Abstract

The domestic sector uses the majority of the energy consumed in Palestine. The Palestinian Central
Bureau of statistics (PCBS) performs periodic statistics regarding the average energy consumption of the
households, but there is no up to date breakdown of the energy consumption in the residential sector.
The Palestinian energy sector main challenges are the high fuel prices, lack of sustainable consumption
and energy insecurity. Developing energy policies and studying the potential of shifting towards more
independent and sustainable energy sources need a clear understanding of the current energy consumption.
A survey was used to collect relevant quantitative and qualitative data. The total number of
households in Hebron who responded to the survey was 322 households. The survey covered physical
characteristics of the dwellings, socioeconomic features of the households in addition to the pattern of
heating the spaces, quantity and type of fuel used for heating. On average the households heated only
9.2% of the total area of their houses during the winter days. The survey revealed that households spend
3.5%e21.6% of their monthly income on space heating during winter. The main contribution to knowledge
of this paper is a regression model to estimate energy consumption based on the data collected
from the survey. The regression model is developed with an R2 adjusted 0.606 indicating 60.6% accuracy
of the predicted energy consumed for heating. The regression model depends on 14 parameters which
include the type of settlement, physical characteristics of the dwelling that are housing typology, level of
thermal insulation of the walls, the main building materials and the housing age. It also depends on
socioeconomic parameters which are the family monthly income and the occupancy period. Moreover,
the type of the heating system used, the number of heated months and the nominal heated area were
influential parameters in this model. The significance of this paper stems from the methodology that
propose an alternative to the energy audit and simulation methods. The proposed method can be used in
contexts where a combination of energy resources is used with no proper metering system and with the
absence of accurate data that is needed for simulation.