An Investigation into the Determinants of Residential Electricity Consumption in Makkah, Saudi Arabia with Particular Reference to the Occupant Behavioural Aspects
Date
2022-11-03
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Saudi Digital Library
Abstract
Saudi Arabia is the largest exporter of petroleum liquids and holds the largest production
capacity of crude oil in the world. However, the apparent development in the country has
increased the demand for the built environment, resulting in higher energy consumption and
environmental pollution. Saudi Arabia had the highest total electricity consumption in the GCC
countries in 2020, consuming 359 TWh. However, it had the second lowest electricity
consumption per capita at 10.31MWh per person. This is because Saudi Arabia has the largest
population compared to other GCC countries, and its electricity consumption is spread over a
large area. The statistics by ECRA show that residential buildings in Saudi Arabia consume
almost 50% of the total electricity sold while commercial, government, industrial, and others
account for 15%, 13%, 20%, and 4%, respectively. It has also been demonstrated that an energy
code and a standard implementation can significantly improve the energy efficiency of
buildings. However, the primary objective of this code is to encourage the construction of more
efficient buildings and energy supply systems. Theoretically, this approach may reduce the
overall energy consumption associated with building characteristics, which is a major objective
the government has been trying to accomplish. However, reducing electricity consumption in
dwellings is a very sophisticated concept that starts with the early design stages and continues
after the occupancy phase.
There is a growing demand for electricity on a national and international scale, even
though the quality of homes and HVAC systems is gradually improving. Occupant behaviour,
among other factors like building characteristics, household socioeconomic characteristics,
meteorological conditions, is observed to play an important role in residential electricity
consumption, which is usually neglected during the design stage. Therefore, this research aims
to investigate the influential factors of residential electricity consumption in Makkah, Saudi
Arabia, with a particular emphasis on the influence of occupant behavioural aspects.
Understanding the complexity of the abovementioned factors requires a research strategy that
draws from quantitative and qualitative techniques, including collecting public questionnaires,
electricity consumption records, meteorological data, and qualitative-related documents and
reports. Therefore, simple descriptive and advanced statistical analyses (e.g., one-way
ANOVA, independent-sample t-test, and correlation coefficients) were used in this research to
identify the relationship and differences between the variables and electricity consumption.
The findings suggest a statistically significant correlation between occupant behaviours,
such as the use of lighting, air conditioning, temperature control, presence patterns, and the
number and use of electrical appliances and electricity consumption. Concerning household
socioeconomic characteristics, family size, length of residency, household income, tenure,
electricity tariffs, respondent’s gender, age, and employment status, and the presence of
teenagers, housemaids, and drivers in the household were proved to be determining factors in
the use of electricity. In addition, there was a statistically significant correlation between
building attributes, such as dwelling type, floor area, the total number of rooms, bedrooms, and
bathrooms, and lighting and air conditioning type and electricity consumption. There was also
a statistically significant correlation between temperature, humidity, solar radiation, wind
speed, and CDD and electricity consumption.
Multiple linear regression (MLR) analyses were also used to determine the variability in
electricity consumption explained by occupant behaviours, building attributes, and household
socioeconomic characteristics. Since the study's samples were gathered in the same city,
meteorological conditions were not included in the MLR models. As a result of the first MLR
model (Model 1), occupant behaviour alone explained 47.9% (R² = 0.479) of the variance in
electricity consumption. The variation increased by 5.9% (R² = .538) with the addition of the
building attributes. The addition of household socioeconomic characteristics caused the
variation to increase by 7.7% (R² = .615). In the second MLR model (Model 2), while
controlling for building variables, 26.1% (R² = 0.261) of the variability in electricity
consumption for the first step (only building attributes), an increase of 27.7% (R² = .538) for
the second step (building attributes and occupant behaviour), and the variance increased by
7.7% (R² = .615) for the last step (building attributes, occupant behaviours, and household
socioeconomic characteristics). As a result, this study highlights that occupant behaviour is the
most significant determinant of residential electricity consumption, which could account for
30–50% of the variation in electricity use.
The study contributes to the body of knowledge within this field by providing a solid
foundation for developing more energy-efficient residential buildings in Saudi Arabia,
considering every possible influence on households' energy consumption, especially occupant
behaviour. In addition, since the study of occupant behaviour has been conducted for decades
in several countries like China, the United States, Canada, and Australia as well as many in
northern and western Europe, one of this study's objectives is to introduce this field in the
Kingdom of Saudi Arabia and to encourage the establishment of a set of investigations that
are specifically focused on Saudi Arabian culture considering local conditions, such as social,
technical, construction, and climatical conditions.
Description
Keywords
Residential electricity consumption, Occupant behaviour, Household socioeconomic characteristics, Building attributes, weather conditions