Load flow studies using artificial neural networks

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Nani Janga
Nani Janga el 18 de Feb. de 2020
Comentada: Prasanna el 6 de Dic. de 2024
I need MATLAB code to train neural networks to solve load flow problems
  4 comentarios
Arman Ali
Arman Ali el 2 de Abr. de 2023
Please send here as well thank you arman.ncepu@gmail.com
Prasanna
Prasanna el 6 de Dic. de 2024
Hi Nani,
To train neural networks for load flow problems, refer the following steps:
  • Collect historical load flow data, including bus voltages, power injections and line flows.
  • For Data generation, use a conventional load flow solver (e.g., Newton-Raphson or Gauss-Seidel) to simulate various scenarios under different load and generation conditions. Ensure that the dataset covers various operating conditions and scenarios.
  • Perform data preprocessing, normalizing and split the data into training and validation sets.
  • Choose a feedforward neural network for function approximation. Define the number of layers and neurons in each layer. For example, use one input layer, one or more hidden layers, and one output layer.
  • Format the input and output data to match the neural network requirements. Ensure the input matrix dimensions are consistent with the network's input layer.
  • Use the ‘train’ function to train the network with the prepared data. Monitor the training process using performance metrics like mean squared error (MSE).

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