You are currently viewing a new version of our website. To view the old version click .
Energies
  • Perspective
  • Open Access

4 January 2023

Energy Poverty and Low Carbon Energy Transition

and
1
Lithuanian Energy Institute, Breslaujos 3, LT-44403 Kaunas, Lithuania
2
School of Electrical and Computer Engineering, National Technical University of Athens, Heroon Polytechniou 9, Zografou Campus, GR-15780 Athens, Greece
*
Authors to whom correspondence should be addressed.

Abstract

In the recent two decades of recorded literature, energy poverty is increasingly understood as a multi-dimensional issue caused by the low-carbon energy transition. In this study, a literature review was performed, the outcome of which confirmed the contentious nature of energy poverty at the regional and international levels of analysis. Furthermore, the collected literature enabled the identification of those domains under which energy poverty is prevailing. The impacts of the current COVID-19 pandemic and the Russian-Ukrainian war on energy prices and energy poverty were also considered key issues of interest in recently published studies (published within the last five years). While all the collected studies in the literature review covered a wide geographical context worldwide, a comprehensive analysis of nurturing energy poverty sources and their consequences was primarily and foremost understood in the household sector, which was the research focus of this study, accordingly. Moreover, future research guidelines that should be drawn regarding energy poverty alleviation were also proposed.

1. Energy Poverty as a Multi-Parametric Issue: Literature Overview

Recently, energy poverty has become a contentious issue that causes disagreement and competitive arguments regionally and globally. In this context, an impressive and ongoing plethora of relevant publications have been issued on energy poverty, either as a situational reality or as a precautionary condition that all countries have to reconcile with, sooner or later. In an attempt to better organize and coherently approach this plethora of relevant productions, this perspective study organized the relevant literature reviews in alignment with the chronological criterion of the last five years of publication (period of 2018-onwards), as well as the sectoral criterion of households, since it is anticipated that energy poverty is gradually affecting and directly impacting urban and densely populated areas globally, where there are not adequate alternative choices to confront the energy poverty occurrence. The literature search was conducted in September 2022 at the Scopus database by setting the following keywords: “Energy”, “Poverty”, “Households”. The sub-criteria of this literature search were: (a) the last five years of documents’ year of publication: “2018–2022”, (b) the three keywords to be altogether placed in the “article title”, and (c) the English-written publications, which represented 90% of the total documents yielded. The snowballing method was also applied, i.e., the reference list of a selected paper during the literature search was used to identify additional papers on this topic. In the end, 53 documents were yielded, organized, and allocated into the key aspects/dimensions of reviewing, as shown in Figure 1 below:
Figure 1. The profile of literature review allocation on energy poverty studies among the four main dimensions of analysis (source: author’s own study).
(A)
The economic dimension, referring to energy poverty and energy vulnerability in developed and developing European countries, focuses on welfare losses, housing policies, and economic concerns. This key aspect of reviewing was further organized into the following spatial contexts of literature studies: Northern Europe, Central Europe, and Mediterranean Europe.
(B)
The geographical dimension, referring to the geographical context/coverage of reviewing, includes the continents of Asia (mainly China, followed by India and Pakistan) and America.
(C)
The in-field dimension, referring to energy poverty and large-scale spatial analyses, focuses on the regional level of analysis and typical infrastructure works involved in similar studies.
(D)
The human dimension, referring to energy poverty and its socio-cultural features and anthropocentric considerations, concentrates on the human adaptation and the community involvement in a global prospect of energy poverty.
Based on the aforementioned literature organization, the key aspects/dimensions A and B were developed in the form of informative tables, while the key aspects/dimensions C and D were deployed in a systematic and creative descriptive-narrative text. Then, the main argumentation issues were subjected to an argumentation analysis in the “Discussion” section, while the concluding remarks of this literature review were signified in the “Conclusions” section, accordingly.

2. Economic Dimension: Energy Poverty and Energy Vulnerability in Developed and Developing European Countries: Welfare Losses, Housing Policies, and Economic Concerns

The first pillar of energy poverty is unavoidably related to energy vulnerability and access to reliable energy sources among developed and developing countries. In this respect, there has been a plethora of relevant studies produced during the time and in varied areas worldwide. Therefore, in this perspective paper, it was decided that the relevant organization of this plentiful literature production would fall under the geographical criterion, among European countries, and under the sectoral criterion of household-focused studies. The relevant literature production is presented in Table 1 in reverse chronological order of publication, from the newest to the oldest, per European territory: North, Central, and Mediterranean, respectively.
Table 1. Allocation of research and objectives and main outcomes among developing and developed countries in Europe (Source: Authors own study).
Based on Table 1, it can be deduced that energy poverty is a multi-faceted and multi-parametric issue that intensively impacts household activities and financial priorities, thus, necessitating different estimation strategies and plans to be followed. In this respect, financial inclusion should be materialized by instrumenting access to funding sources, such as micro-financing households by local banks with attractive interest rates, especially for female-headed households. Indeed, financial inclusion can significantly alleviate energy poverty, but it can also positively affect health and income, which are significant determinants of energy poverty. Therefore, smart-energy policies are capable of nurturing suitable financial conditions for alleviating energy poverty [].

