Under the double-carbon goal, the construction of a new power system with new energy as the main body is the main direction and key way to realize the transformation and upgrading of the power industry. The research on fast and accurate transient power angle stability evaluation under the background of new power systems is of great significance. To this end, the paper proposes a new transient power angle stability evaluation method for power systems with grid-forming new energy based on the physics-informed sequence-to-sequence neural networks (PI-seq2seq) and cascaded convolutional neural networks model. First, the PI-seq2seq network
structure is used to predict the future power angle trajectory, and the loss function with physical
loss terms is constructed to guide the model training process, which avoids the impact of
time-domain simulation taking too long on fast transient evaluation. Secondly, the cascade
convolutional neural networks use the predicted power angle trajectory as input to evaluate the
transient stability and its confidence level, and configure the evaluation confidence level threshold
judgment mechanism to realize the transient stability judgment of the non-fixed evaluation length,
which overcomes the influence of the fixed power angle curve length on the evaluation results.
Finally, it is verified in the Kundur system, and the simulation results show that the method
proposed has obtained satisfactory results in both the power angle curve prediction and the
stability evaluation method.
