Linking Energy Transition to Income Generation for Vulnerable Populations in Brazil: A Win-Win Strategy

Abstract

This article presents the modeling of a solar photovoltaic system connected to the grid in rural low-income communities living in the semiarid region of Brazil. The model is based on the premise that enough electrical energy will be generated locally to meet the household demand for electricity and to produce a surplus that can be sold on the grid. The main idea is that the sun, usually associated with severe droughts in the Brazilian semiarid region, can be transformed into social income while fostering energy autonomy. To model the system, the computational tools Photovoltaic Software (PVSyst7.3.1) and System Advisor Model (SAM) were used. Several configurations (cases) of systems were analyzed and associated with the evaluation of three commercial electricity scenarios, considering the local electricity rate (USD/kWh). A case study was conducted in the rural settlement of Jacaré-Curituba in the Brazilian semiarid region, where different estimated sale prices for the energy surplus were compared with traditional monthly cash transfers to poor families from the social welfare program “Bolsa Família”. The results indicate the viability of this model as an income alternative for low-income communities.

1. Introduction

Energy is an indispensable input for the socioeconomic development of any society [1,2]. Energy strategies carried out by governments or by civil society initiatives around the world aim at increasing efficiency and security while providing an environmentally friendly energy supply through the adoption of renewable energy sources.

The commodity-based rural economy model in Brazil and its role in providing primary goods to the world market are at stake in the debate about development. The Brazilian agricultural sector moves more than USD 100 billion a year and represents approximately 26.6% of the Brazilian gross domestic product (GDP) [3]. The actual agricultural economy is based on the combination of large-scale production (agribusiness for exporting commodities) and medium and small farms, with a predominance of so-called family farming (in which most of the workforce is provided by the family itself). Family farming supplies most of the food to meet the national demand. Seventy percent of the Brazilian diet consists of food (rice, beans, cassava, corn, potatoes, and milk) that comes from small rural producers. However, those producers are extremely vulnerable in social, economic, and environmental (including climatic) terms.

A transition to sustainable energy can be achieved together with an inclusive and equitable rural development process. Promoting rural development can improve the livelihoods of the rural population in a sustainable, economically, and environmentally friendly approach [4]. This can be achieved by providing people with better access to natural, physical, human, social, and technological improvements, as well as control over productive capital (in economic or financial forms), which allows them to secure their livelihoods in a sustainable and equitable manner [5].

Since the second half of the 20th century, rural areas have witnessed significant demographic and land-use transformations in Brazil. These transformations also include the aging of the rural population, massive migration to urban areas, and the marginalization of family farmers during the advancement of large-scale commodity production (e.g., with crops such as soya, beef, cotton, and poultry). Monocultures increase environmental vulnerability and provoke adverse and often irreversible environmental impacts, especially in the context of climate change [6].

Since the Kyoto Protocol—an international treaty to control the emission of greenhouse gases (GHG) in the atmosphere—was signed in 1997, the global community has intensified its efforts to reach these commitments at national scales. Among several key issues, energy plays a relevant role in controlling GHG [7]. The idea of developing “green” energy communities has piqued global interest, mainly as one of the strategies to implement the Sustainable Development Goals (SDGs) established by the 2030 Agenda of the United Nations (UN). More precisely, SDG 7 focuses on clean, accessible, and affordable energy for all [8]. Rural development with the inclusion of renewable energy technologies, together with effective social movements, can thus lead to the improvement of local living conditions and the reduction of unemployment and poverty [9,10,11,12,13].

Key renewable technology options for rural areas include wind, solar, small-scale hydro, biomass, and biogas. Energy systems based on renewable technologies have the potential to reduce the costs of transmission and distribution by means of network optimization. Similarly, it is possible to avoid technical and nontechnical losses of electrical energy, in addition to contributing to the diversification of sources for the national electricity grid [9].

