Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system
Morais, L. B. S., Aquila, G., de Faria, V. A. D., Lima, L. M. M., Lima, J. W. M., & de Queiroz, A. R. (2023). Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system. Applied Energy, 348, 121439.
This work focuses on the development of shallow and deep neural networks in the form of multi-layer perceptron, long-short term memory, and gated recurrent unit to model the short-term load forecasting problem. Different model architectures are tested, and global climate model information is used as input to generate more accurate forecasts.