Previsão de Carga de Curto Prazo para grandes áreas geográficas considerando ponderação por Região Meteorológica
Keywords: Short Term Load Forecasting, Multi Region Forecasting, Artificial Neural Network, Meteorological Station, Meteorological variables weighting
AbstractThis paper presents a short-term multiregional forecasting approach for macro-regions, with the main contribution being the proposal of an indicator that represents the Average Consumption per Meteorological Region (CERM), to be used as weighting of each EM as their importance for the total demand of the macro-region. In addition, the Variation of Load and Temperature index (IVCT) is proposed, based on the historical variation of temperature and demand This indicator is incorporated into a model of neural network of the Multi-layer perceptron type (MLP) for the load forecasting on the horizon of 7 days ahead with hourly and daily discretization. The results showed higher average performance of the variable IVCT in relation to the other combinations performed, and the best results were used to compose the prediction of the MTR. Finally, the proposed model presented a MAPE (Mean Absolute Percentage Error) lower than 1%, presenting superior performance compared to an basis aggregate model for MTR, which shows the efficiency of the proposed methodology.