Domestic sector energy demand and prediction models for Punjab Pakistan

Awan, Usman and Knight, Ian ORCID: https://orcid.org/0000-0002-4871-4016 2020. Domestic sector energy demand and prediction models for Punjab Pakistan. Journal of Building Engineering 32 , 101790. 10.1016/j.jobe.2020.101790

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Abstract

The domestic sector consumes ~48% of Pakistan’s total energy demand, including biofuels. Pakistan is an emerging economy with 210 million people and growing domestic energy demand, facing economic, geographic, geopolitical, and climate change challenges. This paper presents novel insights into the Punjab, Pakistan domestic sector energy demand, which accounts for over 52% of the Pakistan population, along with energy prediction models derived from a statistically significant 4597 responses obtained from a physical questionnaire survey conducted in 2017-18, which aimed at ascertaining the main domestic energy demand drivers. These models will support future government and energy industry policy in this area, especially the transition to a low carbon economy. Currently, 67% of Pakistan’s energy demand is met with non-renewable resources. Analysis of the survey data reveals the key drivers of electrical energy demand per household are the number of appliances, number of lights, and the number of conditioned rooms. In the per capita models, the key drivers are the overall power rating of the appliances, particularly the power rating of the air conditioners for cooling. For annual gas use, weak correlations per household and capita were found only for the floor area. The average annual electricity and gas usages per household are 2401 kWh/a and 5245 kWh/a respectively, and per capita are 391 kWh/ a and 770 kWh/a. For electricity, the occupancy, floor area, conditioned rooms, appliances, lights and power rating have predictive power. For gas, only floor area is predictive.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Architecture
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Publisher:	Elsevier
ISSN:	2352-7102
Date of First Compliant Deposit:	30 September 2020
Date of Acceptance:	2 September 2020
Last Modified:	21 Nov 2024 16:30
URI:	https://orca.cardiff.ac.uk/id/eprint/135216

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