Fast hotspot thermal network for grid optimization of large multi-machine reactive power boosting at ultra-high losses

This research presents a novel fast hotspot lumped-parameter thermal network to estimate the synchronous generator’s reactive power-boosting capabilities under ultra-high power losses for multi-machine control and grid optimization. A system-component approach employs a double-layer thermal network to overcome the high complexity of high-order models while maintaining accurate hotspot prediction. Despite increased uncertainty for the stator hotspot temperature, the model achieves a precision of 6 % for ultra-high losses with a computational time of 5.34 μs. Finally, a scaling thermal rule is proposed to approximate a thermal network for different synchronous generators and validate the model against 24-hour actual data. • Novel fast, accurate hotspot hydrogenerator model for grid and reactive power optimization. • Double-layer network predicts hotspots via Millman-Norton equivalents. • Validated with FEA/Monte Carlo at 275-508 • Thermal scaling rule developed for air-cooled hydrogenators.