Conference Papers Year : 2024

Classification Tree Based AI System for Short Term Prediction for Heat and Power Plants

Andrzej Sokołowski
  • Function : Author
  • PersonId : 1507815
Grzegorz Migut
  • Function : Author
  • PersonId : 1507816
Danuta Strahl
  • Function : Author
  • PersonId : 1507817

Abstract

Companies supplying electrical energy rely mainly on long term agreements with electricity producers, but on the other hand the actual demand should be precisely predicted for 48 h ahead, to take into account the actual weather conditions. The same type of analysis is important also for heat and power plants, but this time the temperature of returning water is the most interested. Some time series models can be used for forecasting. However in daily practice – more popular are average profiles showing the distribution over 24 h. We propose to build an AI system to choose the future profile. First – from the historical data – daily profiles are obtained, by cutting the time series into 24-h periods. Then, these empirical profiles are clustered with hierarchic and non-hierarchic clustering procedures to form homogeneous groups (types of profiles). Finally the classification methods are applied using weather data and observed demand from previous days (up to one week backwards). The measure for the forecasting evaluation has been proposed. Out of the two tested classification methods, CART classification tree performed better.
Embargoed file
Embargoed file
1 10 8
Year Month Jours
Avant la publication
Friday, January 1, 2027
Embargoed file
Friday, January 1, 2027
Please log in to request access to the document

Dates and versions

hal-04948683 , version 1 (14-02-2025)

Licence

Identifiers

Cite

Małgorzata Markowska, Andrzej Sokołowski, Grzegorz Migut, Danuta Strahl. Classification Tree Based AI System for Short Term Prediction for Heat and Power Plants. 10th IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KMES), Sep 2023, Krakow, Poland. pp.134-149, ⟨10.1007/978-3-031-61069-1_10⟩. ⟨hal-04948683⟩
0 View
0 Download

Altmetric

Share

More