Abstract
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.
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Kobylinski, P., Wierzbowski, M., Biele, C. (2018). Influence of Human Based Factors on Small Neighbourhood vs. Household Energy Load Prediction Modelling. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_22
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DOI: https://doi.org/10.1007/978-3-319-73888-8_22
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