IDEAS home Printed from https://ideas.repec.org/a/pop/trustp/v2y2025p97-107.html

A literature review on the relationship between energy poverty and artificial intelligence

Author

Listed:
  • Alina Georgeta AILINCĂ

    ("Victor Slavescu" Financial and Monetary Research Center, INCE, Romanian Academy, Bucharest, Romania)

Abstract

Within the sustainable development goals, an important element is section seven, which talks about affordable, reliable and sustainable energy. At the European Union level, SDGs7 the subject is of increased importance, with extremely high environmental objectives being imposed, including achieving climate neutrality within the next 20 years. In this framework, energy poverty, which describes the inability of households to meet their basic energy needs (for heating, cooking, cooling, lighting), simultaneously touches on issues of social equity, energy infrastructure, climate change and broad socio-economic impact. In this context, although artificial intelligence (AI) raises issues related to a high technological level and huge energy consumption, therefore a possible negative impact on energy poverty, it nevertheless has a great potential to combat it by identifying, forecasting patterns, preventing, mitigating and correcting energy poverty. Prior work, both our own and from the literature, was analyzed to enhance understanding of energy efficiency and artificial intelligence. In this context, the objective of the paper is to to investigate the literature on the capacity of artificial intelligence in alleviating energy poverty by providing solutions on almost all the aforementioned levels (socio-cultural, economic, climate and policy). The results can help us understand what needs to be done further to improve the fight against energy poverty, including from the perspective of population energy security.The implications lie in the factthat it can be of assistance to the state, national and international organizations, local administrations, citizens and non-governmental organizations. The value of the study is given by the precariousness of studies on energy poverty (especially at the national level), often being the elephant in the room. In addition, from the perspective of AI possibilities, the approaches in the literature are even more restricted, being able, by their quality, to contribute to the rise from this status.

Suggested Citation

  • Alina Georgeta AILINCĂ, 2025. "A literature review on the relationship between energy poverty and artificial intelligence," International Conference on Machine Intelligence & Security for Smart Cities (TRUST) Proceedings, Smart-EDU Hub, Faculty of Public Administration, National University of Political Studies & Public Administration, vol. 2, pages 97-107, december.
  • Handle: RePEc:pop:trustp:v:2:y:2025:p:97-107
    as

    Download full text from publisher

    File URL: https://scrd.eu/index.php/trust/article/view/746/778
    Download Restriction: no