3. Geographical Dimension

The second pillar of energy poverty is literature related to a wide, global, geographical coverage of reporting energy poverty, especially in Asia (mainly China, followed by India and Pakistan), America, and Africa (mainly South Africa, followed by Kenya and Nigeria). In this respect, there has been a dedicated plethora of relevant studies that were organized in this perspective paper under the geographical criterion of referencing. The relevant literature production is presented in Table 2 in reverse chronological order of publication, from the newest to the oldest, per continent: Asia, America, and Africa, respectively.
Table 2. Allocation of research studies on energy poverty globally (Source: Authors own study).

4. In Field Dimension: Energy Poverty and Large-Scale Spatial Analyses and Infrastructure Works

As it has been already stated at the preceding section, the spatial analyses and the need of infrastructure updating and expansion has been proven vital, especially among fast emerging economies worldwide. In this context, it has been denoted in the relevant literature that the Indian government has undertaken important inroads to address national energy poverty, while recently announcing the electrification of 100% of villages. Yet, approximately 300 million people have no access to electricity, being considered deeply energy poor, having no electricity grid connection in their households, but covering their energy needs through private sector firms that provide off-grid solutions. However, the ever-expanding grid has stressed that such private firms face uncertainty and must redesign their value propositions and strategies. Such strategies take into consideration that grid expansion is generally designed under high social embeddedness, risky mitigation, and remotely located conditions. Moreover, the roles of private sector companies provide reliable and intermittent electricity services, especially among energy-poor communities worldwide that cannot be undermined [].
From a spatial/geographical point of view that can point out significant implications for domestic policy-making concerned with energy poverty, residential energy efficiency, and energy consumption, especially in alignment with the inability of urban households in the cold-climate zone in densely populated areas, such as northern China, to access sufficient domestic energy services, and thus their vulnerability to energy poverty and the insufficient heating provision []. The authors of this study signified households’ vulnerabilities in having access to adequate heating sources in their homes. This shortage of effective heating is most pronounced in those households that have no access to efficient and flexible networked infrastructures or are of high quality of construction, compared to the heating provision in urban mega-cities in which state subsidies have been provided (these subsidies can operate as buffers for households from energy-poverty areas) [].
From an infrastructural point of view, it has been noted in the literature that transformations in energy structures and governance models are vital preconditions to meeting the needs of communities living in rural and remote areas, serving citizens that are particularly vulnerable to energy and economic poverty. This multi-parametric design of models should ideally consider the multi-faceted global climate and social, economic, and environmental interests, as well as the determination of the scale of design: national, state, and local governments, that can be also compatible with embedded energy infrastructure. Among relevant technologies of large-scale infrastructure are those of decentralized solar solutions that can support energy transformation in spatially, economically, and socially disadvantaged communities. However, the deployment of such scales of technology adoption and energy transformation is hamstrung by path dependencies including policy frameworks, business models, and infrastructure. The obstacles of operating successful decentralized solar PV are typically the disconnect between policy makers and implementers, poor coordination amongst stakeholders, as well as limited institutional focus and competence, which should also be guided by political oppositions in setting policy frameworks of running collaboration among businesses, system suppliers, financial intermediaries, distribution companies, civil society, and end users []. Similarly, technological ventures of PV-installed electricity generations were reported at buildings in a community (in the case of a social housing district of southern Spain in 2017). In such a case, improvements of up to 33% in the winter and 67% in the summer could be obtained while simultaneously reducing the thermal comfort differences among the regional dwellings. Without being phenomenologically obvious, the subsequent decline of prices through the expansion of distributed energy technologies such as PVs can support an opportunity for positive social changes [].
Another critical issue that is associated with large-scale infrastructures is the fact that the implementation of systemic solutions for the benefit of energy security necessitates a properly defined problem that, subsequently, supports authorities in devising instruments understood as the operational form of public intervention (a specific action strategy) in order to provide a comprehensive solution to this case-specific problem [,]. In such a way, the adopting technologies can support the foundation and monitoring of explicit legal frameworks that are defining energy poverty at a local level of analysis []. An indicative technological solution that has been referred to in the literature is the use of geothermal energy as an alternative source of thermal energy, as a measure to reduce low emissions and diminish their consequences from the viewpoint of local ecological security. Therefore, the potential assessment of geothermal energy in increasing the level of energy security was scheduled by lowering, or even eradicating, energy poverty in households, thus, confirming the effectiveness and viability of this energy resource. Other co-evaluations (along with the technological base) are key factors that can be the specific properties of geothermal energy and its relatively low price compared to conventional fossil-fuel-based energy sources [].

