An Auto Regressive Integrated Moving Average (ARIMA) Model for prediction of energy consumption by household sector in Euro area
authors Jahanshahi, A; Jahanianfard, D; Mostafaie, A; Kamali, M
nationality International
journal AIMS ENERGY
author keywords household energy consumption; R program; ARIMA; RMSE; forecasting
keywords EFFICIENCY; CHINA; FUEL
abstract Accurate estimation of the energy need and consumption is considered as one of the most important basis of the economy worldwide. It is also of high importance to mitigate the adverse effects of the release of CO2 (e. g., climate change) from conventional energy sources by using renewable energies, as recommended by European commission. Thus, in this study a forecast regarding the residential energy consumption of the household sector in countries belonging to the Euro area was executed. To proceed with this prediction, time related data from 1990 till 2015 along with Auto Regressive Integrated Moving Average (ARIMA) model were applied. ARIMA model was considered due to possessing the ability of providing accurate results while being able to receive stationary and non-stationary data. The obtained results from the analysis clarified that ARIMA (0,1,1) model is the most accurate model to undertake such prediction as the amount of RMSE achieved was 0.097. This comparison was accomplished by considering the ARIMA (0,1,0) and ARIMA (1,1,2) models as their amounts regarding RMSE were respectively 0.1068149 and 0.0975575. The results indicate that the amount of the energy predicted to be consumed in household sector in EU area is estimated to be 186244 toe (tonne of oil equivalent) which shows a drop in the energy consumption in Euro area probably due to the increase in the energy efficiency especially in recent years.
publisher AMER INST MATHEMATICAL SCIENCES-AIMS
issn 2333-8326
year published 2019
volume 7
issue 2
beginning page 151
ending page 164
digital object identifier (doi) 10.3934/energy.2019.2.151
web of science category Energy & Fuels
subject category Energy & Fuels
unique article identifier WOS:000467429600004
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