Abstract

The increasing incorporation of renewable energy (RE) sources and the growing demand for effective energy storage technologies have become essential in the current energy landscape. One of the main challenges in today’s power networks is reducing power losses while improving grid stability and efficiency. A promising approach to address this challenge is the optimization of battery energy storage systems (BESS) using advanced computational techniques. This study presents an innovative approach to optimize the placement and sizing of BESS within transmission networks using the Integrated Immune Chaotic Squirrel Evolutionary Programming (IICSEP) technique. By combining elements from evolutionary programming (EP), artificial immune system (AIS), squirrel search algorithm (SSA), and chaotic sequences, IICSEP enhances the search process to achieve superior optimization results. Implementation of the proposed IICSEP on a reliability test model i.e. the IEEE 30-Bus Reliability Test System (RTS) exhibited its superiority over the standalone EP and SSA. The results demonstrate significant improvements in power loss reduction, with a more than 73% reduction observed in the IEEE 30-Bus RTS. These findings demonstrate the potential of IICSEP to offer an efficient solution for BESS integration into modern power grids, enhancing system reliability and paving the way for future RE integration.

Keywords

Battery energy storage systems (BESS), Power loss minimization, Integrated immune chaotic squirrel evolutionary programming (IICSEP), Transmission network optimization, Renewable energy integration.

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