Influence of Human Based Factors on Small Neighbourhood vs. Household Energy Load Prediction Modelling

  • Pawel KobylinskiEmail author
  • Mariusz Wierzbowski
  • Cezary Biele
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 722)


The paper aims at reporting lessons learnt while addressing issues concerning modelling energy load prediction for (1) a real small neighbourhood (circa 70 households) and (2) real individual households. The results should be of concern to engineers designing energy balancing systems for small smart energy grids. The endeavour of modelling and implementing 24 h energy load profile prediction in 15 min resolution turned out successful at neighbourhood level. However, at individual household level the modelling encountered important obstacles of objective nature. The uncertainties introduced into energy load profiles by randomly timed human behaviour at a single level can (1) limit or (2) virtually preclude efficient energy load profile prediction. The paper differentiates between the first and the second possibilities by describing two types of stochastic components representing randomly timed human factor.


Electrical energy Smart grids Human factors Prediction Artificial neural networks 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Pawel Kobylinski
    • 1
    Email author
  • Mariusz Wierzbowski
    • 2
  • Cezary Biele
    • 1
  1. 1.Laboratory of Interactive TechnologiesNational Information Processing InstituteWarsawPoland
  2. 2.Faculty of ElectronicsMilitary University of TechnologyWarsawPoland

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