To build energy systems, connected or not to the electrical grid in rural, isolated areas or already electrified urban areas, solar technology is practical, economically viable, and widely available [14,15]. Despite their relatively high initial capital cost, photovoltaic (PV) systems can make a significant contribution to reducing GHG emissions [16]. Its production can also increase sustainability and meet rapidly growing energy demands in a cost-effective manner [17,18,19,20]. Recent reductions in the cost of photovoltaic solar systems have demonstrated their cost competitiveness over other sources [21,22]. The electricity cost of utility-scale solar PV was estimated to be approximately USD 0.07/kWh, which indicates a 13% decline per year since 2019 [23].

This work proposes, within the framework of the concept of distributed generation (DG), a solar model that generates enough energy to meet the load demand of families living in poor areas and rural communities, in addition to producing a surplus of electricity that can be sold. It also evaluates the viability of selling electricity on the grid to the local power utility company or other interested buyers, thus increasing the families’ incomes and contributing in a sustainable way to their financial and energetic autonomy. The analysis and arguments considered here are based on hypothetical cases due to regulatory constraints, as presented further in the article.

It is worth remembering that current Brazilian legislation only establishes a net metering-type electricity compensation system (a system in which consumers produce their own energy to reduce the consumption of energy provided by local utilities). The income generation alternative, as proposed in this work, is compared with other social programs carried out by the Brazilian government. Such programs invest more than USD 396 million per year in social and economic assistance actions for low-income families in urban, rural, and isolated communities [24]. Among the various social programs, the Bolsa Família Program (BF) stands out and offers USD 118.88 (as of 19 April 2023, considering the average amount transferred at that moment) per month for each family. This study also analyzes the potential environmental benefits related to the adoption of a solar energy generation program.

The article is divided into six sections, including the introduction (Section 1). In Section 2, a literature review of some of the studies on the subject is carried out. Additionally, in that section, a review of distributed energy generation for low-income communities in Brazil is presented, and socioenvironmental benefits are highlighted. Section 3 outlines the methodology, highlighting the simulated model and computational tools employed. Section 4 describes a case study and presents solar irradiation data from the site. This section also includes data from field research conducted with a group of 122 families. Section 5 and Section 6 present the results and discussion, respectively, and the final considerations.

2. Literature Review

Numerous initiatives have been carried out around the world to estimate and establish the viability of photovoltaic solar systems and ways to optimize their use. Many of these studies describe energy generation processes compared with other energy sources in different contexts, including urban and rural areas and isolated regions [9,22,25,26,27,28,29]. Farahi and Fazelpour [30] created, for example, an off-grid photovoltaic power system to power a health clinic in a remote area in Southwest Ethiopia.

With the use of photovoltaic solar systems, Jariso et al. [31] made a scenario comparison to evaluate the economic performance of different energy systems to electrify Kutur village in the Axum district in Ethiopia. Kiros et al. [32] analyzed the economic and environmental impact of using solar pumps in a sustainable agricultural development project. Chel and Kaushik [33] highlighted, in turn, the role that solar energy plays in agriculture in rural settlements, reinforcing all the agronomic parameters regarding ecological efficiency, environmental and social impacts, and feasibility beyond technical concerns.

In a nexus approach and with the inclusion of solar energy to benefit agriculture, Santos et al. [34] and Ribó-Pérez et al. [35] evaluated the feasibility and incentives for farmers to use autonomous photovoltaic systems. Al-Saidi and Lahham [36] discussed high-investment rural electrification projects, examining various methods that could be followed to cover the costs needed to implement them, including increasing the cost of production and plant products, as well as subsidizing the cost of PV. This approach has been implemented in Rwanda, supporting local agricultural cooperatives by promoting electrification activities in rural areas and subsidizing PV systems.

Other studies show the benefits of PV systems connected to the electricity grid in urban slums and in electrified rural low-income settlements [37,38,39]. The research by Kyriakarakos et al. [40] evaluated the barriers to the supply of electricity in the context of urban and peri-urban slums in developing countries. This study indicates alternatives that include innovative solutions, promotion of public policies, and rigor in decision-making, financing, and social inclusion.

