Cascading Failure Analysis Based on a Physics-Informed Graph Neural Network
Yuhong Zhu, Yongzhi Zhou, Wei Wei, Ningbo Wang
Abstract
Power flow calculation in quasi-steady states is the basis of cascading failure analysis. However, in recent years, data-driven analysis methods that are based on sufficient data have put forward higher requirements on the speed of power flow calculation. To build a more accurate and efficient neural network for power flow calculation, a physics-informed graph neural network-based model is proposed for faster calculation. Via minimizing the physics-informed loss function and using a pre-training/fine-tuning method, the proposed model is trained to follow the physical equations directly and can generalize to dynamic power networks. Physics-informed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$LOSS$</tex-math></inline-formula> makes the proposed model more interpretable, since the calculation error can be evaluated by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$LOSS$</tex-math></inline-formula> . Then cascading failures are simulated with the proposed model, and a pre-set factor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\zeta$</tex-math></inline-formula> is introduced to balance the speed and accuracy of simulations. Finally, the accuracy of cascading failure simulations with the proposed model is verified in the IEEE 39-bus system, the 118-bus system, the 300-bus system, and a real-world French system. Experimental results show that compared with AC power flow, the proposed physics-informed graph neural network-based power flow model can reduce the simulation time significantly while maintaining high accuracy if <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\zeta$</tex-math></inline-formula> is properly pre-set.