Electricity consumption analysis based on Turkish Household Budget Surveys
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ORIGINAL ARTICLE
Electricity consumption analysis based on Turkish Household Budget Surveys M. Ozgur Kayalica1 Ayse Aylin Bayar3 1 2 3 4
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Avni Ozozen4
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Denizhan Guven2
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Gulgun Kayakutlu1
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Istanbul Technical University, Energy Institute, Istanbul, Turkey Istanbul Technical University, Eurasia Institute of Earth Sciences, Istanbul, Turkey Faculty of Management, Istanbul Technical University, Istanbul, Turkey EnerjiSA Energy Inc., Istanbul, Turkey
Received: 31 March 2020 / Revised: 9 September 2020 / Accepted: 10 September 2020 / Published online: 28 September 2020 The Joint Center on Global Change and Earth System Science of the University of Maryland and Beijing Normal University 2020
Abstract This study was designed to analyse the interaction of household surveys and electricity consumption in Turkey. We used the micro-data set of the Household Budget Survey published by TurkStat for the period 2002–2017. A statistical method and an optimisation method, namely Principal Component Analysis (PCA) and Analytical Hierarchical Processing (AHP), were used to explore the correlations between the components of the household surveys. The first 35 variables among 50 variables were extracted using PCA, and expert opinions validated 26 of 35 ranked using the AHP method. The Artificial Neural Networks (ANN) model, constructed using the input variables defined by expert opinions, gave better prediction results than the ANN model defined using the PCA outcome. ANN sensitivity analysis was conducted to examine the prediction for the components that were validated by AHP evaluations. The results show that dwelling characteristics had more impact on electricity utilisation than did ownership of appliances. It was also discovered that the amount of total expenditure had a negligible impact on electricity consumption. Keywords Household electricity consumption analysis AHP ANN Household Budget Survey
1 Introduction Before the first oil shock erupted in 1973, the energy sector focused on supply rather than demand, aiming to match a certain exogenous energy demand by arranging the supply. & M. Ozgur Kayalica [email protected]
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Following the first oil shock, policymakers paid attention to the energy sector because of the unexpected price increments. Since then, the energy sector has been investigated using energy demand analysis, as well as modelling studies which also take into account the demand side of the system (Bhattacharyya 2019). The energy sector contains different subsections, such as residential, commercial, industrial, and transport. Energy demand varies from subsection to subsection because of their different determinants and behavioural factors. Thus, macro-demand analysis may not represent these factors accurately. To solve this issue, disaggregated demand analysis is of vital importance. Within this context, total income level, population, size of dwellings, habits, and tastes of household members, as well as the efficiency of household devices, are the main determinants of residential energy
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