In the case study by Singh et al. [41] a microgrid system was proposed and optimized involving renewable technologies, including solar energy on a small island in Rottnest, Australia. The authors analyzed the technical, economic, and social aspects and noted that the optimized system had an energy cost (COE) of USD 0.161/kWh, which was lower than the cost of the existing system on the island, which was USD 0.207/kWh. This reduction in the cost of energy showed the economic viability of the system and its potential positive impact on the budgets of families on the island. The study also noted the environmental benefits, with a 34.70% reduction in CO₂ emissions.

Technologies for the distribution of electricity in slum areas are the focus of Jean et al. [42] regarding the distribution of electricity in slum areas and electrified rural areas. The study shows that distributed generation from renewable sources is on the rise, especially in regard to solar energy. Through the pilot project called Solar Pilar in the poverty-ridden Pilar community in Rio de Janeiro, Brazil, the authors analyzed the benefits of inserting distributed solar generation in ninety (90) homes in the slum. They pointed out the vital impact of this new technology on household budgets through the reduction of their energy bills.

Benti et al. [5] conducted a techno-economic analysis of a solar energy system for electrifying a rural school in Southern Ethiopia, integrating PV, diesel, and battery components. Recently, Imam et al. [21] comprehensively assessed the techno-economic viability of grid-connected PV systems for residential buildings in Saudi Arabia through a detailed case study. El-houari et al. [20] designed, simulated, and optimized an autonomous PV system to supply nonpolluting electricity based on a renewable source to a rural house located in Tazouta, Morocco. Similarly, Jean and Brasil Junior [9] developed a model for a solar PV system connected to the grid to meet energy demands and sell the surplus electricity produced to generate income. Falih et al. [43] carried out a technical–economic analysis of a connected hybrid solar system in a low-income house in Diyala, Iraq. By employing the Hybrid Optimization of Multiple Energy Resources (HOMER) computational tool, Diemuodeke et al. [44] determined the optimal configuration of a PV system to satisfy the domestic energy demand of rural coastal communities in the Niger Delta region of Nigeria. Nacer et al. [45] also conducted a study aiming to design an ideal solar energy system that satisfies the electrical needs of farms in rural regions in Algeria while exploring the feasibility and impact of replacing conventional systems with solar energy solutions. Finally, Jean and Brasil Junior [12] conducted a comprehensive study that analyzed the technical and economic feasibility of implementing a photovoltaic solar system for a rural community in Northern Haiti.

Therefore, the literature points out that the implementation of DG systems with the adoption of renewable technologies, mainly solar energy, can improve the livelihoods of people in isolated communities, rural settlements (whether electrified or not), and urban slums. The social benefits of solar energy pointed out by the studies can be expected mainly to (i) increase public awareness and promote incentives for energy savings; (ii) promote the reduction of GHG emissions; (iii) lower the burden of energy costs to low-income populations; and (iv) create new research and employment opportunities and the electrification of remote or economically deprived areas, as well as increase the energy autonomy in households [46,47].

2.1. Distributed Generation for Low Income

Distributed generation can be understood as any small-scale power generation technology providing electricity closer to customers compared to traditional centralized generation. DG technologies generally include engines, small (including micro) turbines, fuel cells, or solar photovoltaics. New technologies are increasingly enhancing the technical and economic viability and, thus, fostering a better and faster adoption of DG.

In Brazil, DG is regulated by Normative Resolution 482/2012, updated as 687/2015, set by the ANEEL (the National Electric Energy Agency in Brazil). The regulation has set up a system of compensation (or net metering), which establishes that consumers can generate their own electricity from renewable sources and that the surplus can be conveyed into the local power utility company network. That energy surplus is converted into energy credits to be used in subsequent periods. Brazilian legislation does not, however, allow for any sale of energy credits by individuals, unless in cases of direct sale of the surplus to another user, based on a formal contract endorsed by the local power utility company.

