Short-term load forecasting using an artificial neural network

Abstract

-Artificial Neural Network (ANN) Method is applied to forecast the short-term load for a large power system. The load has two distinct patterns: weekday and weekend-day patterns. The weekend-day pattern include Saturday, Sunday, and Monday loads. A nonlinear load model is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one or two hidden layers are tested with various combination of neurons, and results are compared in terms of forecasting error. The neural network, when grouped into different load patterns, gives good load forecast.

Pronósticos Demanda de Energía y Potencia a Corto Plazo. Caso de Estudio: Unidad de Control de Pronóstico Noroeste (Área Antioquia-Chocó)

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Regional load forecasting in Taiwan––applications of artificial neural networks

“…In recent years, much research has been conducted on the application of artificial intelligence techniques to load forecasting problems [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. However, the models that have received the most extensive attention are undoubtedly the ANNs, cited among the most powerful computational tools ever developed.…”

Integration of multi layer perceptron and design of experiments for forecasting household electricity consumption

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