5. Human Dimension: Energy Poverty Socio-Cultural Features and Anthropocentric Considerations

Countries that sustain a large share of their population in energy poverty are unavoidably subjected to increases in appliance and electricity demand. Subsequently, designing solutions that estimate latent demand of energy-poor populations often assume a constant income elasticity of demand, making needful the simulate-estimation of responsiveness of electricity demand at income, accounting for non-linearities, and considering other important drivers. Therefore, data from four developing nations can support the assessment of the implications of policy scenarios to achieve Sustainable Development Goal (SDG 7) under different socio-economic futures and universal policies of electricity services, regardless of the high total electricity demand reported and the low average per capita due to no access to policy features. Other socio-economic characteristics of determining the energy poverty are related to electrical appliances of varied types regarding the country, the climate, the income, and the level of stability on electricity provision. It can also be confirmed that as energy-poor populations gain access to electricity services, the demand is anticipated to rise, but in order for biased conclusions to be made, the heterogeneity of energy must also be considered [].
Similarly, clean and health-safe sources of energy consist of a global challenge, implying that income smoothing can be prioritized among other energy poverty reduction interventions, mainly among rural households [,,]. Another challenging issue of energy poverty is its causality in driving the socioeconomic activities of households for domestic or entrepreneurial purposes, especially in terms of the potential danger caused by the lack of access to modern day energy services that have to be accessible and exploitable irrespective of the severity of energy poverty [] and their implication for resource-poor households [].
Another socio-economic parameter is related to the spatial allocation of energy poverty, especially in rural and urban contexts. Indeed, low-income households in rural areas are more energy-deprived than those in urban areas. Furthermore, low-income households in both urban and rural areas are mostly deprived in the dimension of heating fuel. This study recommended that suitable measures to combat energy poverty should be rural–urban specific [,]. At this point it can also be signified that almost 91% of households in rural economies are based on traditional fuels for cooking and heating, not being satisfied since they are deprived of modern sources of exploitable energy. Subsequently, energy inequalities in poor settlements could be better addressed by imposing affordable energy tariffs for the poor and creating long-run job positions [].
The socio-economic determinants of energy poverty are also related to the humanitarian values and cultures that are nurtured, especially in low- and middle-income countries (LMICs) in which young children are highly vulnerable to the adverse effects of household micro-environments. The global interest in this anthropocentric aspect of energy poverty is determined by the UN Sustainable Development Goals (SDGs), specifically SDG 3 up to SDG 7, which urge for a comprehensive multi-sector approach to achieve the 2030 goals. Therefore, it is crucial for researchers to address gaps in understanding the health effects of household micro-environments in resource-poor settings. In this context, a relevant research study examining the associations of household micro-environment variables with episodes of acute respiratory infection (ARI) and diarrhea in Uganda revealed multi-sectoral synergies among energy, water, sanitation, and hygiene factors, thus (mainly African) women empowerment programs can support public health and early childhood illnesses [].
A portion of the literature production that is devoted to energy poverty is irreversibly related to economic poverty, being a dominant paired factor of energy poverty among millions of households in densely populated areas, as India is. Therefore, primary data on various socio-economic variables (SEVs) that have been collected from thousands of households in Mumbai and that were subsequently analyzed are of particular importance and utmost significance, being more conveniently manipulated under relevant income groups []. It was reported that energy poverty mainly depends on households’ expenditures, since a large household is unavoidably related to higher expenses on electricity to meet all needs for heating, cooling, and hot water. Moreover, education sustains a subtle affection for energy poverty since energy conservation measures can be effectively linked to energy poverty reduction, especially among households with lower incomes. In such an approach, the achievement of sustainable energy for all households among densely populated areas, such as India, necessitates policies and strategies regarding electricity affordability and increased awareness of energy conservation practices [].

