Exploring Energy Poverty among Off-Grid Households in the Upper Blinkwater Community, South Africa

Abstract

This paper explores energy poverty and its distribution among households in the Upper Blinkwater community, a typical remote South African community. Its selection was based on being the first identified to benefit from the pilot project implementing a decentralized hybrid mini-grid. We utilize the Foster–Greer–Thorbecke technique, which identifies households below the energy poverty line, measures the depth, and identifies those most vulnerable to energy poverty. A total of 53 households were interviewed by means of a questionnaire. The findings indicate a reliance on diverse energy sources such as wood for heating and LPG for cooking, which has enhanced community resilience and control over energy consumption, with greater proportions not affected by energy poverty. However, about 38% still experience energy poverty. The findings show that energy poverty is unevenly distributed within the community. Older individuals tend to have greater energy security, likely due to the stability provided by social grants. In contrast, female-headed households and lower-income families face the most significant challenges. The study concludes that there are substantial gender disparities and that lower-income households are particularly vulnerable to energy poverty. Therefore, we recommend gender-sensitive interventions to reduce the financial burdens on these vulnerable households, thereby improving their energy security.

1. Introduction

Energy poverty is a concept encompassing the lack of access to modern energy services, with significant impacts on individuals and households. It can manifest in various ways, from complete absence to insufficient access at a socially and financially necessary level within a household [1,2,3,4]. This definition resonates with the majority of the South African population, who have been marginalized and denied basic services due to the legacies of political history. Despite its commendable strides in energy provision, with an electrification rate of over 86%, placing it at the forefront among other sub-Saharan countries [5], it is difficult to imagine that there are still millions of households in South Africa deprived of secure access to electricity and modern energy services, leaving over 50% of the population vulnerable to its impacts [6]. Most affected are those in off-grid and rural areas where poverty levels are much higher [6,7], with approximately 3.5 million households remaining disconnected from the grid. Unfortunately, expanding infrastructure in remote regions presents significant challenges, making it difficult to ensure access to electricity and modern energy services for these communities [8]. Even in cases where electrification has been achieved through non-grid connections, it has proven ineffective in providing thermal energy for cooking and space heating [9].

The Eastern Cape has the lowest grid connection level in South Africa, with a rate of 64.5% [10]. Based on estimates from local sources, 25% of all communities in the Eastern Cape will be connected to the grid in 8 to 15 years at the earliest [11]. The situation has significant implications for the well-being of off-grid communities and the local economy. In the absence of access to electricity and modern energy amenities, communities frequently rely on inefficient and polluting alternatives like wood, coal, or paraffin for cooking and lighting. This continued use of biomass fuels is an alarming issue that must be addressed with urgency, given that it leads to indoor air pollution and causes severe health issues, resulting in more fatalities than tuberculosis, malaria, or other infectious illnesses [12]. The statistics are shocking, with approximately 1.1 million deaths attributed to household air pollution in Africa. In South Africa, the use of paraffin as a source of energy is a significant hazard, resulting in approximately 5000 shack fires and 2000 deaths every year [13]. Moreover, the use of traditional energy sources contributes to environmental degradation, perpetuating the impacts of climate change [14].

Energy poverty not only poses health risks but also hampers various facets of development in affected communities. It limits educational opportunities, hindering children’s ability to study effectively and restricting access to digital resources crucial for modern-age learning. This perpetuates intergenerational poverty and exacerbates inequalities by denying marginalized communities the tools needed to compete in a rapidly evolving global economy. Moreover, the lack of access to electricity restricts the use of productive resources, stifles the growth of small businesses, and impedes the adoption of technologies that could enhance agricultural productivity and food security, further perpetuating cycles of poverty [1,15]. Energy poverty also causes low-income households to spend a higher percentage of their household income on energy than middle-income households [16].

Addressing the energy access issue is therefore not just a matter of ensuring access to basic amenities; it is essential for unlocking the full potential of these communities and catalysing sustainable development. However, a significant gap in the existing literature, particularly in areas like the Eastern Cape, is the limited understanding of the extent of energy poverty and how it is distributed within off-grid communities. Previous studies [7] primarily focused on analysing energy poverty through the lens of electricity access and usage, leaving a significant gap in understanding the socio-economic factors contributing to energy deprivation within these communities. Furthermore, there is a dearth of information regarding the distribution of energy poverty within these off-grid areas. This poses a significant challenge for the government in determining which factors to target and prioritize. This study builds on the work of [17], extending the energy poverty analysis beyond simply identifying specific drivers of energy poverty. Instead, it places greater emphasis on understanding how energy poverty varies across different households and addresses the gap in the literature. Such analysis can reveal the specific needs and challenges faced by various demographic and socioeconomic groups. For policymakers, this information is crucial for developing more effective and equitable energy access strategies. This, in turn, can improve the relevance and impact of policies and provide adequate support to the most vulnerable populations, addressing Target 7.1 of the Sustainable Development Goals (SDG) 7, which seek to ensure universal access to affordable, reliable, and modern energy services.

The rest of the paper is organized as follows: Section 2 discusses policy intervention for the mitigation of energy poverty in South Africa. Section 3 presents a review of the literature. Section 4 discusses the methods used for collecting and analyzing data. Section 5 presents the study findings and their interpretation. Section 6 discusses the results in detail. Finally, Section 7 provides the conclusions and recommendations.

2. Pro-Poor Energy Policy in South Africa

It is commendable that the South African government recognizes the issue of energy poverty and is committed to ensuring that all citizens have access to modern energy services. The National Development Plan (NDP) outlines this commitment and aims to achieve universal energy access by 2030. This is a significant step towards addressing the disparities in energy poverty and improving the well-being of its population. Since democratic rule in 1994, South Africa has implemented several energy policies, such as the 1998 Energy White Paper policy, aimed at making electricity accessible and available to low-income and rural areas [18]. Subsequent policies such as the Integrated National Electrification Plan (INEP) program were implemented to actualize the objectives of the White Paper, and since its implementation, the electrification rate remarkably increased from 42% in 2002 to 89.3% in 2021 [5], placing South Africa at the forefront among other sub-Saharan countries. Figure 1 illustrates the electrification rates in South Africa, providing the progress made in expanding access to electricity.

Nonetheless, despite the overall progress and noticeable improvements, especially in rural areas, as depicted in Figure 1, the reality remains that many remote rural communities still lack access to electricity [17]. Logistical and financial constraints persistently impede grid expansion efforts across various parts of the country [20], perpetuating energy poverty for millions. It is unfortunate that, for a number of reasons, including affordability and reliability, even many that are connected to the grid cannot afford the electricity they have access to [21,22], leaving them vulnerable to the impacts of energy poverty. Lee et al. [23] investigated access to and reliability of electricity in a number of countries, including South Africa. Figure 2 paints a clear picture of the challenges South African households face with accessing energy that is reliable.

