Medium, short and very short-term prognosis of load demand for the Greek Island of Tilos using artificial neural networks and human thermal comfort-discomfort biometeorological data

K. Moustris, K.A. Kavadias, D. Zafirakis and J.K. Kaldellis

Renewable Energy, 2020, vol. 147, issue P1, 100-109

Abstract: The objective of the present work is the medium, short and very short-term prognosis of load demand (LD) for the small-scale island of Tilos in Greece. For this purpose, Artificial Neural Network (ANNs) models were developed to forecast the LD of Tilos for different prediction horizons and time intervals, these covering the cases of 24 h ahead in hourly intervals (medium term prognosis), 2 h ahead in 10-min intervals (short term prognosis) and 10-min ahead in 1-min intervals (very short term prognosis). At the same time, stochastic/persistence autoregressive (AR) models were also developed and compared with the respective ANN models with regards to the LD prediction results obtained.

Keywords: Artificial neural networks; Load demand; Forecasting; Tilos; Greece (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:147:y:2020:i:p1:p:100-109

DOI: 10.1016/j.renene.2019.08.126

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