6. Discussions

Access only to intermittent or unreliable electricity networks is related to welfare losses for households in developing countries and affects their households’ willingness to pay (WTP) in order to lower or avoid significant blackout episodes in terms of both annual income and expenditure as a proxy for income []. In a similar study, it was suggested that lower-income groups were the main contributors to total poverty compared to higher-income households. While it is a fact that poverty rates are directly determined by the choices of energy consumers, relevant models of household energy poverty can be flexible enough to allow for varied assumptions to be considered under a useful sensitivity analysis [].
Additionally, the confrontation of energy poverty is inseparably considered in pairing policies and strategies with governmental initiatives and regulations to promote investment in energy infrastructure technologies which can make the energy pricing affordable to poor local communities, thus, reducing their energy vulnerability and drudgery, while improving their income earning activities and livelihood conditions []. In such a way, central governments, with the aid of municipalities, can ensure that rural dwellers have unhindered access to modern energy facilities, and at the same time, the young population can be motivated to domesticate rural communities and to be involved in the local socioeconomic activities []. However, households have long waited for central governments to solve energy problems, to no avail. Therefore, rural households’ welfare, especially among agricultural-bounded economies, can be improved if investors adopt an installment plan. Nevertheless, it cannot be undermined that businesses (especially small and medium enterprises, SMEs) are concerned about economic gains and that the main source of their profitability comes from the budgets of rural households, as well as the terms of payment on a monthly basis, as well as the feasibility of paying back the household expenses in the long run [].
From a technological point of view, the literature proposed a crucial intervention towards grid reliability and sustainability, jointly with environmental preservation and gendered energy poverty, all offering benefits of the energy expenditure affordability indicator. In such a way, household financial savings range from 12% to 82% based on the implementation level of distributed storage, and generation as well as the local energy mix plans [].
From a multi-parametric framework of energy poverty considerations, the following issues have been collected and represented:
-
Controlling and regulating households’ energy consumption and the emitted huge greenhouse gases (GHG), they can potentially and positively impact energy poverty reduction, implementation of the energy justice principle, and climate change mitigation [].
-
Identifying trust can be valued as an important channel through which ethnic diversity operates, shaping policies regarding social capital in multi-cultural societies and adopting feasible alternative ways to measure energy poverty [].
-
By using quantitative and statistical methods, realistic longitudinal approaches can precisely record the energy efficiency measures that have been adopted in the past, interpreting energy poverty under specific socio-economic conditions and revealing that the improvement of energy efficiency in homes that are at risk of energy poverty has a profound impact on (a) the well-being and quality of life [] and (b) exploring how the social dimension of energy poverty could be integrated into future policymaking processes [].
-
Linking the utility of localized and remote renewable energy sources (RES) with better spatial planning of land uses [,], such as biomass production [], enables policy makers to determine the optimal budgeting mix through relevant weights of each aspect that guarantees the success of the designed energy-oriented ventures [].
-
Relating the energy poverty planning and proposal with the joint appreciation of the concurring environmental, technological, and technological dimensions of modern energy production schemes [,].
Based on the analysis above, the research integration framework for energy poverty is outlined in Table 3 below.
Table 3. Energy poverty overview (Source: authors own study).

7. Conclusions

In conclusion, it can be signified that there is an imperative need for energy poverty to be approached in an integrated and carefully designed strategic planning for low carbon energy transition. Such a plan cannot be appreciated as an “all-in” solution that could be transferred and applied to all places at all times, but it entails the consideration and appreciation of the multi-faceted and distinct characteristics of: economic, technological, innovative, social, and cultural consideration. Only by incorporating and co-evaluating all these dimensions at an integrated level of allocated and case-specific weights could it result in effective and sustainable solutions for energy poverty eradication, energy justice implementation, energy safety provision, climate change mitigation, and public health protection, along with the abiding economic benefits and budgeting savings that can be achieved for local households and commercial energy consumers.
Energy poverty alleviation strategies implemented in line with the low-carbon energy transition should consider important determinants of multi-dimensional energy poverty and need to be better shaped and targeted, taking into account the diversity of households in terms of region, location, income, gender, age, education, behavioral factors, etc. The indicators of multi-dimensional energy poverty and other energy poverty frameworks were created to help decision-makers analyze the situation and assess the effectiveness of implemented policies and measures. Though there are dozens of indices and indicator frameworks created to evaluate energy poverty, there is no best indicator, as the phenomenon of energy poverty is highly context-dependent and for specific countries experiencing specific issues of energy poverty on a low-carbon energy transition path, the different indicators can be applied for energy poverty assessment and monitoring.
Future studies are necessary in the field of energy poverty and low carbon energy transition ranging from developed to developing economies is an important problem, however, the main difference between developed and developing economies approaching low carbon transition in terms of energy poverty as in developing countries energy poverty is mainly linked to energy affordability due to limited access to modern energy supply services. In developed economies, energy poverty is mainly linked to income poverty and increasing energy prices due to the fast penetration of renewables and world energy price shocks, though all households have access to modern energy services due to developed and advanced energy infrastructure. At the same time, people in developing countries are facing problems, such as low electrification rates and the use of environmentally harmful fuels for cooking, such as biomass; and the transition to low-carbon energy, which puts an additional burden on them.
Future research is necessary for analysis of multi-faceted energy poverty phenomena in low carbon energy transition by putting high priority for policies and measuring target alleviation of energy poverty in specific given context and regions that have their own problems and determinants of energy poverty.
In this respect, the inability to attain a socially and materially necessitated level of domestic energy services require energy policies and designers to consider specific energy demand claims in the residential domain, as that of: (A) Domestic energy deprivation is a multi-faceted issue that is predominately determined by the ineffective operation of the socio-technological pathways for covering household energy needs, and as such it should be utmost analyzed by a comprehensive understanding of the fundamentals and operation of different energy services, mainly that of heating and lighting, in homes. (B) The ability to conceptualize and value vulnerability aims at encapsulating the sources of domestic energy deprivation via comprehensive analytical matrices. Subsequently, the identification of the main components and the implications of offering energy services under conditions of vulnerability should relate to domestic energy deprivation worldwide. Conclusively, fuel- and energy-poverty should be considered as different forms of domestic energy circumstances that also impede social inclusion, modern lifestyles, customs, and activities that all identify contemporary societies. In such a way, energy services play a decisive role in people’s lives and nurture a “people-centred” approach to policymaking that stands beyond technical issues and should be driven to meet people’s needs and priorities in energy.