The data on the Figure 2 shows that a significant proportion (9%) of the population in South Africa is not grid connected, leading to limited access to reliable energy sources. Even in areas where households are connected to the grid, a substantial portion (20%) of them experience intermittent energy supply, impacting their daily lives and hindering their ability to access essential service, pressing the need for sustainable solutions to ensure consistent and dependable energy availability for all residents. This can be expected as the rising energy prices disproportionately increase the financial burden, and the most affected are the poor and low-income households, prompting them to cut back on energy consumption [24]. It has been shown that, on an annual average, electricity prices in South Africa have more than doubled since 2008 compared to the sluggish average consumer price index (CPI) [25]. As a result, about 43% of South African households spend more than 10% of their income on electricity [6]. Figure 3 shows trends in electricity prices versus the consumer price index (CPI) for the period 2008–2021.

The data provided in Figure 3 confirms the steady increase in average electricity over the years, outpacing the CPI. Although demand for energy may be price-inelastic in the long run, spending a greater proportion of income on energy expenses can lead to increased financial burden and stress on households, affecting their ability to meet other essential needs and save for the future. This could lead to a decrease in their standard of living, as they may have to cut back on discretionary spending, reduce food consumption, and compromise on healthcare expenses. This may sometimes force households to make difficult choices, such as forgoing necessary home improvements or even experiencing housing instability [16].

On its commitment to the delivery of basic energy services and enabling households to consume more electricity, the Free Basic Energy (FBE) program was implemented in 2003 to provide 50 kWh of electricity per month free to eligible households connected to the grid. This initiative has had some success in providing basic energy services to households and allowing them to consume more electricity [27]. However, there are still significant challenges to overcome, particularly in rural areas where poverty levels are much higher and infrastructure is lacking. For off-grid communities without electricity infrastructure, the Free Basic Alternative Energy Policy (FBAE) provides a monthly subsidy of ZAR 56.29 (equivalent to USD 3.09) for alternative energy forms such as paraffin, coal, liquefied petroleum gas (LPG), and ethanol gel [28]. Where solar home systems (SHSs) were installed, a flat monthly fee of ZAR 58 (equivalent to USD 3.18) is payable for the service. The government then committed to a monthly ZAR 40 subsidy for concessionaires, leaving households with only ZAR 18 (equivalent to USD 0.99) [26]. However, while these policies are sound in principle, irregularities in the implementation and registration processes have hampered their effectiveness, resulting in limited results and leaving many households without assistance [29,30]. Some eligible households are not benefiting from the subsidy, and only about 69% of eligible households actually receive an energy subsidy [30]. In addition, the energy poverty criterion used to determine the indigent excludes a larger proportion of households that are actually classified as poor under the national poverty line [31]. Meanwhile, many households continue to rely on traditional energy sources to supplement their electricity needs.

Moreover, South Africa has grappled with multiple periods of rolling blackouts, with the phenomenon of load shedding persisting since 2007, as the country’s demand for electricity consistently surpasses the available supply [26]. This highlights the need for South Africa to diversify its energy mix and invest more in reliable and sustainable energy sources to ensure energy security, especially in these times when the country is in a very critical phase where local discontent is brewing, and the population is showing signs of impatience over service delivery and energy provision. Energy provision is an important step not only in addressing the social unrest that the country has experienced since 2006 [32] but also as a necessary component of modernization [33]. To enhance its efforts, South Africa can learn from the successes of other nations that have effectively tackled similar issues. India and Bangladesh have implemented successful off-grid renewable energy programs that have reached millions of households in rural areas. However, South Africa, despite having abundant renewable energy resources such as solar and wind energy, faces challenges in implementing similar programs due to a lack of a regulatory framework, social acceptance of community-based mini-grids, and financial sustainability challenges. Additionally, there are financial sustainability challenges for mini-grids, as many households in rural areas may not be able to afford the upfront costs of connecting to a mini-grid [6]. Nonetheless, lessons can be learned from Kenya through the pay-as-you-go (PAYG) model for solar home systems. This model has revolutionized access to energy by allowing households to pay for their energy services incrementally, thereby reducing the initial costs associated with acquiring solar systems [34].

In Brazil, starting in 2003, the government introduced LPG as a replacement for traditional biomass fuels through the Gas Voucher program, also known as the Bolsa Família Gas (Family Allowance Program). This initiative provides cash transfers to poor households, assisting them in purchasing LPG for cooking purposes, aiming to enhance access to cleaner cooking fuels and reduce reliance on traditional biomass [35].

Conversely, South Africa has implemented the Free Basic Electricity (FBE) policy, which provides a certain amount of free electricity to qualifying low-income households. However, there is not an equivalent program specifically for LPG like the Gas Voucher program in Brazil. South Africa’s focus has been primarily on the provision of electricity rather than subsidizing LPG for cooking purposes, reflecting a different approach to energy access and poverty alleviation.

Additionally, Brazil has seen the development of community-based energy projects that offer an innovative approach to renewable energy adoption. These projects allow multiple participants to collectively own and benefit from larger offsite photovoltaic (PV) systems. Through this model, consumers can purchase shares or subscriptions to the energy generated, thereby overcoming barriers associated with traditional individual rooftop installations. This communal approach not only facilitates broader access to renewable energy but also promotes community engagement and shared benefits in the transition to sustainable energy sources [35,36]. Mukumba and Chivanga [6] are of the view that energy poverty in rural areas of South Africa is not uniquely linked to a lack of renewable energy sources but linked to biased policies and technological issues. Then, there is an opportunity for South Africa to glean insights from the experiences of countries like Germany and Denmark. These nations have successfully implemented renewable energy policies, such as feed-in tariffs, which incentivize the production of renewable energy, and have made significant investments in research and development of renewable energy technologies [36,37]. Drawing from these experiences and integrating them into its energy poverty policy while heightening renewable energy efforts will not only assist South Africa in crafting efficient policies and initiatives to address energy poverty but also account for its climate commitment target of net-zero emissions by 2050 [26].

3. Literature Review

Energy poverty is increasingly gaining attention due to its widespread impacts on social equity, economic development, and environmental sustainability. This heightened awareness is driven by the realization that energy is no longer just a luxury but an indispensable commodity enabling individuals to engage meaningfully in social, economic, and cultural activities [38], without which they risk exclusion (Tamás Mesmerises, 2016 [38]). Scholarly interest has grown in understanding and debating the most appropriate criteria for identifying and quantifying energy poverty. The complexity emerges from the various indicators used to capture its multifaceted nature [39]. One primary indicator emphasizes the lack of access to electricity and the reliance on non-clean cooking fuels. Another considers the proportion of income spent on energy, reflecting the economic burden on households and potential trade-offs with essential needs [40,41,42]. Moreover, there is a recognition that energy poverty may not be solely defined by any single factor but rather as a combination of these components [43], also depending on geographical context and socio-economic conditions [39]. Hence, [44,45] offer specific definitions highlighting the broader implications of energy poverty beyond mere lack of energy, emphasizing the importance of access to energy services for basic household functioning and overall well-being.

