Marcelo Elizondo

Physics-informed learning of proprietary inverter models for grid dynamic studies

This paper develops a novel physics-informed neural ordinary differential equations-based framework to emulate the proprietary dynamics of the inverters — essential for improved accuracy in grid dynamic simulations. In current industry practice, the original equipment manufacture...