Author Contributions

D.S. and G.L.K. have contributed equally to this study. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. von Platten, J. Energy poverty in Sweden: Using flexibility capital to describe household vulnerability to rising energy prices. Energy Res. Soc. Sci. 2022, 91, 102746. [Google Scholar] [CrossRef]
  2. Siksnelyte-Butkiene, I. A Systematic Literature Review of Indices for Energy Poverty Assessment: A Household Perspective. Sustainability 2021, 13, 10900. [Google Scholar] [CrossRef]
  3. Drescher, K.; Janzen, B. Determinants, persistence, and dynamics of energy poverty: An empirical assessment using German household survey data. Energy Econ. 2021, 102, 105433. [Google Scholar] [CrossRef]
  4. Eisfeld, K.; Seebauer, S. The energy austerity pitfall: Linking hidden energy poverty with self-restriction in household use in Austria. Energy Res. Soc. Sci. 2022, 84, 102427. [Google Scholar] [CrossRef]
  5. Biernat-Jarka, A.; Trębska, P.; Jarka, S. The role of renewable energy sources in alleviating energy poverty in households in Poland. Energies 2021, 14, 2957. [Google Scholar] [CrossRef]
  6. Stojilovska, A.; Yoon, H.; Robert, C. Out of the margins, into the light: Exploring energy poverty and household coping strategies in Austria, North Macedonia, France, and Spain. Energy Res. Soc. Sci. 2021, 82, 102279. [Google Scholar] [CrossRef]
  7. Barrella, R.; Linares, J.I.; Romero, J.C.; Arenas, E.; Centeno, E. Does cash money solve energy poverty? Assessing the impact of household heating allowances in Spain. Energy Res. Soc. Sci. 2021, 80, 102216. [Google Scholar] [CrossRef]
  8. Boemi, S.N.; Samarentzi, M.; Dimoudi, A. Research of energy behaviour and energy poverty of households in Northern Greece. IOP Conf. Ser. Earth Environ. Sci. 2020, 410, 012083. [Google Scholar] [CrossRef]
  9. Horta, A.; Gouveia, J.P.; Schmidt, L.; Sousa, J.C.; Palma, P.; Simões, S. Energy poverty in Portugal: Combining vulnerability mapping with household interviews. Energy Build. 2019, 203, 109423. [Google Scholar] [CrossRef]
  10. Dogan, E.; Madaleno, M.; Taskin, D. Which households are more energy vulnerable? Energy poverty and financial inclusion in Turkey. Energy Econ. 2021, 99, 105306. [Google Scholar] [CrossRef]
  11. Chen, K.; Feng, C. Linking Housing Conditions and Energy Poverty: From a Perspective of Household Energy Self-Restriction. Int. J. Environ. Res. Public Health 2022, 19, 8254. [Google Scholar] [CrossRef]
  12. Chien, F.; Hsu, C.-C.; Zhang, Y.Q.; Vu, H.M.; Nawaz, M.A. Unlocking the role of energy poverty and its impacts on financial growth of household: Is there any economic concern. Environ. Sci. Pollut. Res. 2022, 29, 13431–13444. [Google Scholar] [CrossRef]
  13. Du, J.; Song, M.; Xie, B. Eliminating energy poverty in Chinese households: A cognitive capability framework. Renew. Energy 2022, 192, 373–384. [Google Scholar] [CrossRef]
  14. Huang, Y.; Jiao, W.; Wang, K.; Li, E.; Yan, Y.; Chen, J.; Guo, X. Examining the multidimensional energy poverty trap and its determinants: An empirical analysis at household and community levels in six provinces of China. Energy Policy 2022, 169, 113193. [Google Scholar] [CrossRef]
  15. Ma, R.; Deng, L.; Ji, Q.; Zhai, P. Environmental regulations, clean energy access, and household energy poverty: Evidence from China. Technol. Forecast. Soc. Change 2022, 182, 121862. [Google Scholar] [CrossRef]
  16. Qin, L.; Chen, W.; Sun, L. Impact of energy poverty on household quality of life—Based on Chinese household survey panel data. J. Clean. Prod. 2022, 366, 132943. [Google Scholar] [CrossRef]
