Keywords
Electrical load usage
Household characteristics
Middle-income households
Energy consumption patterns
How to Cite
Abstract
Electricity is the foundation of modern society, powering a vast array of daily activities and technological advancements. Despite increased electricity access, the majority of Sub-Saharan African countries face the dilemma of energy consumption outpacing generation. Gaining a good grasp of behavioral drivers of energy use, especially among middle-income households (MIHs), is necessary to reduce energy consumption. This study assesses the electricity consumption from MIHs in a targeted area of Masaki, Dar es Salaam region, Tanzania. The study integrated the household characteristics and electrical load consumption patterns in the electricity consumption of MIHs. The 1-month data, between May 2024 and June 2024, were gathered from 99 respondents using an e-questionnaire. The household characteristics included the number of occupants per household, awareness of energy management programs, adoption rate, and interested features and expectations in energy management programs. The electrical load consumption patterns include types of electrical loads, hourly usage, average monthly bills, and fluctuations in monthly energy bills. Findings revealed that the average number of occupants per household was 6, but only two out of 6 occupants per household were aware of energy management programs. Appliance control was the most adopted energy management program (44.12%) followed by real-time energy monitoring (11.76%) and integration with renewable energy sources (8.82%). Contrary, about 96% of respondents were interested in engaging in energy management initiatives aiming at cost-saving (62%) and convenience (20.7%). Evening hours reported to use the most energy (68.7%), followed by night hours (50.5%). The average monthly energy bills were found to range between TZS 70,000 and TZS 300,000 with 48.5% of respondents reporting large swings in their electricity expenses. The findings of this study provide policymakers with evidence that awareness initiatives should be included when formulating energy consumption and efficiency strategies.
References
Gerutu GB, Laoonual Y. Comparison study of cascaded organic rankine cycles with single and dual working fluids for waste heat recovery. J Adv Therm Sci Res. 2024; 11: 1-21. https://doi.org/10.15377/2409-5826.2024.11.1
White MT, Read MG, Sayma AI. Making the case for cascaded organic Rankine cycles for waste-heat recovery. Energy. 2020; 211: 118912. https://doi.org/10.1016/j.energy.2020. 118912
Hu K, Zhang Y, Yang W, Liu Z, Sun H, Sun Z. Energy, exergy, and economic (3E) analysis of transcritical carbon dioxide refrigeration system based on ORC system. Energies. 2023; 16(4): 1675. https://doi.org/10.3390/en16041675
Zare V. A comparative exergoeconomic analysis of different ORC configurations for binary geothermal power plants. Energy Convers Manag. 2015; 105: 127-38. https://doi.org/10 .1016/j.enconman.2015.07.073
Marcello S. On the exergoeconomic assessment of employing Kalina cycle for GT-MHR waste heat utilization. Energy Convers Manag. 2015; 90: 364-74. https://doi.org/10.1016/ j.enconman.2014.11.039
Huang W. Analysis on the changes of household electricity consumption over the past three decades. Mod Econ. 2019; 10: 1487-1506. https://doi.org/10.4236/me.2019.105099
Gerutu GB, Kivugo RO, Lujaji F, Chombo PV. Thermo-economic performance of organic rankine cycle-based waste heat recovery for power generation at a wide range of operating conditions. Glob J Energy Technol Res Updat. 2023; 10: 1-23. https://doi.org/10.15377/2409-5818.2023.10.1
Basta G, Meloni N, Poli F, Talluri L, Manfrida G. Energy, exergy and exergo-economic analysis of an OTEC power plant utilizing kalina cycle. Glob J Energy Technol Res Updat. 2021; 8: 1-18. https://doi.org/10.15377/2409-5818.2021.08.1
World Bank Group. Population total. Available from: https://data.worldbank.org/indicator/SP.POP.T OTL
Statista. Net electricity consumption worldwide in select years from 1980 to 2022. https://www.statista.com/statistics/280704/world-power-consumption/ (Accessed on September 1, 2024).
