IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i15p3656-d1442269.html
   My bibliography  Save this article

Ownership, Patterns of Use and Electricity Consumption of Domestic Appliances in Urban Households of the West African Monetary and Economic Union: A Case Study of Ouagadougou in Burkina Faso

Author

Listed:
  • Komlan Hector Seth Tete

    (Laboratoire Energies Renouvelable et Efficacité Energétique, Institut International d’Ingénierie de l’Eau et de l’Environnement (2iE), Rue de la Science, Ouagadougou 01 BP 594, Burkina Faso)

  • Yrébégnan Moussa Soro

    (Laboratoire Energies Renouvelable et Efficacité Energétique, Institut International d’Ingénierie de l’Eau et de l’Environnement (2iE), Rue de la Science, Ouagadougou 01 BP 594, Burkina Faso)

  • Djerambete Aristide Nadjingar

    (Laboratoire Energies Renouvelable et Efficacité Energétique, Institut International d’Ingénierie de l’Eau et de l’Environnement (2iE), Rue de la Science, Ouagadougou 01 BP 594, Burkina Faso)

  • Rory Victor Jones

    (School of the Built Environment, University of Reading, Reading RG6 6UR, UK)

Abstract

In the West African Monetary and Economic Union (UEMOA), information on the characteristics of the users and patterns of electricity end-uses remains hard to find. This study aims to contribute to reducing the gap in research on domestic electricity consumption in the region by unveiling the ownership rates, patterns of use and electricity consumption of domestic appliances in urban households through a city-wide survey. Three categories of urban users were investigated including high, medium and low consumers. Findings demonstrated various ownership rates for appliances, ranging from 100% for lighting fixtures to 0% for washing machines depending on user category. Domestic electricity demonstrated patterns consisting of three peak demand periods, with the main ones occurring in the evening (19:00 to 20:00) and the night (22:00). Other demand characteristics include an average daily electricity use ranging from 0.50 to 6.42 kWh per household, a maximum power demand of between 0.19 and 0.70 kW and a daily load factor between 35 and 58%. Finally, the appliances contributing the most to domestic electricity use include air-conditioners, fans, fridges and freezers, televisions and lighting fixtures, with contributions differing from one category of user to another. Policy implications including review of the appliances’ importations framework and policies, and incentives for purchasing efficient appliances, design of more tailored policies, considering the different backgrounds of the users, education enhancement on energy behaviours for increasing energy efficiency/conservation, and implementation of DSM programs including load levelling, load shifting and load reducing depending on the type of appliance for energy conservation in the domestic buildings were derived. Overall, a large range of stakeholders of the electricity sector, not only in the West African Economic and Monetary Union (UEMOA), but also in other regions and countries sharing common characteristics should be interested in the results of this study.