  17. Xie, L.; Hu, X.; Zhang, X.; Zhang, X.-B. Who suffers from energy poverty in household energy transition? Evidence from clean heating program in rural China. Energy Econ. 2022, 106, 105795. [Google Scholar] [CrossRef]
  18. Wu, W.-P.; Zeng, W.-K.; Gong, S.-W.; Chen, Z.-G. Does Energy Poverty Reduce Rural Labor Wages? Evidence From China’s Rural Household Survey. Front. Energy Res. 2021, 9, 670026. [Google Scholar] [CrossRef]
  19. Abbas, K.; Li, S.; Xu, D.; Baz, K.; Rakhmetova, A. Do socioeconomic factors determine household multidimensional energy poverty? Empirical evidence from South Asia. Energy Policy 2020, 146, 111754. [Google Scholar] [CrossRef]
  20. Mathen, C.K.; Sadath, A.C. Examination of energy poverty among households in Kasargod District of Kerala. Energy Sustain. Dev. 2022, 68, 472–479. [Google Scholar] [CrossRef]
  21. Gupta, S.; Gupta, E.; Sarangi, G.K. Household Energy Poverty Index for India: An analysis of inter-state differences. Energy Policy 2020, 144, 111592. [Google Scholar] [CrossRef]
  22. Nathan, H.S.K.; Hari, L. Towards a new approach in measuring energy poverty: Household level analysis of urban India. Energy Policy 2020, 140, 111397. [Google Scholar] [CrossRef]
  23. Acharya, R.H.; Sadath, A.C. Energy poverty and economic development: Household-level evidence from India. Energy Build. 2019, 183, 785–791. [Google Scholar] [CrossRef]
  24. Qurat-ul-Ann, A.-R.; Mirza, F.M. Determinants of multidimensional energy poverty in Pakistan: A household level analysis. Environ. Dev. Sustain. 2021, 23, 12366–12410. [Google Scholar] [CrossRef]
  25. Son, H.; Yoon, S. Reducing energy poverty: Characteristics of household electricity use in Vietnam. Energy Sustain. Dev. 2020, 59, 62–70. [Google Scholar] [CrossRef]
  26. Omar, M.A.; Hasanujzaman, M. Multidimensional energy poverty in Bangladesh and its effect on health and education: A multilevel analysis based on household survey data. Energy Policy 2021, 158, 112579. [Google Scholar] [CrossRef]
  27. Dogan, E.; Madaleno, M.; Inglesi-Lotz, R.; Taskin, D. Race and energy poverty: Evidence from African-American households. Energy Econ. 2022, 108, 105908. [Google Scholar] [CrossRef]
  28. Simões, G.M.F.; Leder, S.M. Energy poverty: The paradox between low income and increasing household energy consumption in Brazil. Energy Build. 2022, 268, 112234. [Google Scholar] [CrossRef]
  29. Heynen, A.P.; Lant, P.A.; Sridharan, S.; Smart, S.; Greig, C. The role of private sector off-grid actors in addressing India’s energy poverty: An analysis of selected exemplar firms delivering household energy. Energy Build. 2019, 191, 95–103. [Google Scholar] [CrossRef]
  30. Robinson, C.; Yan, D.; Bouzarovski, S.; Zhang, Y. Energy poverty and thermal comfort in northern urban China: A household-scale typology of infrastructural inequalities. Energy Build. 2018, 177, 363–374. [Google Scholar] [CrossRef]
  31. Yadav, P.; Malakar, Y.; Davies, P.J. Multi-scalar energy transitions in rural households: Distributed photovoltaics as a circuit breaker to the energy poverty cycle in India. Energy Res. Soc. Sci. 2019, 48, 1–12. [Google Scholar] [CrossRef]
  32. Romero Rodríguez, L.; Sánchez Ramos, J.; Guerrero Delgado, M.; Molina Félix, J.L.; Álvarez Domínguez, S. Mitigating energy poverty: Potential contributions of combining PV and building thermal mass storage in low-income households. Energy Convers. Manag. 2018, 173, 65–80. [Google Scholar] [CrossRef]
  33. Assareh, E.; Hoseinzadeh, S.; Ghersi, D.E.; Farhadi, E.; Keykhah, S.; Lee, M. Energy, exergy, exergoeconomic, exergoenvironmental, and transient analysis of a gas-fired power plant-driven proposed system with combined Rankine cycle: Thermoelectric for power production under different weather conditions. J. Therm. Anal. Calorim. 2022. [Google Scholar] [CrossRef]