Boardman [44] defines it as “when a household cannot afford domestic heating and other energy services in cases where it needed to spend more than 10 per cent of its income”.

Bouzarovski and Petrova [45] defined it as “when a household is unable to secure materially and socially necessitated levels of domestic energy services”.

These definitions recognize that energy services, including heating, lighting, and powering appliances, are essential for basic household functioning and overall well-being, linking energy poverty to the inability to afford sufficient heating or cooling, and beyond access to electricity and clean cooking solutions to also include factors like energy affordability, reliability, and quality, affecting nearly 2.6 billion people globally, with Sub-Saharan Africa being the most deprived of electricity access [46].

For developing countries, energy poverty often involves lack of electricity access and reliance on traditional biomass, leading to adverse health outcomes due to indoor air pollution. Efforts addressing it typically prioritize infrastructure expansion, renewable energy promotion, and policies facilitating affordable access to modern energy services [4]. This reality persists in many South African households, where infrastructure struggles to meet current energy demands, with millions of households not connected to the grid, while approximately half of all households in South Africa struggle to meet their basic energy requirements [47]. On average, South Africans spend 14% of their income on energy [36], with the poorest allocating about 27%, compared to the rich who spend only 6% [37,47]. The authors of [48] found that more than 50% of households in South Africa were affected by energy poverty. There has also been a decline in electricity per capita values since 2007, a rate six times higher than in other Southern African countries. This decline suggests that, despite policies like the Free Basic Electricity (FBE) program, the overall consumption of electricity per person is decreasing. At the same time, total energy consumption has been decreasing since 2017 at a rate of 1.5% per year. This highlights the ongoing challenges in ensuring adequate and reliable energy access for all households in South Africa [46]. Furthermore, [49] observed a declining use of clean energy for cooking, water heating, and space heating from 2019 to 2021. This decline indicates that households in South Africa have been increasingly relying on less clean or more polluting energy sources, such as coal, wood, or kerosene, rather than cleaner alternatives like electricity, natural gas, or renewable energy. This shift could be due to economic constraints, rising energy costs, or supply issues, further complicating efforts to address energy poverty in the country.

While defining and measuring energy poverty remain subjects of scholarly debate, the reality of their impacts is undeniably detrimental; recent research indicates that marginalized communities, including rural populations, women, and ethnic minorities, disproportionately bear the effects of energy poverty. For example, ref. [5] examined the issue of gendered energy poverty by focusing on rural women in unelectrified areas of Limpopo, Mpumalanga, and KwaZulu-Natal provinces, investigating the interaction between gender and energy poverty. The study revealed that gendered energy poverty affected women and girls the most at varying levels of severity due to culturally assigned gender roles, such as the task of collecting unclean fuels like firewood to meet their households’ energy needs. This task exposes them to unfavourable conditions, including health issues, time and income poverty, illiteracy, and even premature deaths. The authors of [50] also explored the differing levels of energy poverty experienced by female-headed households of different races and ethnicities. They found that Black/African female-headed households were more exposed and had lower vulnerability to energy poverty compared to women of Colour. The authors of [51,52] found that Black South Africans are more affected by energy poverty due to limited economic opportunities compared to other racial groups. Their analysis suggests that ineffective subsidies contribute to this disparity, calling for a more equitable allocation of resources. These studies suggest that both the gender of the household head and the race or ethnicity significantly interrelate with energy poverty, creating unique challenges and vulnerabilities regarding access to energy depending on who bears the responsibility of securing energy resources. This situation not only perpetuates gender inequality but also exposes women and girls to additional barriers such as poorer access to infrastructure, economic opportunities, and social services, exacerbating their energy poverty.

The authors of [53], on the other hand, contribute to the understanding of energy poverty and its impacts, particularly within informal settlements like the Alexandra township. Building upon existing research, ref. [53] highlights the prevalent challenges faced by residents, particularly those living in backyard shacks, where issues of affordability and access to grid infrastructure are pronounced. Despite South Africa’s commendable electrification efforts, Masuku underscores the persistent nature of household-level energy poverty, with households nationwide unable to meet their basic energy needs. Therefore, we advocate the importance of energy stacking using multiple energy sources to support livelihoods in low-income households.

The authors of [54] examine how informal settlements’ lack of basic services leads to reliance on harmful energy sources, resulting in unhealthy living conditions. The authors of [54] highlight the pervasive effects of energy poverty in South Africa, which result in discrimination against residents of informal settlements and perpetuate socioeconomic disparities from the apartheid era. They argue that the interests of marginalized communities are often overshadowed by those of historically wealthy groups, the new Black middle class, and the professional elite. This situation underscores the government’s responsibility to fulfil its promise of providing a better life for all South Africans by addressing the marginalization and deprivation faced by these communities. The authors of [54] suggest that ending this marginalization is crucial for ensuring that all citizens benefit from social and economic opportunities, and they contend that the true measure of democracy in post-apartheid South Africa lies in how well it addresses these deep-rooted disparities and improves the living conditions of its most vulnerable populations.

Overall, while interventions have been implemented to alleviate energy poverty, success has been limited to date, and persistent inequalities in access to energy and the impacts of energy poverty continue to be felt [55]. Yet, the literature examining this phenomenon remains limited in South Africa. Several studies have assessed and attempted to quantify the prevalence of energy poverty and its associated determinants. While indicators like electricity access are commonly used to describe energy poverty, research has predominantly focused on areas with grid connections, leaving off-grid areas largely unexplored. Consequently, the experiences of households without electricity connections, who often rely on traditional biomass and face severe health and economic challenges, remain underrepresented in the current body of research. Moreover, methodologically, existing studies have employed the expenditure-based approach also known as the Tenth-Percentile Rule and the MEPI, capturing the multiple indicators of energy poverty. This measure may not fully address the challenges faced in developing economies, where both affordability and accessibility are significant issues. This claim holds true, especially in rural areas of South Africa, where access to electricity remains a major obstacle.

The authors of [56] propose the Foster–Greer–Thorbecke (FGT) approach as an alternative method to assess energy poverty. Unlike other approaches that simultaneously consider multiple and energy-related dimensions, the FGT approach suggests a single indicator incorporating all aspects of energy consumption, acknowledging that actual energy expenditure may not always accurately reflect energy poverty, especially for low-income households. As [56] highlights, low-income households may limit their energy consumption to prioritize other essential needs, or they may allocate a smaller proportion of their income to certain selected services such as refrigeration and TV while seeking cheaper alternatives for cooking and heating. In contrast to a fixed energy poverty line, the FGT approach establishes household-specific energy poverty lines. This energy poverty line aids in determining the proportions of households living below the poverty line threshold while allowing for further investigation into how far below the poverty line households are [56].

This study is conducted within the principles of the FGT, recognizing that energy poverty is not uniform and can vary significantly based on household characteristics. The section following this discusses the methodologies outlining the approaches for data acquisition and analysis.

