Modeling Residential Electricity Consumption from Public Demographic Data for Sustainable Cities

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU144275" target="_blank" >RIV/00216305:26210/22:PU144275 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1996-1073/15/6/2163" target="_blank" >https://www.mdpi.com/1996-1073/15/6/2163</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/en15062163" target="_blank" >10.3390/en15062163</a>

Result language

angličtina

Original language name

Modeling Residential Electricity Consumption from Public Demographic Data for Sustainable Cities

Original language description

Demographic factors, statistical information, and technological innovation are prominent factors shaping energy transitions in the residential sector. Explaining these energy transitions re-quires combining insights from the disciplines investigating these factors. The existing literature is not consistent in identifying these factors, nor in proposing how they can be combined. In this paper, three contributions are made by combining the key demographic factors of households to estimate household energy consumption. Firstly, a mathematical formula is developed by considering the demographic determinants that influence energy consumption, such as the number of persons per household, median age, occupancy rate, households with children, and number of bedrooms per household. Secondly, a geographical position algorithm is proposed to identify the geographical locations of households. Thirdly, the derived formula is validated by collecting demographic factors of five statistical regions from local government databases, and then compared with the electricity consumption benchmarks provided by the energy regulators. The practical feasibility of the method is demonstrated by comparing the estimated energy consumption values with the electricity consumption benchmarks provided by energy regulators. The comparison results indicate that the error between the benchmark and estimated values for the five different regions is less than 8% (7.37%), proving the efficacy of this method in energy consumption estimation processes.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20704 - Energy and fuels

Project

<a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

ENERGIES

ISSN

1996-1073

e-ISSN

—

Volume of the periodical

6

Issue of the periodical within the volume

15

Country of publishing house

CH - SWITZERLAND

Number of pages

16

Pages from-to

2163-2163

UT code for WoS article

000775405200001

EID of the result in the Scopus database

2-s2.0-85127032348