    File URL: https://scrd.eu/index.php/trust/article/view/746
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Chao & Zhang, Yuhan & Li, Xiang & Hao, Yanwei, 2024. "Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective," Resources Policy, Elsevier, vol. 88(C).
    2. Ding, Tao & Li, Hao & Liu, Li & Feng, Kui, 2024. "An inquiry into the nexus between artificial intelligence and energy poverty in the light of global evidence," Energy Economics, Elsevier, vol. 136(C).
    3. Stefan Bouzarovski, 2014. "Energy poverty in the European Union: landscapes of vulnerability," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(3), pages 276-289, May.
    4. Jiaqi Liu & Hongji Hu & Samson S. Yu & Hieu Trinh, 2023. "Virtual Power Plant with Renewable Energy Sources and Energy Storage Systems for Sustainable Power Grid-Formation, Control Techniques and Demand Response," Energies, MDPI, vol. 16(9), pages 1-28, April.
    5. Drescher, Katharina & Janzen, Benedikt, 2021. "Determinants, persistence, and dynamics of energy poverty: An empirical assessment using German household survey data," Energy Economics, Elsevier, vol. 102(C).
    6. Shaw, Rita & Attree, Mike & Jackson, Tim & Kay, Mike, 2009. "The value of reducing distribution losses by domestic load-shifting: a network perspective," Energy Policy, Elsevier, vol. 37(8), pages 3159-3167, August.
    7. Kettani, Maryème & Sanin, Maria Eugenia, 2024. "Energy consumption and energy poverty in Morocco," Energy Policy, Elsevier, vol. 185(C).
    8. Lefkothea Papada & Dimitris Kaliampakos, 2024. "Artificial Neural Networks as a Tool to Understand Complex Energy Poverty Relationships: The Case of Greece," Energies, MDPI, vol. 17(13), pages 1-19, June.
    9. Hu, Huanling & Wang, Lin & Peng, Lu & Zeng, Yu-Rong, 2020. "Effective energy consumption forecasting using enhanced bagged echo state network," Energy, Elsevier, vol. 193(C).
    10. Soto, Gonzalo H & Martinez-Cobas, Xavier, 2024. "Green energy policies and energy poverty in Europe: Assessing low carbon dependency and energy productivity," Energy Economics, Elsevier, vol. 136(C).
    11. Crnčec, Danijel & Penca, Jerneja & Lovec, Marko, 2023. "The COVID-19 pandemic and the EU: From a sustainable energy transition to a green transition?," Energy Policy, Elsevier, vol. 175(C).
    12. Kashour, Mohammad, 2023. "A step towards a just transition in the EU: Conclusions of a regression-based energy inequality decomposition," Energy Policy, Elsevier, vol. 183(C).
    13. Karam M. Al-Obaidi & Mohataz Hossain & Nayef A. M. Alduais & Husam S. Al-Duais & Hossein Omrany & Amirhosein Ghaffarianhoseini, 2022. "A Review of Using IoT for Energy Efficient Buildings and Cities: A Built Environment Perspective," Energies, MDPI, vol. 15(16), pages 1-32, August.
    14. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    15. Pino-Mejías, Rafael & Pérez-Fargallo, Alexis & Rubio-Bellido, Carlos & Pulido-Arcas, Jesús A., 2018. "Artificial neural networks and linear regression prediction models for social housing allocation: Fuel Poverty Potential Risk Index," Energy, Elsevier, vol. 164(C), pages 627-641.
    16. Li, Kang & Lloyd, Bob & Liang, Xiao-Jie & Wei, Yi-Ming, 2014. "Energy poor or fuel poor: What are the differences?," Energy Policy, Elsevier, vol. 68(C), pages 476-481.
    17. Apergi, Maria & Eicke, Laima & Goldthau, Andreas & Hashem, Mustafa & Huneeus, Sebastián & Lima de Oliveira, Renato & Otieno, Maureen & Schuch, Esther & Veit, Konstantin, 2024. "An energy justice index for the energy transition in the global South," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    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. Soto, Gonzalo H & Martinez-Cobas, Xavier, 2024. "Green energy policies and energy poverty in Europe: Assessing low carbon dependency and energy productivity," Energy Economics, Elsevier, vol. 136(C).
    2. Takako Mochida & Andrew Chapman & Benjamin Craig McLellan, 2025. "Exploring Energy Poverty: Toward a Comprehensive Predictive Framework," Energies, MDPI, vol. 18(10), pages 1-23, May.
    3. Xu, Xiao-Yu & Peng, Jia-Hui & Wang, Ke-Liang & Zhang, Zhen-Hua, 2025. "Is energy aid a panacea for energy poverty? Evidence from developing countries," Energy Policy, Elsevier, vol. 206(C).
    4. Liu, Minghao & Gou, Zhonghua, 2024. "Examining the relationship between dwelling energy efficiency and fuel poverty for retrofit strategies: A case study of the United Kingdom," Energy, Elsevier, vol. 311(C).
    5. Muhammad Shafiullah & Zhilun Jiao & Muhammad Shahbaz & Kangyin Dong, 2023. "Examining energy poverty in Chinese households: An Engel curve approach," Australian Economic Papers, Wiley Blackwell, vol. 62(1), pages 149-184, March.
    6. Wang, Yuelin & Xu, Bin, 2025. "Assessing the effective drivers of energy poverty reduction in China: A spatial perspective," Energy, Elsevier, vol. 320(C).
    7. Fry, Jane M. & Farrell, Lisa & Temple, Jeromey B., 2022. "Energy poverty and retirement income sources in Australia," Energy Economics, Elsevier, vol. 106(C).
    8. Oskar Szczygieł & Alena Harbiankova & Maria Manso, 2024. "Where Does Energy Poverty End and Where Does It Begin? A Review of Dimensions, Determinants and Impacts on Households," Energies, MDPI, vol. 17(24), pages 1-20, December.
    9. Buchner, Martin & Rehm, Miriam, 2025. "Energy poverty and health: Micro-level evidence from Germany," Energy Economics, Elsevier, vol. 145(C).
    10. Simionescu, Mihaela & Radulescu, Magdalena & Belascu, Lucian, 2024. "The impact of renewable energy consumption and energy poverty on pollution in Central and Eastern European countries," Renewable Energy, Elsevier, vol. 236(C).
    11. Keran Sarah Boyd & Christian Calvillo & Tanja Mueller & Xiaoyi Mu & Tong Zhu, 2023. "The Intersection of Fuel and Transport Policy in Scotland: A Review of Policy, Definitions and Metrics," Energies, MDPI, vol. 16(13), pages 1-14, June.
    12. Elpida Kalfountzou & Lefkothea Papada & Christos Tourkolias & Sevastianos Mirasgedis & Dimitris Kaliampakos & Dimitris Damigos, 2025. "A Comparative Analysis of Machine Learning Algorithms in Energy Poverty Prediction," Energies, MDPI, vol. 18(5), pages 1-20, February.
    13. Clavijo-Núñez, Susana & Núñez-Camarena, Gina M. & Herrera-Limones, Rafael & Hernández-Valencia, Miguel & Millán-Jiménez, Antonio, 2024. "The importance of citizen participation in improving comfort and health in obsolete neighbourhoods affected by energy poverty," Energy Policy, Elsevier, vol. 191(C).
    14. Mara, Eugenia Ramona, 2025. "Mitigating energy poverty in the European union welfare states through renewable energy and technological innovation," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 438-460.
    15. Yiming Xiao & Han Wu & Guohua Wang & Hong Mei, 2021. "Mapping the Worldwide Trends on Energy Poverty Research: A Bibliometric Analysis (1999–2019)," IJERPH, MDPI, vol. 18(4), pages 1-22, February.
    16. Esperanza Vera‐Toscano & Heather Brown, 2022. "Empirical Evidence on the Incidence and Persistence of Energy Poverty in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(4), pages 515-529, December.
    17. Husnain, Muhammad Iftikhar ul & Nasrullah, Nasrullah & Khan, Muhammad Aamir & Banerjee, Suvajit, 2021. "Scrutiny of income related drivers of energy poverty: A global perspective," Energy Policy, Elsevier, vol. 157(C).
    18. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Georghiou, George E., 2021. "Social arrangements, technical designs and impacts of energy communities: A review," Renewable Energy, Elsevier, vol. 169(C), pages 1138-1156.
    19. Simionescu, Mihaela & Cifuentes-Faura, Javier, 2024. "The digital economy and energy poverty in Central and Eastern Europe," Utilities Policy, Elsevier, vol. 91(C).
    20. Chen, Lei & Jiang, Nana & Wang, Shuai, 2025. "An impossible driver for energy justice? Exploring the impact of artificial intelligence on China's energy transition," Energy Policy, Elsevier, vol. 207(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • O35 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Social Innovation

    Statistics

    Access and download statistics

    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:pop:trustp:v:2:y:2025:p:97-107. 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: Professor Catalin Vrabie (email available below). General contact details of provider: https://edirc.repec.org/data/fasnsro.html .

    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.