4. Materials and Methods

4.1. Study Area

The study was conducted in the Upper Blinkwater community. Upper Blinkwater is located is located about 23 km north of Fort Beaufort, a small, urbanized town in the mountains of the Raymond Mhlaba, about 900 m above sea level on a higher plateau at 32°34′46.7″ S and 26°33′33.8″ E. Raymond Mhlaba Local Municipality is a rural area that relies heavily on the agricultural sector, including citrus, forestry, livestock, and crop production. In addition to its economic activities, the municipality has a rich cultural heritage, with historical education institutions such as Healdtown, Lovedale College, and the University of Fort Hare; however, these sites are underutilized as tourism or cultural sites [57]. The municipality is characterized by scattered settlements; it faces significant challenges such as infrastructure issues, and due to limited infrastructure and challenging accessibility, economic opportunities in the municipality are limited, resulting in high levels of poverty and unemployment. As a result, many households rely on social grants as their primary source of income [58,59].

The Upper Blinkwater community was selected for this study because it represents a typical remote community in South Africa that faces significant energy poverty due to its lack of infrastructure and connectivity to the nearest town. The community consists of approximately 67 households, predominantly of Xhosa descent, with a total population of about 254 people, and it currently has no access to the main national grid.

Moreover, this community has been chosen as the first community to benefit from a renewable energy pilot project aimed at implementing a hybrid mini-grid as a solution to rural electrification in South Africa [11]. Focusing on this community allows for the establishment of a comprehensive baseline understanding of its energy poverty, providing insights into the current state of energy access in remote South African communities and setting the stage for assessing the impact of decentralized renewable energy solutions, which is crucial for evaluating the effectiveness of the intervention. The geographical position of Upper Blinkwater is shown in Figure 4.

4.2. Research Design and Sampling

The study adopted a cross-sectional research design. This approach allows for the collection of data from different households at a single point in time. It also helps capture data on multiple variables simultaneously, allowing exploration of energy poverty dynamics by examining residents’ energy usage patterns, expenditures, and various demographic and socioeconomic factors. This type of data enables us to conduct statistical analyses to determine if there were any statistically significant relationships or differences between variables within the sample population, offering insights into the dynamics of energy usage and distribution within the studied population.

Since Upper Blinkwater has a small population size, drawing a sample was impractical and could have resulted in insufficient data for meaningful conclusions [60]. To prevent misrepresentation of the data, all households in this community were included in the survey. However, due to logistical constraints, only 53 households, represented by their household heads, were interviewed based on respondents’ availability and willingness to participate.

The survey was conducted in November 2019 using a questionnaire designed to gather information on various aspects of energy usage. The questionnaire contained questions about the types of energy currently used by the respondents, along with their respective uses, prices, transportation costs, and quantity, that is, how often the energy source is obtained per month. In terms of energy uses, according to [16], energy plays a crucial role in everyday activities such as cooking, lighting, heating, cooling, and refrigeration, linking energy access to health and economic productivity. They assert that susceptibility to any of these factors not only compromises their well-being but also has cascading effects on their economic productivity. In light of this perspective, questions on energy uses included enquiries on energy used for cooking, lighting, heating, cooling, and refrigeration. Demographic factors such as age, gender, and household size were also recorded, along with socio-economic information including education levels, sources of income, and each source’s contribution to the total household income.

Following data collection, thorough cleaning procedures were implemented to ensure data accuracy. The collected data were then analysed using STATA software version 15, and the results are presented in tables and figures, providing a clear picture of the energy consumption patterns, demographic characteristics, and socio-economic factors within the Upper Blinkwater community.

4.3. Assessment of Energy Poverty

This study utilizes the Foster–Greer–Thorbecke (FGT) poverty measure, an aggregated unidimensional metric, measuring the prevalence and depth of energy poverty. The FGT index is a family of poverty measures proposed by Foster, Greer and Thorbecke in 1984 [61]. It measures the headcount ratio, which denotes the proportion of households or individuals existing below the poverty line, offering a clear number of those impacted by poverty, and the poverty delineates the extent to which households fall short of the poverty line, expressed as a fraction of the poverty threshold, showing the depth of poverty, portraying the degree of economic deprivation experienced by individuals. Lastly, the poverty severity index, which accounts for both the depth of poverty and the inequality among the poor, who are those with incomes much lower than the poverty line, has a larger squared gap, highlighting severe deprivation and inequality among the poor. This is an important tool in order to identify the most vulnerable groups of households [62]. The FGT measure traditionally focuses on either income or consumption expenditure to assess poverty levels. Its measure relies on the poverty gap, which is the disparity between the poverty line and the actual income or expenditure of households that fall below the poverty threshold [24]. To incorporate energy poverty, the energy poverty gap is calculated using household expenditures on energy services and the energy poverty line. This gap represents the income a household spends on energy services beyond the energy poverty line. For households with expenditures above the fuel poverty line, the energy poverty gap is a positive real number; otherwise, it is zero [24].

The inclusion of the energy poverty line within the FGT framework offers several advantages. Unlike fixed expenditure-based thresholds, which may lack objectivity or comparability across income levels, the FGT approach provides a household-specific poverty line, tailored to individual circumstances [63]. This personalized assessment considers factors such as household size, composition, and energy consumption needs, resulting in a more accurate evaluation of energy poverty across diverse populations. The energy poverty line, derived from mean per capita consumption expenditure on energy use [64], reflects actual spending patterns [65] and captures the affordability threshold for energy services [63,66]. The FGT poverty measure is expressed as:

$${\mathrm{F}\mathrm{G}\mathrm{T}}_{\mathrm{p}}={\left(\frac{1}{\mathrm{N}}{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\left(\frac{{\mathrm{y}}_{\mathrm{i}}}{\mathrm{z}}\right)}^{\mathrm{p}}\right)}^{\frac{1}{\mathrm{p}}}$$

(1)

where ${\mathrm{F}\mathrm{G}\mathrm{T}}_{\mathrm{p}}$ is the FGT poverty measure with parameter p, N is the total number of individuals or households, y_i is an individual’s or household’s expenditure, z is the poverty line, and p is the parameter that determines the sensitivity of the measure to poverty at different income levels.

For assessing energy poverty among households without electricity, the FGT examines the distribution of energy expenditure relative to the energy poverty line. The FGT index of energy poverty, denoted as F(α,E), is calculated as:

$$\mathrm{F}(\mathsf{\alpha },\mathrm{E})=\frac{1}{\mathrm{N}}{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\left(\frac{y_{\mathrm{i}}}{\mathrm{E}}\right)}^{\mathsf{\alpha }}$$

(2)

where $\mathrm{F}(\mathsf{\alpha },\mathrm{E})$ represents the FGT index of energy poverty, which quantifies the level of energy poverty among households. α is a parameter that determines the sensitivity of the index to changes in the distribution of energy expenditure. A higher value of α indicates greater sensitivity to variations in energy expenditure among households. y_i is the per capita energy expenditure of household i, representing the amount spent on energy needs by each household. E is a certain level or threshold of energy expenditure, defined as two-thirds of the mean per capita expenditure on energy use within the community. By comparing each household’s per capita energy expenditure to the average per capita energy expenditure without electricity, raised to the power of α, and averaging across all households, Equation (2) quantifies the level of energy poverty. The FGT approach categorizes households based on their capacity to meet energy requirements, with the severity of energy poverty increasing with higher values of the FGT index F(α,E).

