Publication detail

Forecasting Electricity Consumption in Czech Republic

UHER, V. BURGET, R. DUTTA, M. MLÝNEK, P.

Original Title

Forecasting Electricity Consumption in Czech Republic

Type

conference paper

Language

English

Original Abstract

Correct prediction of electricity consumption is important for planning its production in the short term, but also in the long term due to the construction of new power plants and mining planning. Accurate prediction is a challenging task because the consumption changes both in the day and during the whole year. The paper describes a method based only on input data for consumption. No additional influences were included such as temperature, wind, GDP (Gross Domestic Product). Five machine learning algorithms were used to create a predictive model. The best results were achieved with a local polynomial regression algorithm. Daily prediction error was 5.77%, weekly 3.49% and monthly 2.41%.

Keywords

Electricity consumption, forecast, machine learning, optimalization, prediction

Authors

UHER, V.; BURGET, R.; DUTTA, M.; MLÝNEK, P.

RIV year

2015

Released

9. 7. 2015

Location

Prague, Czech Republic

ISBN

978-1-4799-8497-8

Book

Proceedings of the 38th International Conference on Telecommunication and Signal Processing, TSP 2015

ISBN

NEUVEDENO

Pages from

262

Pages to

265

Pages count

4

URL

https://ieeexplore.ieee.org/document/7296264

BibTex

@inproceedings{BUT115494,
  author="Václav {Uher} and Radim {Burget} and Malay Kishore {Dutta} and Petr {Mlýnek}",
  title="Forecasting Electricity Consumption in Czech Republic",
  booktitle="Proceedings of the 38th International Conference on Telecommunication and Signal Processing, TSP 2015",
  year="2015",
  pages="262--265",
  address="Prague, Czech Republic",
  doi="10.1109/TSP.2015.7296264",
  isbn="978-1-4799-8497-8",
  url="https://ieeexplore.ieee.org/document/7296264"
}