Automating Power System Optimization and Analysis Through ETAPPy Integration

This paper introduces a novel algorithm developed using EtapPy to optimize power system settings, focusing on reducing short circuit currents and improving overall system efficiency. The study utilizes a modified IEEE 9-Bus microgrid system, incorporating renewable energy sources such as wind and solar energy. Unlike traditional approaches, this study pioneers a rare and innovative integration of Python with E TAP, unlocking the potential for significantly more autonomous features within ETAP's framework. As a proof of concept, the algorithm automates the adjustment of transformer settings in the modeled microgrid system, demonstrating its capability to streamline system optimization processes. The results validate that by enabling automated adjustments and analyzing their effects through short circuit studies, this method lays the groundwork for more comprehensive and complex automation in future power system optimization efforts.