UNEP. Not yet built for purpose: Global building sector emissions still high and rising. https://www.unep.org/news-and-stories/press-release/not-yet-built-purpose-global-building-sector-emissions-still-high#:~:text=The%20report%20finds%20that%20in,a%20third%20of %20global%20demand (Accessed on September 1, 2024).
Santamouris M, Vasilakopoulou K. Present and future energy consumption of buildings: Challenges and opportunities towards decarbonisation. e-Prime - Adv Electr Eng Electron. 2021; 1: 100002. https://doi.org/10.1016/j.prime.2021.100002 (Accessed on September 1, 2024).
González-Torres M, Pérez-Lombard L, Coronel JF, Maestre IR, Yan D. A review on buildings energy information: Trends, end-uses, fuels and drivers. Energy Rep. 2022; 8: 626-37. https://doi.org/10.1016/j.egyr.2021.11.280
Berardi U. A cross-country comparison of the building energy consumptions and their trends. Res Conserv Recyc. 2017; 123: 230-41. https://doi.org/10.1016/j.resconrec.2016.03.014
Fokaides PA, Polycarpou K, Kalogirou S. The impact of the implementation of the European Energy Performance of Buildings Directive on the European building stock: The case of the Cyprus Land Development Corporation. Energy Pol. 2017; 111: 1-8. https://doi.org/10.1016/j.enpol.2017.09.009
Kalua A, Urban residential building energy consumption by end-use in Malawi. Buildings. 2020; 10(2): 31. https://doi.org/10.3390/buildings10020031
Umbark MA, Alghoul SK, Dekam EI. Energy consumption in residential buildings: Comparison between three different building styles. Sust Dev Res. 2020; 2(1): 1-8. https://doi.org/10.30560/sdr.v2n1p1
Alghoul S, Agha K, Zgalei A, Dekam E. Energy saving measures of residential buildings in North Africa. Rev Gap Analy. 2018; 7: 2018.
Tawil I, Abeid M, Abraheem E, Alghoul S, Dekam E. Review on solar space heating-cooling in Libyan residential buildings. Solar Energy Sust Dev J. 2018; 7: 78-112. https://doi.org/10.51646/jsesd.v7iSI.76
Energy Efficiency and Renewable Energy. Energy Data Facts, https://rpsc.energy.gov/energy -data-facts#:~:text=How%20much%20energy%20does%20the,of%20total%20U.S.%20ener gy%20consumption (Accessed on September 1, 2024).
Sustainable Energy Authority of Ireland (SEAI). Energy in Ireland 2023 Report. https://www.seai.ie/publications/Energy-in-Ireland-2023.pdf (Accessed on September 1, 2024).
IEA. Japan. https://www.iea.org/countries/japan/energy-mix (Accessed on September 1, 2024).
IEA. Germany. https://www.iea.org/countries/germany/efficiency-demand (Accessed on September 1, 2024).
Esmaeilimoakher P, Urmee T, Pryor T, Baverstock G. Identifying the determinants of residential electricity consumption for social housing in Perth, Western Australia. Energy Build. 2016; 133: 403-13. https://doi.org/10.1016/j.enbuild.2016.09.063
Al-Jbour A, Abutayeh H, Qawasmeh BR. An assessment tool for energy audit of buildings in Jordan using simulation. Glob J Energy Technol Res Updat. 2024; 11: 1-51. https://doi.org/10.15377/2409-5818.2024.11.1
Hakawati B, Mousa A, Draidi F. Smart energy management in residential buildings: the impact of knowledge and behavior. Sci Rep. 2024; 14: 1702. https://doi.org/10.1038/s41598-024-51638-y
Sakah M, de la Rue du Can S, Diawuo FA, Sedzro MD, Kuhn C. A study of appliance ownership and electricity consumption determinants in urban Ghanaian households. Sust Cities Soc. 2019; 44: 559-81. https://doi.org/10.1016/j.scs.2018.10.019
Hu T, Yoshino H, Jiang Z. Analysis on urban residential energy consumption of hot summer & cold winter zone in China. Sustain Cities Soc. 2013; 6: 85-91.
