Autor:
Siwek, Krzysztof ; Osowski, Stanisław ; Szupiluk, Ryszard
Współtwórca:
Tytuł:
Ensemble neural network approach for accurate load forecasting in a power system
Tytuł publikacji grupowej:
Temat i słowa kluczowe:
neural networks ; blind source separation ; ensemble of predictors ; load forecasting
Abstract:
The paper presents an improved method for 1?24 hours load forecasting in the power system, integrating and combining different neural forecasting results by an ensemble system. We will integrate the results of partial predictions made by three solutions, out of which one relies on a multilayer perceptron and two others on self-organizing networks of the competitive type. As the expert system we will apply different integration methods: simple averaging, SVD based weighted averaging, principal component analysis and blind source separation. ; The results of numerical experiments, concerning forecasting the hourly load for the next 24 hours of the Polish power system, will be presented and discussed. We will compare the performance of different ensemble methods on the basis of the mean absolute percentage error, mean squared error and maximum percentage error. They show a significant improvement of the proposed ensemble method in comparison to the individual results of prediction. The comparison of our work with the results of other papers for the same data proves the superiority of our approach.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Data wydania:
Typ zasobu:
DOI:
Strony:
Źródło:
AMCS, volume 19, number 2 (2009) ; kliknij tutaj, żeby przejść