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Impacts of Tariffs on Energy Conscious Behavior with Respect to Household Attributes in Saudi Arabia

Author

Listed:
  • Kh Md Nahiduzzaman

    (Life Cycle Management Laboratory, School of Engineering, University of British Columbia, 1137 Alumni Avenue, Kelowna, BC V1V 1V7, Canada)

  • Abdullatif Said Abdallah

    (Faculty of Architecture, Building and Planning, University of Melbourne, Melbourne, VIC 3053, Australia)

  • Arash Moradzadeh

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran)

  • Amin Mohammadpour Shotorbani

    (Life Cycle Management Laboratory, School of Engineering, University of British Columbia, 1137 Alumni Avenue, Kelowna, BC V1V 1V7, Canada)

  • Kasun Hewage

    (Life Cycle Management Laboratory, School of Engineering, University of British Columbia, 1137 Alumni Avenue, Kelowna, BC V1V 1V7, Canada)

  • Rehan Sadiq

    (Life Cycle Management Laboratory, School of Engineering, University of British Columbia, 1137 Alumni Avenue, Kelowna, BC V1V 1V7, Canada)

Abstract

Historically, the combination of generous subsidies along with extreme climate has led to unsustainable domestic electricity consumption in Saudi Arabia. The residential sector constitutes a significant portion of this consumption. Amid the economic challenges, the country enforced a new electricity tariff for residential consumers in 2018. This study thus leverages change in 2018–2020 by collecting and analyzing the electricity consumption data of 73 households in the Eastern Province of Saudi Arabia. The energy consumption is modeled based on the households’ attributes (e.g., dwelling type, ownership, number of residents, rooms, ventilation type, etc.) and applied tariffs using a machine learning technique. The extreme learning machine (ELM) is employed in solving the overfitting problem due to low-volume data. The correlation matrix is also constructed to determine the relationship between the household attributes. The ELM model developed in this study extracts the correlation between the input variables in determining energy consumption and also predicts the energy consumption related to low consumption data. The findings indicated that the electricity consumption between the pre-revised tariff year and the revised tariff enforcement year saw a reduction which was consistent in the subsequent years. This was also validated by the paired sample t -test, which showed a significant decrease in electricity consumption for the study period. The analysis also revealed that several household attributes had a relatively high impact on the reduction in the electricity consumption level following the revised tariffs, whereas the majority of the attributes had a moderate impact. In addition to these key findings, the demonstrated pathway adopted in this study is itself a methodological contribution that provides critical information about the sensitivity of the impacts of tariffs on energy consumption with respect to different household attributes. Economic factors being the critical stress need to be blended with existing energy consciousness for positive changes in favor of energy-saving behavior of the household members. The study does not attempt to represent the population of concern, but demonstrates a methodology that would help unleash inherent energy consciousness in favor of sustainable and energy-efficient behavior.

Suggested Citation

  • Kh Md Nahiduzzaman & Abdullatif Said Abdallah & Arash Moradzadeh & Amin Mohammadpour Shotorbani & Kasun Hewage & Rehan Sadiq, 2023. "Impacts of Tariffs on Energy Conscious Behavior with Respect to Household Attributes in Saudi Arabia," Energies, MDPI, vol. 16(3), pages 1-24, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1458-:d:1054641
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    References listed on IDEAS

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    1. Azevedo, Isabel & Delarue, Erik & Meeus, Leonardo, 2013. "Mobilizing cities towards a low-carbon future: Tambourines, carrots and sticks," Energy Policy, Elsevier, vol. 61(C), pages 894-900.
    2. Wang, Zhaohua & Zhang, Bin & Zhang, Yixiang, 2012. "Determinants of public acceptance of tiered electricity price reform in China: Evidence from four urban cities," Applied Energy, Elsevier, vol. 91(1), pages 235-244.
    3. Mohammad AlHashmi & Gyan Chhipi-Shrestha & Rajeev Ruparathna & Kh Md Nahiduzzaman & Kasun Hewage & Rehan Sadiq, 2021. "Energy Performance Assessment Framework for Residential Buildings in Saudi Arabia," Sustainability, MDPI, vol. 13(4), pages 1-25, February.
    4. Krarti, Moncef & Dubey, Kankana & Howarth, Nicholas, 2017. "Evaluation of building energy efficiency investment options for the Kingdom of Saudi Arabia," Energy, Elsevier, vol. 134(C), pages 595-610.
    5. Du, Gang & Lin, Wei & Sun, Chuanwang & Zhang, Dingzhong, 2015. "Residential electricity consumption after the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 157(C), pages 276-283.
    6. Mohammad AlHashmi & Gyan Chhipi-Shrestha & Kh Md. Nahiduzzaman & Kasun Hewage & Rehan Sadiq, 2021. "Framework for Developing a Low-Carbon Energy Demand in Residential Buildings Using Community-Government Partnership: An Application in Saudi Arabia," Energies, MDPI, vol. 14(16), pages 1-36, August.
    7. Peter C. Reiss & Matthew W. White, 2008. "What changes energy consumption? Prices and public pressures," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 636-663, September.
    8. Pothitou, Mary & Hanna, Richard F. & Chalvatzis, Konstantinos J., 2016. "Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study," Applied Energy, Elsevier, vol. 184(C), pages 1217-1229.
    9. Wu, Ya & Zhang, Li, 2017. "Evaluation of energy saving effects of tiered electricity pricing and investigation of the energy saving willingness of residents," Energy Policy, Elsevier, vol. 109(C), pages 208-217.
    10. Liu, Che & Sun, Bo & Zhang, Chenghui & Li, Fan, 2020. "A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine," Applied Energy, Elsevier, vol. 275(C).
    11. Arash Moradzadeh & Omid Sadeghian & Kazem Pourhossein & Behnam Mohammadi-Ivatloo & Amjad Anvari-Moghaddam, 2020. "Improving Residential Load Disaggregation for Sustainable Development of Energy via Principal Component Analysis," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    12. Fan Zhang, 2015. "Energy Price Reform and Household Welfare: The Case of Turkey," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    13. Anna Justyna Parzonko & Agata Balińska & Anna Sieczko, 2021. "Pro-Environmental Behaviors of Generation Z in the Context of the Concept of Homo Socio-Oeconomicus," Energies, MDPI, vol. 14(6), pages 1-18, March.
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    1. Alettin Irmak & Nurlan Kurmanov & Onaikhan Zhadigerova & Zukhra Turdiyeva & Aigul Bakirbekova & Gaukhar Saimagambetova & Assilbek Baidakov & Aigul Mukhamejanova & Madina Tolysbayeva & Sagyngali Seitzh, 2023. "Shaping Energy-Saving Behavior in Education System: A Systematic Review," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 46-60, July.
    2. Lia Marchi & Jacopo Gaspari, 2023. "Energy Conservation at Home: A Critical Review on the Role of End-User Behavior," Energies, MDPI, vol. 16(22), pages 1-22, November.

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