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Tytuł pozycji:

Assessing households’ gas and electricity consumption: a case study of Djelfa, Algeria

Tytuł:
Assessing households’ gas and electricity consumption: a case study of Djelfa, Algeria
Autorzy:
Boukarta, Soufiane
Berezowska-Azzag, Ewa
Tematy:
Algeria
gas consumption
electricity consumption
household characteristics
housing characteristics
density
statistical approach
GIS
Data publikacji:
2018-12-30
Wydawca:
Uniwersytet im. Adama Mickiewicza w Poznaniu
Język:
angielski
Prawa:
CC BY-NC-ND: Creative Commons Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 4.0
Źródło:
Quaestiones Geographicae; 2018, 37, 4; 111-129
0137-477X
2081-6383
Dostawca treści:
Biblioteka Nauki
Artykuł
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Households are the major energy consumer and contributor to the emission of greenhouse gases. The Algerian policy of mastering energy has improved building energy efficiency since 1994 by introducing thermal regulation (DTR). However, energy consumption is still increasing instead of decreasing, which is mainly due to occupants’ behaviour which is difficult to estimate and predict. This paper explores the impact of households and housing characteristics on residential gas and electricity consumption in the 36 municipalities of the department of Djelfa (Algeria) which is located in an arid and semi-arid climate zone. This paper is based on GIS and statistical techniques. It considers the yearly gas and electricity energy consumption (2013) of the municipalities of the department of Djelfa. The method is organised in four steps: (a) a multiple linear regression is used to construct two estimative models of gas and electricity. The models have more than 93% of accuracy for both gas and electricity models; (b) estimating gas and electricity consumption for 2008 according to the developed models; (c) organisation of the census data of 2008 in five dimensions: the population distribution, household characteristics, housing type and occupancy, and finally household appliance ownership; (d) a set of sensitivity analysis is performed based on Principal Component Analysis (PCA) and Pearson’s bivariate correlation and finally a path analysis is performed based on Structural Equation Model (SEM) to assess the importance of each variable. The overall impact of all these variables indicates that increasing the household size is the first factor reducing the electricity and gas consumption followed by the housing surface, density, room occupancy, and older households, while increasing the education level and appliance ownership boosts both per-capita gas and electricity consumption.

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