In fact, this normative resolution was an important regulatory milestone for DG in Brazil. Since then, distributed generation systems, mainly solar, have grown. According to the Brazilian Association of Photovoltaic Solar Energy (Absolar), in December 2022, the installed capacity of photovoltaic solar energy in Brazil was 24.00 gigawatts (GW), against 14.154 GW in December 2021 and 8.016 GW in December 2020 [47,48]. In increasing the installed capacity by 69.56% from December 2021 to December 2022, solar energy surpassed wind sources (which produce 23.8 GW). Figure 1 shows the evolution of solar energy over a period of ten years starting in 2012, the year the legal framework was created, and ending in 2022. Investments in solar energy are estimated to have reached approximately USD 16.90 billion, generating USD 5.11 billion as income and over 478,000 jobs since 2012 [48,49]. In terms of environmental outcomes, solar energy has prevented the emission of 20.80 million tons of CO₂ into the atmosphere between 2021 and 2022.

In early 2023, a new piece of legislation, Brazilian Ordinary Federal Law—14300/2022, went into effect, establishing the Social Renewable Energy Program (PERS, in Portuguese). PERS focuses on investments in the installation of photovoltaic systems and other renewable sources for family farmers and residents of urban areas that participate in the social programs of the federal government. There is also the More Light for the Amazon Program (MLA), which facilitates access to electricity through the use of clean and renewable energy generation, mainly from solar sources, in remote and low-income regions (residents of riverside communities, indigenous peoples, quilombolas, rural settlements, residents of conservation units, schools, health centers, and community water wells). Currently (2023), 1,576,940 DG systems are installed in Brazil, 132,299 of which are in rural areas (8.40%) [48,49].

DG is often considered a viable solution to the electricity needs of low-income areas (isolated areas, rural settlements, and marginalized slum areas). It is important to note that there are low-income areas (urban, rural, and isolated) that are connected to the grid, but there are still some that are not. In rural and isolated nonconnected areas, the cost of providing electricity is relatively high due to the low density of the population. There is relatively low demand, long distances, and generally very low per capita income.

Centralized energy systems are vulnerable to endemic energy theft, which reduces service reliability, causes nontechnical losses, and consequently, increases electricity prices. Such practices work as a vicious circle that marginalizes low-income populations from the official energy systems. DG systems offer little possibility for energy theft, as systems are generally mounted on metal structures attached to homes. Another great advantage offered by DG systems is the possibility of training residents. As they are local and small-scale systems, services related to measurement, bill collection, and basic maintenance can be carried out by the participants of the systems once instructed in such activities.

DG’s initial investment is low, and the equipment can be reused in the event of moving to another location. Unlike centralized generation, DG does not require large investments in transmission and distribution that generate losses, the acquisition of large areas for its construction, and the socio-environmental risks and environmental impacts that all large constructions bring to the local population. Considering the actual energy tariffs, the costs of installation of DG systems are becoming more competitive each time.

2.2. Socio-Environmental Benefits of Solar DG

Although considered clean energy, the generation of electricity in hydroelectric plants brings about socio-environmental impacts due to the need to displace populations before flooding the area of the reservoirs [50,51]. In addition, there are environmental impacts, such as (i) changes in the physical and biological characteristics of water bodies; (ii) changes in land use and landscape cover; (iii) changes in the region’s flora, fauna, and climate; and (iv) environmental pollution caused by the emission of greenhouse gases [50].

Recent studies have shown that reservoirs can act as sources of greenhouse gases [52,53,54]. According to Kelman et al. [55], the main gases released into the atmosphere are carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O), which are gases of biogenic origin that result from the decomposition of organic material. The author shows that these gases are released by bubbling, diffusion on the surface of the lake, and decompression of the flow after passing through the turbines.

The amounts of gases emitted by reservoirs of hydroelectric plants vary according to the location. Some authors state that the results obtained in the boreal region, for example, show gas emissions at their maximum value between the first 3 to 5 years after filling the reservoir. This figure differs for natural aquatic environments by approximately 10 years for CO₂ and 4 years for CH₄ [56]. In the specific case of semiarid and tropical regions, the restoration of environmental levels can take much longer, mainly due to environmental factors such as temperature and water quality, among others [50].

