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The Forecasting of the Daily Heat Demand of the Public Sector Buildings with District Heating

  • Yuliia Parfenenko
  • Vira ShendrykEmail author
  • Svitlana Vashchenko
  • Natalya Fedotova
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 538)

Abstract

This study is devoted to the increasing of the heat energy demand forecasting accuracy for district heating of the public sector buildings.

The authors have analyzed forecasting techniques used for the heat energy demand forecasting for buildings with district heating. The system model for description the forecasting process as a part of the information support of the heat energy management process in the public sector institution is proposed.

The mathematical model of the heat energy demand forecasting of a public sector building have been developed. It is based on the usage of the artificial neural networks technology. It takes into account both meteorological and social components of impact on the heat energy demand. The computational experiments that prove its accuracy have been carried out. The proposed models have been implemented in the forecasting subsystem of the information and analysis system «HeatCAM».

Keywords

Forecasting Heat energy demand Neural network Information system Energy management 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yuliia Parfenenko
    • 1
  • Vira Shendryk
    • 1
    Email author
  • Svitlana Vashchenko
    • 1
  • Natalya Fedotova
    • 1
  1. 1.Sumy State UniversitySumyUkraine

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