PINNs applied to power system state estimation on the IEEE 14-bus system claim up to 11% higher accuracy, 75% lower result variance, and 30% faster convergence than traditional iterative methods.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2023 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Physics-Informed Neural Networks for Accelerating Power System State Estimation
PINNs applied to power system state estimation on the IEEE 14-bus system claim up to 11% higher accuracy, 75% lower result variance, and 30% faster convergence than traditional iterative methods.