Bernal and Rodrigues-Filho [51] analyzed the socio-cultural impact that the construction of the Luiz Gonzaga Hydroelectric Power Plant in Northeast Brazil had on the livelihoods of traditional populations. The most common impacts identified by the authors were related to (i) the forced displacement of populations; (ii) the loss of territory; (iii) the internal conflict among the population (for example, conflicts over the use of water, energy, irrigation, and human and animal consumption); and (iv) cultural, nutritional, and economic losses resulting from land deprivation and the consequent decrease in the community’s traditional productive activities. Removal or resettlement of traditional populations in different regions of the country gave rise to internal confrontations and a social movement (movement of those affected by dams).

On the other hand, the impacts of photovoltaic energy generation appear to be largely reduced. PV systems easily adapt to the local architecture, as long as there is sunlight [57]. The mass installation of PV systems connected to the electricity grid can contribute to reducing the construction of hydroelectric power plants and saving water in hydroelectric reservoirs during periods of drought. In addition, solar energy can spare the need to temporarily use highly intensive GHG-emitting thermoelectric plants in times of drought.

3. Materials and Methods

3.1. Model Specification

In this research, the modeling includes the construction of a PV system where enough electricity can be generated to meet the demand of the consumer unit and generate surplus electricity to be loaded into the local power utility company grid. Figure 2 shows the system organization process. Such a scheme demands a preset partnership arrangement connecting the actors involved, including the research team, the energy users participating in the project, and the power utility company.

This model focuses on low-income families living in poor regions and/or rural communities. For the sale of the surplus of electricity, it is estimated that the local power utility company would pay each unit consumer an amount (monetary value). Considering that, as mentioned above, according to the present legislation, payment in cash for the energy distributed on the grid by individuals is not mandatory, the present study focuses on hypothetical modeling. The aim is to provide support for further regulatory improvements that can lead to more socio-environmentally sound policies. The amount will be calculated based on the net revenue of the power grid, multiplied by the resale fee, as presented in the sales scenarios herein. Some trading scenarios were considered, varying the energy tariff (USD/kWh) in the region from 70% to 100% of the actual price charged to individual consumers:

• 1st scenario—trading the surplus at 70% of the electricity tariff of the local power utility company;
• 2nd scenario—trading the surplus at 80% of the electricity tariff of the local power utility company;
• 3rd scenario—trading the surplus at 100% of the electricity tariff of the local power utility company.

Estimated revenues were compared with the cash transferred to low-income families under the Bolsa Família program (BF), which is currently paying USD 118.88 per month (by April 2023) to each participating family. This model will be tested in a low-income rural settlement (Jacaré-Curituba) in the Brazilian semiarid region.

3.2. Simulation and Data Processing Tools

For the assembly and simulation of the model, the following computational tools were used: Photovoltaic Software (PVSyst 7.3.1) and the System Advisor Model (SAM 2022.11.21). QuantumGIS (QGIS) was also used to prepare maps of solar irradiation distribution and the location of the rural settlement. QGIS is a geoprocessing tool used to develop maps and work with georeferenced data.

3.2.1. Photovoltaic Software

Photovoltaic Software (PVSyst) is a computational tool that offers the possibility of carrying out studies and sizing and analyzing photovoltaic systems. The tool has a series of features, from simulations and calculations to issuing reports and technical documentation. Due to its scope, functionalities, calculation precision, and reliability, PVSyst is one of the most commonly used computational tools. PVSyst consists of a large-scale climate database from NASA and Meteonorm, as well as complete technical information and data from a variety of manufacturers of photovoltaic modules, inverters, batteries, and other equipment. The PVSyst project area is made up of two types of environments, namely, preliminary design and detailed design. In the environment called preliminary design, quick and simplified calculations for preliminary studies of a project can be performed, and in the environment of detailed design, more detailed simulations, for example, of a photovoltaic plant with several variants within the same project, can be made.

3.2.2. System Advisor Model

The System Advisor Model is a free computational tool developed by the National Renewable Energy Laboratory (LNER or NREL) that allows for the modeling and simulation of energy projects. For grid-connected solar PV system designs, SAM makes predictions of performance and energy costs based on the installation and operating costs and the system design parameters specified by the designer. SAM allows designs to be modeled and simulated with multiple drives with Maximum Power Point Tracking (MPPT) or DC optimizers.