In this case, the energy poverty threshold, as defined by [51], is set at two-thirds of the mean per capita expenditure on energy use. That is to say, households whose monthly energy expenditure meets or exceeds the energy poverty line (E) are classified as non-poor in terms of energy. Then any households with expenditures below the energy poverty line but higher than one-third of the mean per capita expenditure are categorized as moderately energy-poor, while spending less than one-third of the mean per capita expenditure on energy are considered extremely energy-poor [66]. The higher the value of the FGT index (F(α,E)), the more severe the energy poverty among the respondents [67].

5. Results

5.1. Socioeconomic Profile of the Respondents

Table 1. The socioeconomic composition of the respondents.

Variable	Mean	Standard Deviation (SD)	Min.	Max.
Age	52.4	17.6	24	101
Household Size	3.4	2.06	1	8
Wages	552.8	967.7	0	3500
Grant	1093.6	1310.3	0	5500
Remittance	454.7	1073	0	4300
Own Business	220.8	1127.5	0	8000
Monthly Income	2321.9	1990.1	0	8890

Income amount is expressed in rands per month (ZAR).

shows the socioeconomic composition of the respondents. Based on the data, the respondents exhibited a diverse socioeconomic profile. The average age of respondents was 54.4 years (SD = 17.6), indicating a middle-aged demographic with considerable age variability. The data revealed variations in household sizes, with an average of 3.4 members (SD = 2.06).

In terms of income sources, the data reveals a diverse range of economic activities among respondents in the Upper Blink Water community, each contributing varying amounts to household income. Specifically, employed respondents earned an average monthly salary of approximately ZAR 552.83 (equivalent to USD 30.38). Remittances also play a significant role in contributing to household income, with an average monthly contribution of ZAR 454.7 (equivalent to USD 24.98), which indicates the importance of financial support from family members or relatives living elsewhere. Self-employment demonstrates entrepreneurial efforts within the community, where individuals engage in various small-scale businesses or ventures to generate income independently, and it emerged as another income-generating activity, with self-employed individuals generating at least ZAR 220.6 (equivalent to USD 12.12) per month on average.

Grants also play a significant role in contributing to the monthly income of respondents, with the mean amount being substantial compared to other sources such as wages, remittances, or earnings from their own businesses. The mean amount received through grants is ZAR 1093.6 (equivalent to USD 60), with a standard deviation of ZAR 1310.3 (equivalent to USD 71.9). This indicates a notable variation in the amounts received, ranging from ZAR 0 to ZAR 5500 (equivalent to USD 302.19). Grants serve as an important social safety net, providing financial support to individuals and families, especially those with lower incomes or facing economic challenges.

The data reveal a mean monthly income of ZAR 2321.9 (equivalent to approximately USD 127.58) among the respondents, with a wide range of total monthly incomes spanning from ZAR 0 to ZAR 8890 (equivalent to approximately USD 488.46). This broad income range highlights significant income disparities existing among households within the Upper Blinkwater community. The mean income of ZAR 2321.9 suggests a moderate level of overall income within the community. However, the wide range of incomes, reaching up to ZAR 8890, indicates substantial variation in individual earning capacities and financial circumstances among respondents. This may imply that while some households may have higher incomes and may have relatively stable incomes, others may experience financial constraints and lower income levels and may face challenges in meeting basic needs.

5.2. Findings on Energy Sources and Their Usage

The findings in this section provide insight into the various types or sources of energy used within the Upper Blinkwater community, as well as the specific purposes for which these energy sources are utilized, such as cooking, heating, lighting, cooling, and refrigeration. In view of [4,16], it is essential to note that Upper Blinkwater operates off-grid, meaning it lacks access to centralized electricity. Consequently, activities such as cooling and refrigeration systems were not prevalent, while cooking, lighting, and heating remained essential energy uses.

Table 2. Distribution of energy source and usage among respondents.

Energy Type	Energy Statistics
	No. of Respondents	Mean	Standard Deviation (SD)
Wood	51	0.96	0.192
Paraffin	49	0.92	0.267
LPG	45	0.85	0.478
Candles	50	0.94	0.233
Diesel (Generator)	7	0.13	0.361
Solar	2	0.04	0.342

provides a description of the energy sources utilized by respondents in the Upper Blinkwater community. The data show a number of energy types being used, which included firewood, paraffin, liquefied petroleum gas (LPG), candles, and generators.

Figure 5 presents the energy use of the respondent. In Figure 5, firewood emerged as the predominant energy source in the Upper Blinkwater community, with a substantial majority of 15 households (96.2%, SD = 0.192) relying on it primarily for two main purposes: space heating (79.2% of households) and cooking (73.6% of households). Despite advancements in technology and access to modern energy sources, firewood continues to play a critical role as the primary fuel for meeting essential household needs such as space heating and cooking. However, LPG appeared to be the most commonly used fuel for cooking, with 45 households (representing approximately 79.2% of users) primarily utilizing it for this purpose. LPG is commonly used, even more than paraffin, which ranked second in prevalence among energy sources, and was relied upon by a significant portion of 49 households (92.5%, SD = 0.267) for various essential purposes. Specifically, paraffin was predominantly used for providing lighting (92% of households), cooking (41.5%), and space heating (18.9% of households). The widespread utilization of paraffin highlights its importance in fulfilling critical energy needs across different aspects of daily life among respondents in the Upper Blinkwater community.

Overall, the reliance on firewood for space heating and cooking, coupled with the popularity of LPG for cooking and the multifunctional use of paraffin, indicates the diverse energy situation and the strategic choices made by households to meet their essential energy requirements.

Candles, on the other hand, were predominantly utilized for lighting purposes in approximately 50 households (94.3%, SD = 0.233) within the Upper Blinkwater community, indicating a significant reliance on candles as an energy source for illumination among a notable portion of households. In comparison to paraffin, the use of candles suggests a slightly higher adoption rate than paraffin. This indicates that candles serve as a popular alternative or supplementary lighting option alongside paraffin. The choice to use candles may be influenced by factors such as convenience, availability, or affordability, particularly in households where paraffin use may not fully meet lighting needs or where candles are perceived as a more suitable option for specific situations. While paraffin remains a common and versatile energy source utilized for multiple purposes, including lighting, cooking, and space heating, the use of candles demonstrates how households diversify their energy sources.

Based on the data, only about 13.2% of households used a diesel generator, and merely 3.8% of households used solar energy, although only for lighting and charging cell phones. This demonstrated a relatively low adoption rate of solar technology for meeting household energy needs. According to ref. [55], the limited adoption of cleaner energy sources can be due to the high upfront costs associated with solar installations, perceived complexities in maintenance and operation, and limited access to financing or incentives for renewable energy adoption. Additionally, diesel generators may be used as backup power sources rather than primary energy solutions due to ongoing operational costs and fuel requirements.

