Integrated immune chaotic evolutionary programming (IICEP) optimizer tool for integrating battery energy storage systems in transmission network for loss minimization

Demand for renewable energy resources has increased in today’s energy landscape, seeking technological solutions to improve power systems' flexibility and stability. Transmission networks are critical components for delivering electricity in an efficient and reliable manner. However, the networks are susceptible to power losses, which lower overall system efficiency and increase operational costs. The development of a new novel optimization technique called Integrated Immune Chaotic Evolutionary Programming (IICEP) has successfully meet its objective to minimize loss by finding the optimal position and sizing of BESS within the transmission network. IICEP combined the benefits of Evolutionary Programming (EP) and clonal qualities of Artificial Immune System (AIS) with the addition of a chaotic process to provide a superior solution in optimization techniques. Three battery energy storages are inserted into the networks, each with the proper placement and sizes to achieve the purpose. The IICEP algorithm is tested on an IEEE 30-Bus RTS to determine its efficacy. The findings are compared to standard EP and AIS. It demonstrates that the IICEP technique offers a better performance in lowering power losses. This optimization technique can aid networks system strategy. When power losses are eliminated, proper network planning can lower operational cost and improve energy efficiency.