Power system transient stability assessment based on the multiple paralleled convolutional neural network and gated recurrent unit

Protection and Control of Modern Power Systems

Table 10 The parameter setting of MP CNN + GRU on the IEEE 145-bus system

CNN branch	Quantity/function
Time sequence dimension	34
Input feature dimension	1096
Convolution layer	5/ReLU
Convolution kernel size	7 × 7
Convolution kernel Quantity	128
Pooling layer	5
Pooling size	5 × 5
Pooling method	Max-pooling
Full connection layer units	128
Dropout rate	0.2

Full connection layer	Quantity/function
Layers	3/ReLU
Units on the first layer	128
Units on the second layer	64
Units on the last layer	1
Loss function	Improved FL
Optimizer	Adam
Initial learning rate	4 × 10^–3
The first decay rate (β₁)	0.8
The second decay rate (β₂)	0.5
Epsilon (ε)	2 × 10^–9
Total parameters of the model	36,284