Integrated Immune Chaotic Evolutionary Programming (IICEP) for Integrating Battery Energy Storage System in Transmission Network

Energy consumption has experienced significant growth on a global scale in the past decade. This has caused the growing demand of renewable energy resources into grid systems which has led to the need for technological solutions that can improve the stability of power systems. Electrical transmission network is an essential component for effectively and reliably transporting electricity. However, they are prone to power losses, which reduce overall system efficiency and raise operational expenses. Any remedial action to include compensating devices into the current system will require optimal sizing and sizing so as to avoid any over-compensation or under-compensation phenomena. This research investigates an approach of mitigating these losses by incorporating Battery Energy Storage Systems (BESS) into the transmission network. BESS is known to be a promising technology, providing several advantages such as peak shaving, load leveling, and improved grid stability. The purpose of this study is to find the optimal location and sizing of battery energy to minimize loss dissipated by the system using a newly proposed technique termed Integrated Immune Chaotic Evolutionary Programming (IICEP). IICEP is proposed to integrate BESS into the transmission network with a focus on loss minimization. IICEP integrates the operators of clonal features of Artificial Immune System (AIS) with the addition of a chaotic element into the original Evolutionary Programming (EP). It offers a better solution in optimization performance. Three battery energy storages are integrated into the network, each with the placement and sizing to meet the goal. The algorithm of IICEP is tested on IEEE 30- Bus RTS to observe its effectiveness. The results are compared with the traditional EP and AIS, resulting in a lower optimal solution of power losses.