A study of appliance ownership and electricity consumption determinants in urban Ghanaian households

Abstract The residential sector in Ghana accounts for about 40% of aggregate electricity consumption out of which urban centers contribute 70%. The high weighted share of residential electricity use is attributed to high appliance ownership and use, and other household/building factors. The ability to determine how changes in the pattern of these factors influence electricity demand is critical if efforts to reduce consumption are to be effective. This study combines a residential electricity consumption survey (RECS) with electricity end-use monitoring of 60 households in Tema city Ghana, to yield the first ever comprehensive investigation of city-scale electricity consumption in urban Ghanaian homes. A multiple linear regression analysis is used to identify the most statistically significant indicators of appliance ownership and household electricity consumption. Results indicate that ownership of air conditioner, freezer, fan, refrigerator and television; and changes in socio-economic and building factors such as energy efficiency awareness and practice; income; household size and floor space show high statistical significance, and collectively explain 57% variance in households’ total electricity consumption. The presence of dependent children increases ownership of television, iron, washing machine and small kitchen appliances. This work provides a solid foundation for developing more tailored energy-saving policy interventions targeted at households.

[1]  Merve Bedir,et al.  Determinants of electricity consumption in Dutch dwellings , 2013 .

[2]  Yongqiang Zhu,et al.  Distributed generation and Demand Side Management , 2010, CICED 2010 Proceedings.

[3]  Kenichi Hasegawa,et al.  Relationship between possession of electric appliances and electricity for lighting and others in Japanese households , 2005 .

[4]  F. Teng,et al.  Estimation of urban residential electricity demand in China using household survey data , 2013 .

[5]  Yoshikuni Yoshida,et al.  A new method for household energy use modeling: A questionnaire-based approach , 2018 .

[6]  Jeyhun I. Mikayilov,et al.  The impact of age groups on consumption of residential electricity in Azerbaijan , 2017 .

[7]  Mark Howells,et al.  Determinants of electricity demand for newly electrified low-income African households , 2008 .

[8]  Jorge Alberto Rosas-Flores,et al.  Saturation, energy consumption, CO2 emission and energy efficiency from urban and rural households appliances in Mexico , 2011 .

[9]  Wilfried Elmenreich,et al.  Residential demand response scheme based on adaptive consumption level pricing , 2016 .

[10]  Neil Brown,et al.  Information, communication and entertainment appliance use—Insights from a UK household study , 2012 .

[11]  Rolf Katzenbach,et al.  Towards a sustainable electrification in Ghana: A review of renewable energy deployment policies , 2017 .

[12]  Sean Lyons,et al.  Energy use and appliance ownership in Ireland , 2010 .

[13]  I. Vassileva,et al.  Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception , 2011 .

[14]  R. Rajagopal,et al.  Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior , 2013 .

[15]  Catia Cialani,et al.  Household and industrial electricity demand in Europe , 2018, Energy Policy.

[16]  Jukka Paatero,et al.  A model for generating household electricity load profiles , 2006 .

[17]  Tian Sheng Allan Loi,et al.  Analysing households’ responsiveness towards socio-economic determinants of residential electricity consumption in Singapore , 2018 .

[18]  Kevin J. Lomas,et al.  Determinants of high electrical energy demand in UK homes: Socio-economic and dwelling characteristics , 2015 .

[19]  Ryoko Nakano,et al.  Determinants of energy savings in Indonesia: The case of LED lighting in Bogor , 2018, Sustainable Cities and Society.

[20]  J. Macías,et al.  Assessment of electrical saving from energy efficiency programs in the residential sector in Mexicali, Mexico , 2018 .

[21]  Robert Van Buskirk,et al.  Refrigerator Efficiency in Ghana: Tailoring an appliance market transformation program design for Africa , 2007 .

[22]  D. O’Hora,et al.  Nudging electricity consumption using TOU pricing and feedback: evidence from Irish households , 2017 .

[23]  I. Azevedo,et al.  Residential electricity consumption in Portugal: Findings from top-down and bottom-up models , 2011 .

[24]  Michael A. McNeil,et al.  Modeling diffusion of electrical appliances in the residential sector , 2010 .

[25]  Anthony Amoah,et al.  Energy demand in Ghana: A disaggregated analysis , 2016 .