Farahbakhsh H, Ugursal V, Fung A. A residential end-use energy consumption model for Canada. Int J Energy Res. 1998; 22: 1133-43. https://doi.org/10.1002/(SICI)1099-114X(19981025)22:13<1133::AID-ER434>3.0.CO;2-E
Wan K, Yik F. Building design and energy end-use characteristics of high-rise residential buildings in Hong Kong. Appl Energy. 2004; 78: 19-36. https://doi.org/10.1016/S0306-2619(03)00103-X
Shimoda Y, Fujii T, Morikawa T, Mizuno M. Residential end-use energy simulation at city scale. Build Environ. 2004; 39: 959-67. https://doi.org/10.1016/j.buildenv.2004.01.020
Adelekan IO, Jerome AT. Dynamics of household energy consumption in a traditional African city, Ibadan. Environmentalist. 2006; 26: 99-110. https://doi.org/10.1007/s10669-006-7480-2
Haider S, Zafar S, Jindal A, Socioeconomic drivers of residential electricity expenditures in India. Utilities Pol. 2024; 88: 101735. https://doi.org/10.1016/j.jup.2024.101735
Bridge BA, Adhikari D, Fontenla M. Electricity, income, and quality of life. Soc Sci J. 2016; 53(1): 33-9. https://doi.org/10.1016/j.soscij.2014.12.009
Amirifard M, Sinton RA, Kurtz S. How demand-side management can shape electricity generation capacity planning. Utilities Pol. 2024; 88: 101748. https://doi.org/10.1016/j.jup.2024.101748
Romero-Jordán D, del Río P. Analysing the drivers of the efficiency of households in electricity consumption. Energy Pol. 2022; 164: 112828. https://doi.org/10.1016/j.enpol.2022.112828
Shabur MA, Ali MF. An analysis of the correlation between income and the consumption of energy in Bangladesh. Energy Inform. 2024; 7: 17. https://doi.org/10.1186/s42162-024-00321-7
Francisco ER, Aranha F, Zambaldi F, Goldszmidt R. Electricity Consumption as a Predictor of Household Income: a Spatial Statistics Approach. Conference: VIII Brazilian Symposium on Geoinformatics, 19-22 November, Campos do Jordão, São Paulo, Brazil: 2005, p. 175-92.
Ali SSS, Razman MR, Awang A, Asyraf MRM, Ishak MR, Ilyas RA, et al. Critical Determinants of Household Electricity Consumption in a Rapidly Growing City. Sustainability. 2021; 13: 4441. https://doi.org/10.3390/su13084441
Wijaya ME, Tezuka T. A Comparative study of households’ electricity consumption characteristics in indonesia: a techno-socioeconomic analysis. Energy Sust Dev. 2013; 17: 596-604. https://doi.org/10.1016/j.esd.2013.09.004
Kim MJ. Characteristics and determinants by electricity consumption level of households in Korea. Energy Rep. 2018; 4: 70-6. https://doi.org/10.1016/j.egyr.2017.12.001
Jones RV, Fuertes A, Lomas KJ. The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings. Renew Sust Energy Rev. 2015; 43: 901-17. https://doi.org/10.1016/j.rser.2014.11.084
Anderson B, Lin S, Newing A, Bahaj A, James P. Electricity consumption and household characteristics: implications for census-taking in a smart metered future. Computers Env Urb Syst. 2017; 63: 58-67. https://doi.org/10.1016/j.compenvurbsys.2016.06.003
Cayla JM, Maizi, N, Marchand C. The role of income in energy consumption behavior: evidence from French households Data. Energy Pol. 2011; 39: 7874-83. https://doi. org/10.1016/j.enpol.2011.09.036
Yalcintas M, Kaya A. Roles of income, price and household size on residential electricity consumption: comparison of Hawaii with similar climate zone states. Energy Rep. 2017; 3: 109-18. https://doi.org/10.1016/j.egyr.2017.07.002
Schrammel J, Diamond LM, Fröhlich P. Influencing residential electricity consumption with tailored messages: long-term usage patterns and effects on user experience. Energ Sustain Soc. 2023; 13: 15. https://doi.org/10.1186/s13705-023-00386-4