Generally, the findings emphasize a widespread dependence on traditional energy sources like firewood and paraffin for essential household functions, with minimal uptake of cleaner energy sources, suggesting potential barriers or preferences for traditional methods despite the availability of alternative technologies.

5.3. Energy Expenditure of the Respondents

This section analyses the energy consumption patterns of the respondents and assesses the state of energy poverty among them. The section begins by estimating the total energy expenditure across households and subsequently determining the per capita energy expenditure line. The summary statistics of energy expenditure are provided in

Table 3. Summary statistics of energy expenditure among respondents.

Energy Type	Mean Expenditure	Std. Dev	Min.	Max.
Wood	48.5	21.69	0	100
Paraffin	50.47	49.86	0	200
LPG	104.15	107.39	0	375
Candles	34.42	21.57	0	125
Generator	10.23	33.84	0	150
Total Energy Expenditure	247.75	160.49	25	814
Per Capita Energy Expenditure	92.4	78.17	10	316

Expenditure amount is expressed in rands (ZAR) per month.

. In Table 3, the analysis of energy expenditure patterns reflects a diverse range of energy consumption patterns among the respondents. The findings reveal the use of various energy sources, including wood, paraffin, LPG, candles, and generators. Notably, respondents in the Upper Blinkwater community allocate their monthly budgets towards different energy expenditures. Specifically, they spend approximately ZAR 48.5 (equivalent to USD 2.66) per month on wood, highlighting their significant reliance on this traditional fuel source for heating and cooking purposes. In comparison, paraffin incurs a monthly expense of ZAR 50.47 (equivalent to USD 2.77), indicating another substantial expenditure for lighting and cooking needs among households. The most substantial expenditure among the energy sources is for LPG (liquefied petroleum gas), with an average monthly spending of ZAR 104.15 (equivalent to USD 5.72).

In contrast, respondents allocate relatively lower expenditures towards candles, averaging ZAR 34.42 (equivalent to USD 1.89) per month, and generators, with an expenditure of ZAR 10.23 (equivalent to USD 0.56) per month. These lower expenditures on candles and generators suggest their supplementary roles or occasional usage for specific lighting and power needs, highlighting the cost-effectiveness and practicality of these energy alternatives in complementing primary energy sources like wood and paraffin. However, significant variations are observed, particularly in paraffin and LPG expenditures, as indicated by the standard deviations. This suggests differing consumption habits and possibly disparities in affordability or access to certain energy sources among households.

The total energy expenditure, on the other hand, provides an overview of the overall cost associated with various energy sources. Across all energy sources, the average monthly energy expenditure was ZAR 247.75 (equivalent to USD 13.6) per month. These results indicate that a significant portion of household income is spent on meeting basic energy needs, which, according to the general idea of energy expenditure in the MEPI [7], is likely to strain their already limited financial resources. The MEPI assesses the proportion of income spent on energy, and a lower value indicates a lesser financial burden on households regarding energy costs. As shown in Table 1, on average, a household’s average monthly income amounts to ZAR 2321 (equivalent to USD 127.52). Therefore, applying the MEPI, spending 10% of income on energy is a burden for a family. In this case, the respondents’ expenditure of ZAR 247.75 or USD 13.6 is more than 10% of their monthly income, suggesting a financial burden among the respondents.

Moreover, the per capita energy expenditure indicating average individual spending, totalling ZAR 92.40 (equivalent to USD 5.07), suggests a relatively manageable level of energy expenditure relative to income. However, the observation of higher average energy expenditure compared to per capita energy expenditure raises concerns about potential disparities in energy consumption among households. This indicates that certain households might be consuming a disproportionately large amount of energy, likely influenced by varying socio-economic factors or disparities in energy access.

5.4. Energy Poverty of the Respondents

Energy poverty levels among the respondents were assessed to understand the varying degrees of hardship experienced by off-grid households in meeting their energy needs.

Figure 6 presents a summary statistic of the prevalence of energy poverty, categorizing respondents into three distinct groups: “No energy poverty”, “Moderate energy poverty”, and “Extreme energy poverty”.

In light of the per capita energy expenditure, which serves as a threshold to determine whether households are considered to be in energy poverty or not, the poverty line for energy expenditure is ZAR 92.40, or approximately USD 5.07 per capita per month, meaning that households with a monthly energy expenditure equal to or greater than per capita are classified as non-poor energy households. Those with expenditures below ZAR 92.40 but greater than one-third of that value are classified as moderately poor, while households spending less than one-third of ZAR 92.40 or USD 5.07 on energy are considered extremely poor energy households.

Overall, any household spending at or above ZAR 92.40 or USD 5.07 per month on their energy needs is considered non-poor in terms of energy expenditure, while those spending less than this amount fall into the categories of moderately poor or extremely poor, depending on their energy expenditure relative to this threshold.

The data then revealed that the majority of respondents, comprising 62.26%, were not considered energy-poor, suggesting that these households were able to afford their energy needs at a level above the defined threshold of ZAR 92.40 or USD 5.07 per month. This finding suggests a relatively higher level of energy affordability among these households, signifying that a majority of respondents have sufficient financial capacity to meet their energy requirements. It also implies a more stable energy situation compared to households categorized as moderately poor or extremely poor, who may struggle to meet basic energy needs within their budget constraints.

However, the remaining 37.7% of households experience varying degrees of energy poverty. Among them, 22.6% fall into the category of moderate energy poor, indicating that these households have energy expenditures below but greater than one-third of the threshold of ZAR 92.40 or USD 5.07. This implies that while respondents classified as moderately energy poor may have relatively better access to energy sources compared to the “Extreme energy poverty” group, they still face notable challenges in accessing reliable energy services since their energy spending and affordability are slightly less than one-third of ZAR 92.40 or USD 5.07 on their energy needs.

Within the energy-poor group, 15.1% of households were classified as extremely energy-poor, indicating severe energy poverty with energy expenditures significantly below the defined threshold. This suggests that respondents in this category likely experience substantial difficulties in accessing modern and reliable energy services, leading to a heavy reliance on traditional and potentially less sustainable energy sources.

Overall, the distribution of energy poverty levels highlights disparities in energy access and affordability among the surveyed households.

5.5. Energy Poverty Distribution According to Respondents’ Socioeconomic Characteristics

The objective of this study was to analyse how energy poverty varies across different demographic and economic factors among the surveyed population. In this section, we explore how energy poverty is distributed across key socioeconomic characteristics of the respondents, including gender, age, household size, education attainment, income, and income composition. The aim is to understand the disparities in energy access within various demographic and socioeconomic groups.

Table 4. Distribution of energy poverty and respondents’ socioeconomic characteristics.

