Residential past and future energy consumption: Potential savings and environmental impact

In order to identify main drivers behind changes in electricity and fuel consumptions in the household sector in Jordan, two empirical models are developed based on multivariate linear regression analysis. In addition, this paper analyzes and evaluates impacts of introducing some efficient measures, such as high efficiency lightings and solar water heating systems, in the housing stock, on the future fuel and electricity demands and associated reduction in GHG emissions. It was found that fuel unit price, income level, and population are the most important variables that affect demand on electrical power, while population is the most important variable in the case of fuel consumption. Obtained results proved that the multivariate linear regression models can be used adequately to simulate residential electricity and fuel consumptions with very high coefficient of determination. Without employing most effective energy conservation measures, electricity and fuel demands are expected to rise by approximately 100% and 23%, respectively within 10 years time. Consequently, associated GHG emissions resulting from activities within the residential sector are predicted to rise by 59% for the same period. However, if recommended energy management measures are implemented on a gradual basis, electricity and fuel consumptions as well as GHG emissions are forecasted to increase at a lower rate.

[1]  Merih Aydinalp,et al.  Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks , 2004 .

[2]  Jamal O. Jaber,et al.  Electricity consumption and associated GHG emissions of the Jordanian industrial sector : Empirical analysis and future projection , 2008 .

[3]  Jesus Villalobos,et al.  Projected impact of industrial assessment center program recommendations on U.S. manufacturing energy consumption , 2005 .

[4]  Bilal Akash,et al.  Medium-range planning economics of future electrical-power generation options , 2004 .

[5]  Haji Hassan Masjuki,et al.  Potential CO2 reduction by implementing energy efficiency standard for room air conditioner in Malaysia , 2001 .

[6]  Kristin Aunan,et al.  Co-benefits of climate policy—lessons learned from a study in Shanxi, China , 2004 .

[7]  Yixiang Zhang,et al.  Determinants and policy implications for household electricity-saving behaviour: Evidence from Beijing, China , 2011 .

[8]  Haji Hassan Masjuki,et al.  Electricity savings from implementation of minimum energy efficiency standard for TVs in Malaysia , 2005 .

[9]  Jamal O. Jaber,et al.  Prospects of energy savings in residential space heating , 2002 .

[10]  Jamal O. Jaber,et al.  Evaluation of conventional and renewable energy sources for space heating in the household sector , 2008 .

[11]  Patrick E. Phelan,et al.  Forecasting the electricity consumption of the Mexican border states maquiladoras , 2004 .

[12]  Bilal Akash,et al.  Analysis of energy and exergy use in the Jordanian urban residential sector , 2008 .

[13]  Alan S. Fung,et al.  Modelling of residential energy consumption at the national level , 2003 .

[14]  Eric Hirst,et al.  Estimating energy savings due to conservation programmes: The BPA residential weatherization pilot programme , 1985 .

[15]  Steven C. Wheelwright,et al.  Forecasting methods and applications. , 1979 .

[16]  John A. Paravantis,et al.  Energy conservation in small enterprises , 2007 .

[17]  Aris Tsangrassoulis,et al.  On the energy consumption in residential buildings , 2002 .

[18]  Haji Hassan Masjuki,et al.  Projected electricity savings from implementing minimum energy efficiency standard for household refrigerators in Malaysia , 2003 .

[19]  Jamal O. Jaber Greenhouse gas emissions and barriers to implementation in the Jordanian energy sector , 2002 .

[20]  Arif Hepbasli,et al.  Residential-commercial energy input estimation based on genetic algorithm (GA) approaches: an application of Turkey , 2004 .

[21]  Ibrahim Dincer,et al.  Energy intensities for Canada , 1996 .

[22]  Yoav Benjamini,et al.  Modeling residential demand for natural gas as a function of the coldness of the month , 1978 .

[23]  Nepal. Rāshṭriya Yojanā Āyoga,et al.  National population strategy , 1983 .

[24]  Dieter M. Imboden,et al.  Long-term energy savings and greenhouse gas emission reductions in the Swiss residential sector , 2007 .

[25]  Merih Aydinalp,et al.  Modeling of the appliance, lighting, and space-cooling energy consumptions in the residential sector using neural networks , 2002 .

[26]  Wei Lu Potential energy savings and environmental impact by implementing energy efficiency standard for household refrigerators in China , 2006 .

[27]  M. Parti,et al.  The Total and Appliance-Specific Conditional Demand for Electricity in the Household Sector , 1980 .

[28]  Douglas C. Montgomery,et al.  Applied Statistics and Probability for Engineers, Third edition , 1994 .

[29]  Constantinos A. Balaras,et al.  Potential for energy conservation in apartment buildings , 2000 .

[30]  V. Ismet Ugursal,et al.  Impact of appliance efficiency and fuel substitution on residential end-use energy consumption in Canada , 1996 .

[31]  Bilal Akash,et al.  Energy saving and CO2 mitigation through restructuring Jordan's transportation sector: The diesel passenger cars scenario , 2007 .