Neural Systems for Short-Term Forecasting of Electric Power Load

Authors:
Michał Bąk;Andrzej Bielecki
Affiliations:
Institute of Computer Science, Jagiellonian University, Nawojki 11, 30-072 Kraków, Poland;Institute of Computer Science, Jagiellonian University, Nawojki 11, 30-072 Kraków, Poland
Venue:
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Year:
2007

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Abstract

In this paper a neural system for daily forecasting of electric power load in Poland is presented. Basing on the simplest neural architecture - a multi-layer perceptron - more and more complex system is built step by step. A committee rule-aided hierarchical system consisting of modular ANNs is obtained as a result. The forecasting mean absolute percentage error (MAPE) of the most effective system is about 1.1%.