4. Case Study

4.1. Study Area

The rural settlement Jacaré-Curituba is situated in the municipalities of Poço Redondo and Canindé de São Francisco (state of Sergipe), in a region known as Baixo São Francisco (Low São Francisco River), in the caatinga biome. According to Brazilian standards, Jacaré-Curituba is considered a large irrigated settlement. Gathering farmers under the national agrarian reform policy (set by the Constitution of 1988), the settlement encompasses an area of 3105 ha, of which 1860 ha are irrigated. In its 630 lots, with areas between 2 and 3 ha, approximately 900 families live. They are settled in 36 “agrivillages” (with approximately 20 households in each). Most settlers (686) have irrigation systems. The settlement has significant economic importance for the local context.

Regarding its climatology, according to the Köppen and Geiger classification, the study area is assigned to the BSh class (hot semiarid) and is characterized by scarce rainfall and great irregularity in its distribution, low cloudiness, strong insolation, and high evaporation rates. The vegetation is xerophytic (Caatinga), with latitudes of 0° and 30° (tropics and subtropics), which are typically close to regions with a tropical savanna climate or humid subtropical climate. The average annual temperature in the region is approximately 25.30 °C. There is little rainfall throughout the year, with an annual average of 510.15 mm and a rainy period from March to July (autumn–winter).

The settlement is connected to the electricity grid, and electricity is used both for domestic (lighting, use of equipment, etc.) and for irrigation purposes. The main problems faced due to the supply of electricity in the settlement are unscheduled blackouts of short duration, low voltage (a consequence of the excessive length of the network), and undersized transformers. In the view of settlers, the energy bill is considered high for their standard of living. A survey in 2022 of a sample of 122 families showed that more than 66% agreed that energy costs strongly compromised household income (Figure 3). The above-listed reasons corroborate the need for electricity supply alternatives.

The choice of the case study in Jacaré-Curituba is driven by our involvement in the region through the INCT-Odisseia project, which aims to promote sustainable and innovative solutions for communities in vulnerable areas.

4.2. Local Solar Potential

Monthly average insolation data for Jacaré-Curituba and nearby areas were obtained through the NASA POWER platform. The profile indicating the solar radiation and clearness index is presented in Figure 4. The monthly average solar radiation in the settlement is 5.50 kWh/m²/day, a high potential compared to those screened in surveys in other parts of the world [18,32,38,58]. Furthermore, the map created using QGIS indicates, with a broader view, the distribution of the solar radiation potential in the region (Figure 5). Data show that the location has great solar potential and that it is maintained throughout the year, even in winter, which guarantees the viability of solar energy projects. Solar energy can, then, transform the longtime threat of strong insolation and high evaporation rates that affect the semiarid region into an inclusive and empowering alternative for low-resource families in the region.

4.3. Analysis of Possible Configurations

Table 1 presents five alternative settings, which include the cost of installation, the power generation of each system, and the estimated area required for the installation. Data in this table are derived from the simulated model and the panel manufacturers. The projection of the installation cost for each household unit includes the main components of the system, the technical project, the formal Technical Responsibility Note (which is a normative requirement), and the labor cost. To determine the power of the systems, input data, such as the energy consumption of the household unit and the associated installation costs, were used. The panel used in the simulation is polycrystalline silicon, with a maximum power of 340 Wp and a 17.52% efficiency. In addition, the surplus electricity to be generated was also considered according to the research objectives. The energy to be loaded onto the grid was determined based on the relationship between the output power of the PV panel (according to the method established by Nascer et al. [44]) and the demand for electricity to be met, according to Equation (1). The sale of energy is the result of the ratio of surplus electricity and the local energy tariff (2):

$$E_{IG}=Y_{PV}{f}_{PV}\left({\displaystyle \frac{G_T}{G_{T,STC}}}\right)\left[1+{\alpha }_P\left(T_C-T_{C,STC}\right)\right]-E_L$$