  34. Sonawane, C.R.; Panchal, H.N.; Hoseinzadeh, S.; Ghasemi, M.H.; Alrubaie, A.J.; Sohani, A. Bibliometric Analysis of Solar Desalination Systems Powered by Solar Energy and CFD Modelled. Energies 2022, 15, 5279. [Google Scholar] [CrossRef]
  35. Swierszcz, K.; Grenda, B.; Szczurek, T.; Chen, B. The importance of geothermal energy in energy security: Towards counteracting energy poverty of households. In Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019, Granada, Spain, 10–11 April 2019; Education Excellence and Innovation Management through Vision. 2020; pp. 771–781. [Google Scholar]
  36. Poblete-Cazenave, M.; Pachauri, S. A model of energy poverty and access: Estimating household electricity demand and appliance ownership. Energy Econ. 2021, 98, 105266. [Google Scholar] [CrossRef]
  37. Mohan, G. The impact of household energy poverty on the mental health of parents of young children. J. Public Health 2022, 44, 121–128. [Google Scholar] [CrossRef]
  38. Abbas, K.; Xu, D.; Li, S.; Baz, K. Health implications of household multidimensional energy poverty for women: A structural equation modeling technique. Energy Build. 2021, 234, 110661. [Google Scholar] [CrossRef]
  39. Ashagidigbi, W.M.; Babatunde, B.A.; Ogunniyi, A.I.; Olagunju, K.O.; Omotayo, A.O. Estimation and determinants of multidimensional energy poverty among households in Nigeria. Sustainability 2020, 12, 7332. [Google Scholar] [CrossRef]
  40. Olang, T.A.; Esteban, M.; Gasparatos, A. Lighting and cooking fuel choices of households in Kisumu City, Kenya: A multidimensional energy poverty perspective. Energy Sustain. Dev. 2018, 42, 1–13. [Google Scholar] [CrossRef]
  41. Odeku, K.O.; Meyer, E. Socioeconomic implications of energy poverty in South African poor rural households. Acad. Entrep. J. 2019, 25, 12. [Google Scholar]
  42. Zhang, Z.; Shu, H.; Yi, H.; Wang, X. Household multidimensional energy poverty and its impacts on physical and mental health. Energy Policy 2021, 156, 112381. [Google Scholar] [CrossRef]
  43. Olawumi Israel-Akinbo, S.; Snowball, J.; Fraser, G. An Investigation of Multidimensional Energy Poverty among South African Low-income Households. South Afr. J. Econ. 2018, 86, 468–487. [Google Scholar] [CrossRef]
  44. Mgwambani, S.L.; Kasangana, K.K.; Makonese, T.; Masekameni, D.; Gulumian, M.; Mbonane, T.P. Assessment of household energy poverty levels in Louiville, Mpumalanga, South Africa. In Proceedings of the 2018 International Conference on the Domestic Use of Energy, DUE, Cape Town, South Africa, 3–5 April 2018; pp. 1–7. [Google Scholar] [CrossRef]
  45. Terfa, Z.G.; Ahmed, S.; Khan, J.; Niessen, L.W.; on behalf of the IMPALA Consortium. Household Microenvironment and Under-Fives Health Outcomes in Uganda: Focusing on Multidimensional Energy Poverty and Women Empowerment Indices. Int. J. Environ. Res. Public Health 2022, 19, 6684. [Google Scholar] [CrossRef]
  46. Sharma, S.V.; Han, P.; Sharma, V.K. Socio-economic determinants of energy poverty amongst Indian households: A case study of Mumbai. Energy Policy 2019, 132, 1184–1190. [Google Scholar] [CrossRef]
  47. Aweke, A.T.; Navrud, S. Valuing energy poverty costs: Household welfare loss from electricity blackouts in developing countries. Energy Econ. 2022, 109, 105943. [Google Scholar] [CrossRef]
  48. Ye, Y.; Koch, S.F. Measuring energy poverty in South Africa based on household required energy consumption. Energy Econ. 2021, 103, 105553. [Google Scholar] [CrossRef]