[26]  Policy framework on energy access and key development indicators: ECOWAS interventions and the case of Ghana , 2016 .

[27]  I. Ahemen,et al.  A survey of power supply and lighting patterns in North Central Nigeria-The energy saving potentials through efficient lighting systems , 2016 .

[28]  Energy efficiency deployment: A pathway to sustainable electrification in Ghana , 2018 .

[29]  Barbara Schlomann,et al.  Characterization of the household electricity consumption in the EU, potential energy savings and sp , 2011 .

[30]  H Lee Willis,et al.  Spatial electric load forecasting , 1996 .

[31]  Detlef P. van Vuuren,et al.  Model projections for household energy use in developing countries , 2012 .

[32]  R. Tol,et al.  Energy-using appliances and energy-saving features: Determinants of ownership in Ireland , 2008 .

[33]  B. Dong,et al.  A survey on energy consumption and energy usage behavior of households and residential building in urban China , 2017 .

[34]  Rory V. Jones,et al.  The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings , 2015 .

[35]  Matthew Leach,et al.  Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider , 2016 .

[36]  Yumiko Iwafune,et al.  High-resolution determinant analysis of Japanese residential electricity consumption using home energy management system data , 2016 .

[37]  S. Gyamfi,et al.  The energy efficiency situation in Ghana , 2018 .

[38]  H. Scott Matthews,et al.  One size does not fit all: Averaged data on household electricity is inadequate for residential energy policy and decisions , 2013 .

[39]  Emmanuel K. Boon,et al.  Energy delivery and utilization for rural development: Lessons from Northern Ghana , 2009 .

[40]  Carlos Alberto Discoli,et al.  Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption at the Great La Plata region, Buenos Aires, Argentina , 2017 .

[41]  P. Kwakwa.  ENERGY-GROWTH NEXUS AND ENERGY DEMAND IN GHANA: A REVIEW OF EMPIRICAL STUDIES , 2014 .

[42]  Basab Chakraborty,et al.  Demand side management in developing nations: A mitigating tool for energy imbalance and peak load management , 2016 .

[44]  B. Behera,et al.  A ladder within a ladder: Understanding the factors influencing a household's domestic use of electricity in four African countries , 2017 .

[45]  S. M. Hakimi.  Multivariate stochastic modeling of washing machine loads profile in Iran , 2016 .

[46]  Keith Baker,et al.  Improving the prediction of UK domestic energy-demand using annual consumption-data , 2008 .

[47]  S. Gyamfi,et al.  Improving electricity supply security in Ghana—The potential of renewable energy , 2015 .

[48]  Shigeru Matsumoto,et al.  How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data , 2016 .

[49]  Rory V. Jones,et al.  Determinants of high electrical energy demand in UK homes: Appliance ownership and use , 2016 .

[50]  Michael Conlon,et al.  Characterising domestic electricity consumption patterns by dwelling and occupant socio-economic variables: An Irish case study , 2012 .

[51]  Stefan Feuerriegel,et al.  Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications , 2016 .

[52]  H. Yoshino,et al.  Analysis on urban residential energy consumption of Hot Summer & Cold Winter Zone in China , 2013 .

[53]  T. Sanquist,et al.  Lifestyle factors in U.S. residential electricity consumption , 2012 .

[54]  V. Ismet Ugursal,et al.  Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector , 2008 .

[55]  Trevor Pryor,et al.  Identifying the determinants of residential electricity consumption for social housing in Perth, Western Australia , 2016 .

[56]  Iain MacGill,et al.  Statistical analysis of drivers of residential peak electricity demand , 2017 .

[57]  Y. Shimoda,et al.  Residential end-use energy simulation at city scale , 2004 .

[58]  K. Sreekanth,et al.  A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs , 2017 .

[59]  Mohammad Reza Mohammadi,et al.  Modeling the electrical energy consumption profile for residential buildings in Iran , 2018 .

[60]  R. Belmans,et al.  Impact of residential demand response on power system operation: A Belgian case study , 2014 .

[61]  Min-Jeong Kim.  RETRACTED: Characteristics and determinants by electricity consumption level of households in Korea , 2018, Energy Reports.