of distributed and renewable energy sources, efficiently handle peak energy demand, and lower the costs related to growing distribution networks. In order to find out the ideal location and size of ESSs in a distribution network, this paper suggests a practical method that makes use of the Dandelion Optimizer (DO). Reducing the system's total yearly cost—which accounts for costs connected to power outages, voltage variations, and peak load—is the aim. The IEEE 33 bus radial system is used to implement the study's methods. The results from the original system and the suggested DO are compared to show how the position of the ESS affects the voltage profile and total cost. In addition, a comparison is presented between the results of the Ant Lion Optimizer (ALO), the Whale Optimization Algorithm (WOA) and the planned Design of Dandelion Optimizer (DO), indicating that the DO has achieved more savings than the other Algorithms. Findings indicate that the (DO) method delivers a net cost reduction of 7% and 1.7% compared to the WOA and ALO methods respectively, while also improving the voltage profile. The minimum bus voltage increased by 0.277% in the case of WOA and by 4.27% in the case of ALO while applying the DO increased this voltage by 6.6% with respect to the original system. The locations and sizes of the acquired ESSs are advantageous for system implementation due to the ease of use and effectiveness of the recommended methodology in resolving the optimization problem that was explored.
 
Special Issue of AEIC 2024 (Electrical and System & Computer Engineering  Session)