Variable Mean Expenditure		Level of Energy Poverty
		No Energy Poverty		Moderate Energy Poverty		Extreme Energy Poverty
Gender	Male	14	(26.4%)	7	(13.2%)	2	(3.8%)
	Female	19	(35.9%)	5	(9.43%)	6	(11.3%)
Age	≤30	4	(7.55%)	1	(1.9%)	1	(1.9%)
	31–40	5	(9.43%)	1	(1.9%)	1	(1.9%)
	41–50	8	(15.1%)	1	(1.9%)	1	(1.9%)
	51–60	6	(11.3%)	6	(11.3%)	5	(9.43%)
	≥61	10	(18.87%)	3	(5.66%)	0	(0%)
Education	No Schooling	4	(7.55%)	1	(1.9%)	3	(5.66%)
	Primary	19	(35.9%)	9	(17%)	3	(5.66%)
	Secondary	9	(17%)	2	(3.77%)	2	(3.77%)
	Tertiary	1	(1.9%)	0	(0%)	0	(0%)
Source of income	No income	3	(5.66%)	3	(5.66%)	2	(3.77%)
	Wages	13	(24.5%)	1	(1.9%)	1	(1.9%)
	Grant	22	(41.5%)	9	(17%)	5	(9.43%)
	Remittance	7	(13.2%)	1	(1.9%)	1	(1.9%)
	Own business	4	(7.5%)	0	(0%)	0	(0%)
Income level	≤1000	5	(9.43%)	4	(7.55%)	6	(11.3%)
	1001–3000	12	(22.6%)	7	(13.2%)	2	(3.77%)
	3001–5000	11	(20.7%)	1	(1.9%)	0	(0%)
	5001≥	5	(9.43%)	0	(0%)	0	(0%)

provides a detailed breakdown of the distribution of energy poverty among these socioeconomic characteristics.

The results show that the majority of surveyed female-headed households (35.6%) were energy secure, compared to 24.6% of men, while 13.2% of male-headed households are moderately affected by energy poverty, compared to 9.43% of households headed by women. However, women were also overrepresented among those living in extreme energy poverty, 11.3%, compared to 3.8% for their male counterparts. These results suggest a gender gap in energy poverty, with female respondents presenting different scenarios: although many female-headed households have access to reliable energy sources, a significant proportion of women are disproportionately affected by energy poverty compared to men.

The data indicate a generally lower vulnerability to energy poverty across all age groups except for respondents aged 51 to 60, who are disproportionately affected. In this age group, 9.43% of respondents are classified as severely affected by energy poverty, compared to only 1.9% in other age groups below 50 years. Interestingly, respondents over the age of 61 have the highest levels of energy security, with zero percent experiencing severe energy poverty. The results indicate a deviation from the reflected trend, indicating a decline in energy poverty as age increases; however, vulnerability reaches a peak among respondents in their fifties and declines thereafter. It also indicates how resilient older people can be, as they seem to be more secure in their energy even as they get older.

Regarding respondents’ educational attainment and energy poverty, a distinct pattern was observed, with the majority of respondents with a primary education being classified as non-energy-poor (58.49%), followed by those with a secondary education (24.53%). On the other hand, a considerable percentage (5.66%) of those with no schooling and those with primary education were severely affected by energy poverty. Furthermore, those who have a tertiary qualification were the least likely to experience energy poverty and were neither moderately nor severely affected by energy poverty. These findings highlight the role of education in reducing energy poverty, indicate a clear correlation between educational level and energy poverty among respondents, and suggest that higher education is associated with lower levels of energy poverty.

Significant disparities were noted among respondents’ sources of income and their susceptibility to energy poverty. According to the data, social grant recipients comprised the majority (41.5%) of non-energy-poor households, followed by those whose income derived from wages, accounting for approximately 24.5% of households. However, social grant recipients also constituted the majority (9.43%) of those living in extreme energy poverty, along with a significant portion (17%) moderately affected by energy poverty. Similarly, households with no source of income were predominantly concentrated among those moderately (5.66%) and extremely (3.77%) affected by energy poverty. In contrast, households supported by a business or wage earner exhibited lower rates of energy poverty, with no instances of energy poverty observed among respondents whose income originated from their own business. These findings indicate that while social grant recipients predominantly fall into the non-energy-poor category, they are nonetheless the most vulnerable to energy poverty compared to other income groups.

When the income levels of the respondents were analysed, the data revealed a higher percentage of respondents with a total monthly income between ZAR 1001–3000 and ZAR 3001–5000 were more energy secure than other income brackets. Moreover, respondents with less than ZAR 1000 (equivalent TO USD 54.9) per month were identified as particularly impacted by energy poverty, highlighting substantial vulnerability within this income bracket. On the other hand, those with higher incomes, particularly those above ZAR 3000 (equivalent to USD 164.8), were less prone to encountering extreme energy poverty, with only 1.9% reporting moderate energy poverty. Additionally, respondents with incomes above ZAR 5000 (equivalent to USD 274.7) reported no severity of energy poverty. These results reflect a clear relationship between respondents’ income levels and their vulnerability to energy poverty, suggesting that higher income levels are associated with greater energy security, while lower incomes correlate with increased susceptibility to energy poverty.

6. Discussion

The results of this study revealed that households in the Upper Blinkwater community rely on a combination of energy sources to fulfil their daily energy demands, and wood is primarily used for heating spaces, while LPG emerges as the most utilized source for cooking. This observation resonates with the common scenario encountered in many rural communities, particularly those located in remote areas in Africa and South Africa, where accessing modern energy grids poses significant challenges. To meet their energy requirements, these communities often resort to traditional fuels, alternative fuels, or off-grid energy sources [68]. However, this finding reflects the persistent energy disparities and challenges faced by remote, non-electrified communities. Recent findings from [7,69] also revealed that relying on a single energy type is no longer sufficient or sustainable, even among electrified communities due to the increasing electricity price. Concurring with [24,55], not only are those in non-electrified areas confronted by high upfront costs and limited infrastructure to transition up the energy ladder, but there is also a widespread phenomenon affecting even many grid-connected households, who also find it difficult to keep up with the pace of rising energy prices. As a result, they are seeking cost-effective alternative ways to either supplement or completely substitute modern electricity. Consequently, there is a reliance on multiple energy sources as households seek to optimize their energy expenditure.

In essence, adopting multiple energy types empowers households to take control of their energy consumption, reduce dependence on centralized energy systems, which may be unreliable or inaccessible, and enhance their resilience, allowing them to better cope with energy-related challenges. This can be confirmed by the fact that their average per capita energy expenditure, determining whether households in this community are energy-poor by virtue of not being connected to the national grid, reveals that the majority are not energy-poor. As per the definition by [3,4], the absence of an electricity connection often correlates with energy poverty, meaning that a non-electricity connection is a significant indicator of potential energy poverty. However, the results of this study have proven otherwise, indicating the need to assess energy poverty beyond just access; affordability and utilization are crucial. However, a significant proportion of households still experience varying degrees of energy poverty. This implies diverse backgrounds and vulnerabilities among residents, and indeed upon analysing the distribution of energy expenditure, the findings revealed varying levels of expenditure across different energy sources. Specifically, expenditures on wood and candles were relatively lower, which aligns with the abundance of firewood often available within or near the communities, as stated by [64]. However, among the respondents, we observed a decreasing reliance on firewood for cooking as modern alternative LPG emerged as the most preferred energy source. This contrasts with most rural communities in South Africa, such as Ga-Malahlela village in Limpopo Province [64], where firewood remains predominantly used even with an electricity connection. The findings in the study highlight the significance of LPG, suggesting its prominence as a preferred energy source among respondents. This also implies a positive shift towards reduced dependence on traditional or less dependable energy sources in favour of more modern, efficient, and convenient energy options, indicating a growing desire for modernization.

