REGIONAL TRAJECTORIES OF HOUSEHOLD ENERGY EFFICIENCY: MODELING FOR POLICY DECISION-MAKING IN POST-WAR UKRAINE
Анотація
The article offers a methodological framework for the comprehensive assessment of regional convergence and divergence processes in household energy efficiency based on multifactor modeling. The purpose of developing this model is to support the adoption of substantiated managerial decisions that will contribute to the formation of a fair and effective energy transition policy in post-war Ukraine. The model is based on the adapted Cobb-Douglas function, which takes into account a wide range of factors (socio-economic, behavioral, climatic, technical, and others) that directly influence energy consumption levels in the residential sector. The proposed approach enables not only the identification of key determinants of household energy efficiency across different regions but also the detection of common dynamic patterns (attractors) that outline regional development trajectories, considering the potential for convergence as well as the risks of divergence in energy efficiency levels among regions. The practical significance of the model lies in its application for simulating various policy scenarios and corresponding managerial decisions. This facilitates the planning and evaluation of the effectiveness of targeted subsidy programs for energy efficiency measures for households and communal enterprises, the development of comprehensive energy modernization plans for the housing stock, and the assessment of the impact of climate change on energy consumption in the residential sector. Additionally, the model supports substantiating the feasibility of creating educational programs on energy saving and the rational use of resources for households. The results of the simulation analysis within the model have enabled the formulation of scientifically grounded recommendations to improve the efficiency and fairness of resource allocation in the household energy supply sector. This, in turn, will contribute to the adoption of strategically balanced and adaptive decisions at the regional level, ensuring a sustainable and equitable energy transition for Ukraine in the post-war period.
Посилання
Green Economy Financing Facilities (2020) EBRD and E5P help 43,000 households in Ukraine become more energy efficient. Available at: https://surl.li/cvbxmi
Kurbatova T., Spivakovskyy S., Sotnyk M., Hyrchenko Ye. (2021) Solar energy advancement in Ukraine’s households: Is the feed-in tariff economically justified? IEEE 20th International Conference on Modern Electrical and Energy Systems, September 21-24, Kremenchuk, Ukraine. DOI: https://doi.org/10.1109/MEES52427.2021.9598758
Kurbatova T., Sotnyk I., Prokopenko O., Bashynska I., Pysmenna U. (2023) Improving the feed-in tariff policy for renewable energy promotion in Ukraine’s households. Energies 16, 6773. DOI: https://doi.org/10.3390/en1619677
Berkowitz D. (2022). Regional trends and convergence in Europe, 2000–2021. The World Bank. Available at: https://surl.lu/zyzcap
Nayak S., Sahoo D. (2022). Regional economic growth in India: convergence or divergence? Competitiveness Review, 32(1), 155–178. DOI: https://doi.org/10.1108/CR-10-2020-0131
Cornille D., Fankhauser S. (2006). Energy intensity in transition economies: Is there convergence towards the EU average? Applied Economics, 38(8), 899–912. DOI: https://doi.org/10.1080/00036840500392955
Lee J., Park J. (2022). Global energy intensity convergence using a spatial panel growth model. Applied Economics, 54(56), 6564–6580. DOI: https://doi.org/10.1080/00036846.2022.2131715
Holz F., Förster H. (2020). Divergence and convergence in energy efficiency: Evidence from EU countries. Energy Economics, 87, 104720. DOI: https://doi.org/10.1016/j.eneco.2019.104720
Boßmann T., Samadi S. (2018). Policy convergence in the EU energy transition: A multi-level governance perspective. Energy Research & Social Science, 44, 53-61. DOI: https://doi.org/10.1016/j.erss.2018.04.012
Lin B., Ouyang X. (2021). Regional energy efficiency convergence and its influencing factors: Evidence from China. Energy Economics, 95, 105105. DOI: https://doi.org/10.1016/j.eneco.2021.105105
Zhao X., Fan Y., Wei Y. M. (2019). Energy efficiency convergence in China: Evidence from dynamic panel data models. Energy, 178, 628-636. DOI: https://doi.org/10.1016/j.energy.2019.04.021
Wang Y., Li J. Chen, H. (2018). Income effect on household energy consumption and energy-saving behavior: Evidence from urban China. Energy Policy, 120, 397-404. DOI: https://doi.org/10.1016/j.enpol.2018.05.042
Zhang X., Zhou K. (2020). Technological innovation and energy efficiency: Evidence from renewable energy development. Renewable and Sustainable Energy Reviews, 130, 109958. DOI: https://doi.org/10.1016/j.rser.2020.109958
Sun Y., Yang S., Li M. (2019). Demographic impacts on residential energy consumption: A case study of China’s urban households. Energy, 183, 1144-1153. DOI: https://doi.org/10.1016/j.energy.2019.06.169
Liu Q., Wang S., Huang G. (2021). Climate impact on household energy consumption patterns: A regional analysis. Applied Energy, 291, 116785. DOI: https://doi.org/10.1016/j.apenergy.2021.116785
Apergis N., Payne J. (2017). Renewable energy, economic growth and policy: Evidence from the EU countries. Energy Policy, 101, 1-8. DOI: https://doi.org/10.1016/j.enpol.2016.11.025
Lall S., Yilmaz S. (2001). Regional Economic Convergence: Do Policy Instruments Make a Difference?. The Annals of Regional Science, 35, 153-166. DOI: https://doi.org/10.1007/s001680000035.