Suggested Citation

  • Komlan Hector Seth Tete & Yrébégnan Moussa Soro & Djerambete Aristide Nadjingar & Rory Victor Jones, 2024. "Ownership, Patterns of Use and Electricity Consumption of Domestic Appliances in Urban Households of the West African Monetary and Economic Union: A Case Study of Ouagadougou in Burkina Faso," Energies, MDPI, vol. 17(15), pages 1-39, July.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3656-:d:1442269
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/15/3656/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/15/3656/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xuechao Xia & Hui Sun & Zedong Yang & Weipeng Yuan & Dianyuan Ma, 2022. "Decoupling Analysis of Rural Population Change and Rural Electricity Consumption Change in China," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    2. Mohamed, Ahmed M.A. & Al-Habaibeh, Amin & Abdo, Hafez & Elabar, Sherifa, 2015. "Towards exporting renewable energy from MENA region to Europe: An investigation into domestic energy use and householders’ energy behaviour in Libya," Applied Energy, Elsevier, vol. 146(C), pages 247-262.
    3. Peprah, Forson & Gyamfi, Samuel & Effah-Donyina, Eric & Amo-Boateng, Mark, 2023. "The pathway for electricity prosumption in Ghana," Energy Policy, Elsevier, vol. 177(C).
    4. Adeoye, Omotola & Spataru, Catalina, 2019. "Modelling and forecasting hourly electricity demand in West African countries," Applied Energy, Elsevier, vol. 242(C), pages 311-333.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giacomo Falchetta & Nicolò Stevanato & Magda Moner-Girona & Davide Mazzoni & Emanuela Colombo & Manfred Hafner, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," Working Papers 2020.09, Fondazione Eni Enrico Mattei.
    2. Pesantez, Jorge E. & Li, Binbin & Lee, Christopher & Zhao, Zhizhen & Butala, Mark & Stillwell, Ashlynn S., 2023. "A Comparison Study of Predictive Models for Electricity Demand in a Diverse Urban Environment," Energy, Elsevier, vol. 283(C).
    3. Dragan Pamučar & Ibrahim Badi & Korica Sanja & Radojko Obradović, 2018. "A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya," Energies, MDPI, vol. 11(9), pages 1-25, September.
    4. Falchetta, Giacomo & Stevanato, Nicolò & Moner-Girona, Magda & Mazzoni, Davide & Colombo, Emanuela & Hafner, Manfred, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," FEP: Future Energy Program 305213, Fondazione Eni Enrico Mattei (FEEM) > FEP: Future Energy Program.
    5. Di Leo, Senatro & Caramuta, Pietro & Curci, Paola & Cosmi, Carmelina, 2020. "Regression analysis for energy demand projection: An application to TIMES-Basilicata and TIMES-Italy energy models," Energy, Elsevier, vol. 196(C).
    6. Shusen Zhu & Hui Sun & Xuechao Xia & Zedong Yang, 2023. "Decoupling Analysis of Carbon Emissions and Forest Area in China from 2004 to 2020," Land, MDPI, vol. 12(7), pages 1-15, July.
    7. Hamagham Peter Ishaku & Humphrey Adun & Moein Jazayeri & Mehmet Kusaf, 2022. "Decarbonisation Strategy for Renewable Energy Integration for Electrification of West African Nations: A Bottom-Up EnergyPLAN Modelling of West African Power Pool Targets," Sustainability, MDPI, vol. 14(23), pages 1-36, November.
    8. Delzendeh, Elham & Wu, Song & Lee, Angela & Zhou, Ying, 2017. "The impact of occupants’ behaviours on building energy analysis: A research review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1061-1071.
    9. Maaouane, Mohamed & Zouggar, Smail & Krajačić, Goran & Zahboune, Hassan, 2021. "Modelling industry energy demand using multiple linear regression analysis based on consumed quantity of goods," Energy, Elsevier, vol. 225(C).
    10. Abdul Conteh & Mohammed Elsayed Lotfy & Oludamilare Bode Adewuyi & Paras Mandal & Hiroshi Takahashi & Tomonobu Senjyu, 2020. "Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets," Sustainability, MDPI, vol. 12(7), pages 1-20, March.
    11. Jin, Haowei & Guo, Jue & Tang, Lei & Du, Pei, 2024. "Long-term electricity demand forecasting under low-carbon energy transition: Based on the bidirectional feedback between power demand and generation mix," Energy, Elsevier, vol. 286(C).
    12. Mohsin, Muhammad & Taghizadeh-Hesary, Farhad & Iqbal, Nadeem & Saydaliev, Hayot Berk, 2022. "The role of technological progress and renewable energy deployment in green economic growth," Renewable Energy, Elsevier, vol. 190(C), pages 777-787.
    13. Murray, D.M. & Liao, J. & Stankovic, L. & Stankovic, V., 2016. "Understanding usage patterns of electric kettle and energy saving potential," Applied Energy, Elsevier, vol. 171(C), pages 231-242.
    14. Kondi-Akara, Ghafi & Hingray, Benoit & Francois, Baptiste & Diedhiou, Arona, 2023. "Recent trends in urban electricity consumption for cooling in West and Central African countries," Energy, Elsevier, vol. 276(C).
    15. Adeoye, Omotola & Spataru, Catalina, 2020. "Quantifying the integration of renewable energy sources in West Africa's interconnected electricity network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    16. Zhou, Kaile & Yang, Shanlin, 2016. "Understanding household energy consumption behavior: The contribution of energy big data analytics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 810-819.
    17. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    18. Wu, Han & Liang, Yan & Heng, Jiani, 2023. "Pulse-diagnosis-inspired multi-feature extraction deep network for short-term electricity load forecasting," Applied Energy, Elsevier, vol. 339(C).
    19. Ehtiwesh, Amin & Kutlu, Cagri & Su, Yuehong & Riffat, Saffa, 2023. "Modelling and performance evaluation of a direct steam generation solar power system coupled with steam accumulator to meet electricity demands for a hospital under typical climate conditions in Libya," Renewable Energy, Elsevier, vol. 206(C), pages 795-807.
    20. Abid, Hamza & Thakur, Jagruti & Khatiwada, Dilip & Bauner, David, 2021. "Energy storage integration with solar PV for increased electricity access: A case study of Burkina Faso," Energy, Elsevier, vol. 230(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3656-:d:1442269. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.