The findings further prove disproportionate, with the respondents’ demographics and socioeconomic factors presenting unique challenges and vulnerabilities, influencing the extent to which individuals and communities are affected by inadequate access to energy services. Notably, there is a significant gender disparity, but in support of the SDGs on gender and equity, which are to ensure fairness and justice in the distribution of resources, opportunities, and benefits among all individuals and communities, particularly those who are disadvantaged or marginalized, including women [70]. The findings indicate that vulnerability to energy poverty was minimal among female-headed households. This finding aligns with [25], that households headed by women often experience lower levels of energy poverty compared to those headed by men because women have a tendency to prioritise household essential needs and are resilient in coping with challenges. However, this seemingly positive trend is countered by the stark reality that women were also overrepresented in the extreme energy poverty group, suggesting a higher vulnerability to severe energy poverty among women. This implies that while female-headed households may have lower rates of overall energy poverty, they remain susceptible to severe energy deprivation. Gender disparities may influence experiences of energy poverty, with variations attributed to societal roles and habits. Mofokeng [71] thinks that this disparity often stems from underlying issues such as unequal access to resources, limited economic opportunities, and societal structures that disproportionately affect women in managing household energy needs, perpetuating gender disparities in energy access. As a result, energy poverty disproportionately affects women and girls, who are often seen as the primary users of unclean and unhealthy energy sources. Overall, female-headed households bear a disproportionate burden of energy insecurity. Supported by [50], this vulnerability is mostly reflected among Black South African women compared to their White counterparts.

The data also revealed a significant trend indicating a decline in energy poverty with increasing age. Specifically, respondents aged 51 to 60 years were notably impacted by energy poverty, with a substantial proportion categorized as extremely or moderately energy-poor. This suggests that as individuals grow older, they may encounter difficulties in accessing resources to meet their energy needs, such as upgrading to more energy-efficient appliances. However, an intriguing observation emerged indicating that beyond the age of 61, no severity of energy poverty was observed. This suggests that older individuals in the Upper Blinkwater region experience greater energy security compared to younger and middle-aged groups. Similar results were observed in [39], who also showed that there is a correlation between the age of household heads and their MEPI scores, suggesting that as household heads age, their MEPI scores significantly decline. This indicates that household heads of a younger age tend to have higher levels of energy poverty compared to older household heads. In other words, younger household heads were more likely to experience greater energy poverty, while older household heads were relatively more energy secure. This phenomenon can potentially be attributed to financial assistance provided in the form of social grants [17]. In South Africa, individuals meeting the indigent criteria qualify as beneficiaries of old age grants at the age of 60 years. As illustrated in Table 1, grants contributed significantly to household income, offering the elderly household heads financial stability, likely contributing to their reduced vulnerability to energy poverty [17].

The findings of this study also indicate that individuals with lower incomes are at a higher risk of experiencing energy poverty compared to those with higher incomes. This suggests that the affordability of energy plays a crucial role in determining energy security. This finding is corroborated by [39], who demonstrated that higher-income earners have the financial means to access and afford cleaner energy alternatives, thereby contributing to the alleviation of energy poverty. Moreover, the study revealed that individuals reliant on grants are particularly vulnerable to energy poverty, with a high percentage classified as extremely energy-poor. Furthermore, the study uncovered that individuals dependent on grants are notably susceptible to energy poverty, with a significant proportion classified as extremely energy-poor. This indicates that even with larger grant amounts, households continue to face energy poverty. This, according to [17], could be attributed to the fact that higher grant amounts might correspond to an increasing number of grant recipients, potentially leading to larger household sizes and increased energy demands, consequently increasing vulnerability to energy poverty. The authors of [39] found similar results and emphasized that grant recipients often do not allocate these funds toward obtaining clean energy solutions. It is important to note that social grant recipients in South Africa are typically selected based on specific welfare deprivation criteria such as unemployment, disabilities, and low income. Therefore, it can be anticipated that the funds will be used to address the endless household needs requiring money.

7. Conclusions

The evaluation of energy poverty in off-grid communities revealed a reliance on diverse energy sources, with a noticeable transition from traditional to modern energy sources, particularly with an increasing preference for LPG for cooking, driven by considerations of convenience and efficiency. The per capita energy expenditure of households in this community has proved resilience and adaptability, although a significant proportion still faces severe energy poverty, attributed to disparities in income and associated financial burdens. Thus, energy poverty levels vary significantly across different characteristics, reflecting diverse socioeconomic backgrounds and vulnerabilities within the community. Although social grants provide financial stability and help reduce vulnerability to energy poverty, they may not fully address the underlying socioeconomic factors contributing to energy poverty; as a result, challenges persist, especially among lower-income households that rely on grants. Gender disparities are also evident, with women overrepresented in extreme energy poverty groups despite a higher overall percentage not experiencing energy poverty. These highlights heightened vulnerability among female-headed households, pointing towards specific challenges faced by women in accessing affordable and reliable energy services. Moreover, energy poverty peaks among respondents aged 51 to 60, suggesting challenges in accessing resources for energy-efficient upgrades. Interestingly, older individuals beyond the age of 61 exhibit greater energy security, likely due to the stability provided by social grants. This indicates a potential correlation between age, financial stability, and energy security within the community.

This paper has successfully shown that not all off-grid households without an electricity connection necessarily experience energy poverty, and importantly, the results have shown who might be most vulnerable to energy poverty, filling a gap in the literature and enabling decision-makers to develop better policies addressing underlying issues pertaining to the delivery of modern energy. In light of these findings, the government is urged to consider fast-tracking the rollout of community-based mini-grid renewable energy technologies and programs that contribute to making energy services more affordable and accessible. Additionally, promoting community-based income-generating programs and offering entrepreneurship support can enhance economic opportunities within communities, reduce reliance on social grants, and ensure financial stability.

For policy, addressing irregularities in the administration of the Free Basic Alternative Energy (FBAE) within municipalities and prioritizing female-headed families within the eligibility criteria are essential for advancing access to cleaner energy sources. This acknowledges the disproportionate impact of energy poverty on this demographic and promotes gender equity in energy access. Additionally, introducing preferential pricing for social grant beneficiaries and minimum wage workers can further increase affordability and promote inclusivity, ultimately benefiting those most in need while contributing to broader socioeconomic development goals.