Mills B., Schleich J. (2012). Residential energy-efficient technology adoption, energy conservation, knowledge, and attitudes: An analysis of European countries. Energy Policy, 49, 616–628. DOI: https://doi.org/10.1016/j.enpol.2012.07.008
Baidoo A., Danquah J., Nunoo E. and et al. (2024) Households’ energy conservation and efficiency awareness practices in the Cape Coast Metropolis of Ghana. Discover Sustainability, 5 (2). DOI: https://doi.org/10.1007/s43621-023-00154-6
Das A., Paul S. (2015). Artificial illumination during daytime in residential buildings: Factors, energy implications and future predictions. Applied Energy, 158, 65–85. DOI: https://doi.org/10.1016/j.apenergy.2015.08.006
Nazeriye M., Haeri A., Haghighat F. (2021). Understanding the influence of building characteristics on enhancing energy efficiency in residential buildings: A data mining-based study. Journal of Building Engineering, 43, 103069. DOI: https://doi.org/10.1016/j.jobe.2021.103069
Le T., Gangwei C., Weijun G., Determinants and approaches of household energy consumption: A review, Energy Reports, 10, 2023, 1833-1850. DOI: https://doi.org/10.1016/j.egyr.2023.08.026
Sun Y., Wang J., Li, X. (2022). Behavioral variability and its impact on residential energy consumption: Implications for energy-saving interventions. Energy and Buildings, 257, 111789. DOI: https://doi.org/10.1016/j.enbuild.2021.111789
Alberini A., Filippini M. (2011). Response of residential electricity demand to price: The effect of measurement error. Energy Economics, 33(5), 889–895. DOI: https://doi.org/10.1016/j.eneco.2011.06.004
Reguant M. (2024). Measuring the impact of time-of-use pricing on electricity consumption: Evidence from Spain. ICREA Scientific Highlights. Available at: https://surl.li/gmtwsu
Octopus Energy (2018). Almost a third of consumers shift consumption out of peak, finds time-of-use tariff study. Current News. Available at: https://surl.li/gqglxt
Wilson C., Dowlatabadi H. (2007). Models of decision making and residential energy use. Annual Review of Environment and Resources, 32, 169-203. DOI: https://doi.org/10.1146/annurev.energy.32.053006.141137
Sunikka-Blank M., Galvin R. (2012). Introducing the prebound effect: The gap between performance and actual energy consumption. Building Research & Information, 40(3), 260-273. DOI: https://doi.org/10.1080/09613218.2012.690952
Bröchner J., Brandt N. (2011). Household energy consumption and demographics: Evidence from Sweden. Energy Policy, 39(9), 5707-5717. DOI: https://doi.org/10.1016/j.enpol.2011.07.018
Catalina T., Iordache V., Caracaleanu B. (2013). Influence of building insulation on energy consumption in residential buildings. Energy and Buildings, 65, 293-298. DOI: https://doi.org/10.1016/j.enbuild.2013.06.029
Santamouris M. (2016). Innovative materials and technologies for energy efficiency and comfort in buildings. Energy and Buildings, 116, 200-210. DOI: https://doi.org/10.1016/j.enbuild.2015.11.034
Rehman S., Mourshed M., Rezgui Y. (2019). Impact of climate variability on energy demand of residential buildings: A systematic review. Renewable and Sustainable Energy Reviews, 114, 109337. DOI: https://doi.org/10.1016/j.rser.2019.109337
Mlecnik E. (2010). Energy efficiency in residential buildings: Comparing multi-family apartments and single-family houses. Energy Policy, 38(4), 1934-1943. DOI: https://doi.org/10.1016/j.enpol.2009.11.027
Pérez-Lombard L., Ortiz J., Pout, C. (2008). A review on buildings energy consumption information. Energy and Buildings, 40(3), 394-398. DOI: https://doi.org/10.1016/j.enbuild.2007.03.007
OECD (2014), Greening Household Behaviour: Overview from the 2011 Survey – Revised edition, OECD Studies on Environmental Policy and Household Behaviour, OECD Publishing. DOI: http://dx.doi.org/10.1787/9789264214651-en
Steg L., Vlek, C. (2009). Encouraging pro-environmental behaviour: An integrative review and research agenda. Journal of Environmental Psychology, 29(3), 309-317. DOI: https://doi.org/10.1016/j.jenvp.2008.10.004
Whitmarsh L., O'Neill S., Lorenzoni I. (2011). Public engagement with climate change: What do we know and where do we go from here? International Journal of Media & Cultural Politics, 7(1), 19-32. DOI: https://doi.org/10.1386/macp.7.1.19_1
Ramos A., Rodrigues A., Silva C., Almeida M. (2016). Energy efficiency and income: Analysis of residential energy consumption in Portugal. Energy Policy, 96, 109-120. DOI: https://doi.org/10.1016/j.enpol.2016.05.01
Allcott H., Greenstone, M. (2012). Is There an Energy Efficiency Gap? Journal of Economic Perspectives, 26(1), 3-28. DOI: https://doi.org/10.1257/jep.26.1.3
International Energy Agency (2020). Energy Efficiency 2020. Available at: https://www.iea.org/reports/energy-efficiency-2020