Tang J, Wang Z, Lee Y, Yang L. Machine learning approach to uncovering residential energy consumption patterns based on socioeconomic and smart meter data. Energy. 2022; 240: 122500. https://doi.org/10.1016/j.energy.2021.122500
Rokonuzzaman M, Jahan S, Haque MS. Household electricity consumption of middle-class family in chiitagong - a case study. American J Energy Res. 2016; 4(2): 35-41. https://doi.org/10.12691/ajer-4-2-2
Masebinu RO, Kambule N. Electricity consumption data of a middle-income household in Gauteng, South Africa: Pre and Post COVID-19 lockdown (2019-2021). Data Brief. 2022; 43: 108341. https://doi.org/10.1016/j.dib.2022.108341
Liu Y, Gao Y, Hao Y, Liao H. The relationship between residential electricity consumption and income: a piecewise linear model with panel data. Energies. 2016; 9(10): 831. https://doi.org/10.3390/en9100831
Never B, Kuhn S, Fuhrmann-Riebel H, Albert S, Gsell S, Jaramillo M, et al. Energy saving behaviours of middle-class households in Ghana, Peru and the Philippines. Energy Sust Dev. 2022; 68: 170-81. https://doi.org/10.1016/j.esd.2022.03.003
IEA50. The Potential of Behavioural Interventions for Optimising Energy Use at Home. https://www.iea.org/articles/the-potential-of-behavioural-interventions-for-optimising-energ y-use-at-home (Accessed on September 1, 2024).
Zhou K, Yang S. Understanding household energy consumption behavior: The contribution of energy big data analytics. Renew Sust Energy Rev. 2016; 56: 810-9. https://doi.org/10.1016/j.rser.2015.12.001
Ofetotse L, Essah EA, Yao R. Evaluating the determinants of household electricity consumption using cluster analysis. J Building Eng. 2021; 43: 102487. https://doi.org/10.1016/j.jobe.2021.102487
Motlagh O, Paevere P, Hong TS, Grozev G. Analysis of household electricity consumption behaviours: Impact of domestic electricity generation. Appl Math Comp. 2015; 270: 165-78. https://doi.org/10.1016/j.amc.2015.08.029
Wang J, Wang R, Cai H, Li L, Zhao Z. Smart household electrical appliance usage behavior of residents in China: Converging the theory of planned behavior, value-belief-norm theory and external information. Energy Build. 2023; 296: 113346. https://doi.org/10.1016/j.enbuild.2023.113346
Cui X, Lee M, Koo C, Hong T. Energy consumption prediction and household feature analysis for different residential building types using machine learning and SHAP: Toward energy-efficient buildings. Energy Build. 2024; 309: 113997. https://doi.org/10.1016/j.enbuild.2024.113997
Kaale LD, Kato T, Sakamoto K. Growth with disparity in a rich diverse city: case of the economic capital dar es salaam. In: Sakamoto K, Kaale LD, Ohmori R, Kato (Yamauchi) T, Eds. Changing Dietary Patterns, Indigenous Foods, and Wild Foods. Singapore: Springer; 2023. https://doi.org/10.1007/978-981-99-3370-9_7
The Citizen. Tanzania’s per capita income increases by five percent. https://www.thecitizen.co.tz/tanzania/news/national/tanzania-s-per-capita-income-increases-by-five-percent-4396556 (Accessed on September 1, 2024).
Ontario Tech. Dar es Salaam, Tanzania. https://sites.ontariotechu.ca/sustainability today /urban-and-energy-systems/Worlds-largest-cities/energy-projections/dar-es-salaam.php (Accessed on September 1, 2024).
National Bureau of Statistics. Impact of Access to Sustainable Energy Survey (IASES2021/22): Key Findings Report. https://www.nbs.go.tz/nbs/takwimu/Energy /The%202021-22%20Impact%20of%20Access%20to%20Sustainable%20Energy%20 Survey%20-%20English-Key%20Findings%20Report.pdf (Accessed on September 1, 2024).
TanzaiaInvest. Tanzania energy mix. https://www.tanzaniainvest.com/energy (Accessed on September 1, 2024).
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2024 Regina Mvungi, Respicius Kiiza, Pius Victor Chombo