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.
Highlights
Since the beginning of the 20th century, the amount of global energy demand has increased constantly due to the effective growth in different technologies for various applications [1,2,3] and revolution in social urges
In order to proceed with this research, the annual energy consumption of residential segments located in countries belonging to the Euro area has been chosen to be inserted in auto regressive integrated moving average (ARIMA) model as an input
In order to proceed with the identification of the AR and MA orders of the ARIMA model, auto correlation function (ACF) and partial auto correlation function (PACF) graphs were illustrated (Figures 4 and 5)
Summary
Since the beginning of the 20th century, the amount of global energy demand has increased constantly due to the effective growth in different technologies for various applications [1,2,3] and revolution in social urges. Between 1996 and 2006, the residential segment was responsible for consuming the approximate 30% of the average of energy consumption globally. Due to the fact that the residential buildings share a large portion of energy consumption, it is crucial for any applied forecasting software on this segment to be highly contributed in order to achieve the objectives in regards with the energy policy [6]. In this study we aimed to predict the energy consumption in Euro area household sector using an auto regressive integrated moving average (ARIMA) model to be used for future energy supply planning activities. In order to proceed with this research, the annual energy consumption of residential segments located in countries belonging to the Euro area has been chosen to be inserted in ARIMA model as an input. After presenting a prior art, this study will present the details of the methodology applied and the predictions have been provided afterwards followed by a discussion on the results achieved
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