(1)

where $E_{IG}$ indicates the energy injected into the grid (kWh), $E_L$ is the local electrical load (kWh), $Y_{PV}$ represents the output power of the PV under standard test conditions (STC) (kW), α_P is the power temperature coefficient (%/°C), $f_{PV}$ is the PV derating factor (%), $G_{T,STC}$ is incoming radiation under STC (kW/m²), $G_T$ indicates the solar radiation striking the PV panel (kW/m²), $T_C$ denotes the temperature of the PV cells (°C), and $T_{C,STC}$ is $T_C$ under STC (25 °C).

$$S_G=E_{IG}\times E_{TA}$$

(2)

In this equation, $E_{TA}$ represents the local energy tariff (USD/kWh), and $S_G$ indicates the sale of energy to the grid (USD).

Table 1. Description of simulated settings. Source: elaborated by the authors.

Cases	Power (kWp)	Required Area (m2)	Panel No.	Power per Panel (Wp)	Unit Cost (USD)
Case 1	2.554	15.522	8	340	3346.16
Case 2	5.108	31.045	16	340	6092.60
Case 4	6.100	34.926	18	340	7993.58
Case 5	6.800	38.807	20	340	6771.14
Case 3	7.300	42.687	22	340	7547.86

Table 1. Description of simulated settings. Source: elaborated by the authors.

Cases	Power (kWp)	Required Area (m2)	Panel No.	Power per Panel (Wp)	Unit Cost (USD)
Case 1	2.554	15.522	8	340	3346.16
Case 2	5.108	31.045	16	340	6092.60
Case 4	6.100	34.926	18	340	7993.58
Case 5	6.800	38.807	20	340	6771.14
Case 3	7.300	42.687	22	340	7547.86

5. Results and Discussion

5.1. Electrical Performance Analysis

The graphs in Figure 6a,b indicate the estimated monthly generation of each simulated case in PVSyst and SAM. Figure 7a,b shows the surplus electricity variation, considering the two computational tools used. Monthly averages of electricity generation vary according to each case. Case 3 had the highest average electricity generation, at 1005.74 kWh/month, and case 1 had the lowest average monthly electricity generation (351.60 kWh/month). The configurations (cases 1, 2, 4, and 5) represent approximately 35.00%, 70.00%, 83.50%, and 93.10% of the value of case 3, respectively. In fact, case 3 shows greater electricity generation capacity than other configurations and is followed by case 4, which indicates that these two configurations have a better capacity to load surplus electricity onto the local power utility company network than the other cases (Figure 7a,b), as highlighted in the research by Jean and Brasil Junior [9] and Sajjad et al. [59]. Notably, when comparing the results of PVSyst and SAM, the mean variation was only 0.84% between the simulated cases, which indicates that the results are consistent.

5.2. Economic Analysis

Revenue was estimated by considering sales of surplus electricity to the local power utility company (Figure 8, Figure 9 and Figure 10). In all the simulated cases, the corresponding revenue was identified. However, a comparison of these estimations with the values received through public family allowances (the Bolsa Femília, BF, cash transfers) shows the following:

• In the 70% sales scenario (Figure 8), the estimated monthly revenue average in simulated case 1 (lower generation of surplus electricity) is USD 23.54, i.e., 19.80% less than the BF transfer (

  Table 2. Comparative analysis of revenues and returns between cases compared to BF cash transfers. Elaborated by the authors.

  Cases	Sale at 70% (USD)	Sale at 80% (USD)	Sale at 100% (USD)	Variation in Relation to BF (%)			Payback (Years)
  				Sale at 70%	Sale at 80%	Sale at 100%
  Case 1	23.54	26.91	33.63	19.80	22.63	28.29	8.29
  Case 2	56.66	64.75	80.94	47.66	54.47	68.08	6.27
  Case 4	69.51	79.44	99.30	58.47	66.82	83.53	5.68
  Case 5	78.58	89.80	112.26	66.10	75.54	94.42	5.60
  Case 3	85.06	97.21	121.52	71.55	81.77	102.21	5.48