  49. Murombo, T. Regulating energy in South Africa: Enabling sustainable energy by integrating energy and environmental regulation. J. Energy Natural Res. Law 2015, 33, 320–348. [Google Scholar] [CrossRef]
  50. Nduka, E. How to get rural households out of energy poverty in Nigeria: A contingent valuation. Energy Policy 2021, 149, 112072. [Google Scholar] [CrossRef]
  51. Longe, O.M.; Ouahada, K. Mitigating household energy poverty through energy expenditure affordability algorithm in a smart grid. Energies 2018, 11, 947. [Google Scholar] [CrossRef]
  52. Streimikiene, D.; Lekavičius, V.; Baležentis, T.; Kyriakopoulos, G.L.; Abrhám, J. Climate Change Mitigation Policies Targeting Households and Addressing Energy Poverty in European Union. Energies 2020, 13, 3389. [Google Scholar] [CrossRef]
  53. Awaworyi Churchill, S.; Smyth, R. Ethnic diversity, energy poverty and the mediating role of trust: Evidence from household panel data for Australia. Energy Econ. 2020, 86, 104663. [Google Scholar] [CrossRef]
  54. Boemi, S.-N.; Papadopoulos, A.M. Energy poverty and energy efficiency improvements: A longitudinal approach of the Hellenic households. Energy Build. 2019, 197, 242–250. [Google Scholar] [CrossRef]
  55. Lakatos, E.; Arsenopoulos, A. Investigating EU financial instruments to tackle energy poverty in households: A SWOT analysis. Energy Sources Part B Econ. Plan. Policy 2019, 14, 235–253. [Google Scholar] [CrossRef]
  56. Rus, A.V.; Rovinaru, M.D.; Pirvu, M.; Bako, E.D.; Rovinaru, F.I. Renewable Energy Generation and Consumption Across 2030—Analysis and Forecast of Required Growth in Generation Capacity. Transform. Bus. Econ. 2020, 19, 746–766. [Google Scholar]
  57. Ioannou, K.; Tsantopoulos, G.; Arabatzis, G.; Andreopoulou, Z.; Zafeiriou, E. A spatial decision support system framework for the evaluation of biomass energy production locations: Case study in Regional unit of Drama, Greece. Sustainability 2018, 10, 531. [Google Scholar] [CrossRef]
  58. Arabatzis, G.; Malesios, C. Pro-Environmental attitudes of users and not users of fuelwood in a rural area of Greece. Renew. Sustain. Energy Rev. 2013, 22, 621–630. [Google Scholar] [CrossRef]
  59. Zografidou, E.; Petridis, K.; Petridis, N.; Arabatzis, G. A financial approach to renewable energy production in Greece using goal programming. Renew. Energy 2017, 108, 37–51. [Google Scholar] [CrossRef]
  60. Istudor, N.; Dinu, V.; Nitescu, D.C. Influence Factors of Green Energy on EU Trade. Transform. Bus. Econ. 2021, 20, 116–130. [Google Scholar]
  61. Du, J.; Peng, S.; Song, W.; Peng, J. Relationship between Enterprise Technological Diversification and Technology Innovation Performance: Moderating Role of Internal Resources and External Environment Dynamics. Transform. Bus. Econ. 2020, 19, 52–73. [Google Scholar]
  62. Bouzarovski, S.; Petrova, S. A global perspective on domestic energy deprivation: Overcoming the energy poverty-fuel poverty binary. Energy Res. Soc. Sci. 2015, 10, 31–40. [Google Scholar] [CrossRef]
  63. Hasheminasab, H.; Streimikiene, D.; Pishahang, M. A novel energy poverty evaluation: Study of the European Union countries. Energy 2023, 264, 126157. [Google Scholar] [CrossRef]
  64. Nguyen, C.P.; Su, T.D. The influences of government spending on energy poverty: Evidence from developing countries. Energy 2022, 238, 121785. [Google Scholar] [CrossRef]
  65. Abbas, K.; Butt, K.M.; Xu, D.; Ali, M.; Baz, K.; Kharl, S.H.; Ahmed, M. Measurements and determinants of extreme multidimensional energy poverty using machine learning. Energy 2022, 251, 123977. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.