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Prediction of Power Consumption for Small Power Region Using Indexing Approach and Neural Network

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6352))

Abstract

The problem of prediction of 24-hour ahead power consumption in a small power region is a very important practical problem in power engineering. The most characteristic feature of the small region is large diversity of power consumption in the succeeding hours of the day making the prediction problem very hard. On the other side the accurate forecast of the power need for each of 24 hours of the next day enables to achieve significant saving on power delivery. The paper proposes the novel neural based method of forecasting the power consumption, taking into account the trend of its change associated with the particular hour of the day, type of the day as well as season of the year

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© 2010 Springer-Verlag Berlin Heidelberg

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Siwek, K., Osowski, S., Swiderski, B., Mycka, L. (2010). Prediction of Power Consumption for Small Power Region Using Indexing Approach and Neural Network. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15819-3_8

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  • DOI: https://doi.org/10.1007/978-3-642-15819-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15818-6

  • Online ISBN: 978-3-642-15819-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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