Households’ Electricity Consumption in Hungarian Urban Areas

Ferenc Bakó,Judit Berkes,Cecília Szigeti

doi:10.3390/en14102899

Abstract

The aim of this study is to examine the factors influencing the electricity consumption of urban households and to prove these with statistically significant results. The study includes 46 small and medium-sized towns in Hungary. The methodology of the study is mainly provided by a model that can be used for this purpose; however, the results obtained with the traditional regression method are compared with the results of another, more complex estimation method, the artificial neural network, which has the advantage of being able to use different types of models. The focus of our article is on methodological alignment, not necessarily the discovery of new results. Certain demographic characteristics significantly determine the energy demand of a household sector in a municipality. In this case, as the ratio of people aged 60 or over within a city rises by 1%, the urban household average energy consumption decreases by 61 kilowatt hours, and when it rises by 1%, the amount of pollutants expelled from urban households’ average energy consumption may decrease by 22.8745 kg. The research area of our paper was greatly influenced by the availability of the statistical data. The results can be used in the planning of urban developments.

Highlights

The perceptrons’ activation function contained a tangent function, and, since we aimed to discover how capable some of the methods are of estimating an urban household’s energy intensity, with knowledge of certain parameters, we deleted the energy consumption values of 16 cities from the previous regression model—defining them as a quasi-missing value
We will expand on all of this in more detail; the decreased item numbers still play an important role in the case of artificial neural networks
The results show that the artificial neural network gave more accurate results than the linear regression

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The relationship between energy consumption and economic growth is one of the most significant issues in environmental economics. The most significant problem related to energy consumption is the increase in CO2 emissions and its harmful effects. This issue can be examined at both the macro- and micro-levels. Indirect CO2 pollution from electricity consumption is neglected. This was a strong motivation for carrying out this research

Objectives

Results

Conclusion