  ). In case 3 (greater generation of surplus electricity), the estimated average monthly revenue is USD 85.06, which represents approximately 71.55% of the BF transfer. Case 4 and case 5 present average revenues of 58.47% and 66.10% of the BF transfer, respectively;
• In the 80% sales scenario (Figure 9), the cases with average revenues closest to the BF transfer are case 3 (81.77%), followed by case 5 (75.54%) and case 4 (66.82%). Case 1 (22.63%) and case 2 (54.47%) have much lower average revenues compared to the BF transfer;
• In the 100% sale scenario (Figure 10), case 3 (102.21%) exceeds the BF transfer value. Case 1 (28.29%) remains well below the BF allowance. Case 5 (94.42%) and case 4 (83.53%) present values approximate with the BF transfer.

Figure 11 compares the revenues generated in the three energy sales scenarios (70%, 80%, and 100% of the local tariff), considering only case 3 of each energy sales scenario. Only in the 100% sale scenario is the average monthly revenue slightly (2.21%) higher than the monthly family allowance paid by the BF program. In the sales scenarios at 70% and 80%, the average monthly revenue is 28.45% and 18.23% below the BF transfer, respectively. As in the study developed by Jean and Brasil Junior [9], the scenarios show the viability of an alternative source of income (social energy income) through the sale of surplus electricity generated by low-income families themselves. Those vulnerable families depend on the revenue from low-profit agriculture and the cash transfers from governmental social programs. However, to define the ideal case to be implemented, it would be necessary to carry out a more in-depth analysis of the investments required to install the system.

In the analysis carried out thus far, as shown in Table 2, only the energy surplus is considered. If family consumption is taken into account, the income effect (energy sold + energy savings) is more significant. It would take approximately five years of the cost of cash transfers (BF program) to pay back the investment necessary for installing the best alternative PV system. Considering that the useful life of the PV panels is 25 years, the model analyzed in this paper can guarantee revenue similar to that provided as cash transfers by the government for almost 20 years after paying off the costs of installation. However, unlike the cash-transfer policy, a social energy income program also provides an important environmental service, which should be considered.

5.3. An Estimate of Environmental Benefits

Thus, an important aspect to be considered is related to environmental benefits, namely how much CO₂ could be saved with this solar energy initiative? Figure 12 shows the estimates of CO₂ that could be saved per year for each simulated case in the study. Case 3 (greater electricity generation capacity) could avoid approximately 4.59 tons/year of CO₂, which corresponds to 114.75 tons of CO₂ avoided in 25 years, thus contributing to the reduction of the carbon footprint.

In addition to the environmental benefits mentioned, it is important to highlight the positive economic impacts associated with the reduction of CO₂ emissions. The decrease of 4.59 tons of CO₂ per year, as presented in Case 3, not only contributes to climate-change mitigation but also can result in significant savings in terms of carbon credits and public health costs [60].

6. Conclusions

From a sustainable development perspective, this work presented the modeling of a solar distributed generation system as an alternative for income generation and energy autonomy for low-income populations. A simulated experiment conducted as a case study with households in the Jacaré-Curituba rural settlement in the Brazilian semiarid region demonstrates the viability of solar energy as a source of income (social energy income) for people living in socially, economically, and climatically vulnerable regions. According to the scenarios analyzed, the income from energy generation is alternative or complementary to the ones issued by public social welfare programs, among which the Bolsa Família allowance is one of the most prominent. The most viable scenario (case 3) indicates that households would have an income 102.21% higher than their current earnings with the BF transfer value (USD 118.88). It is important to emphasize that the cost-benefit analysis may be more positive, considering the Brazilian government’s proposal to reduce import taxes on solar panels.

Producing solar energy as a source of income by selling the surplus is a possible way to liberate vulnerable populations from dependency on governmental aid to the poor. At the same time, it can greatly contribute to reducing GHG emissions, as evidenced in the estimates of the avoided CO₂ environmental benefits in Section 5.3. As observed in Case 3, the most viable system would save approximately 4.59 tons of CO₂ per year. Adopting a social energy income initiative in this region is also a guarantee of lower socio-environmental impacts, such as those produced by extreme and frequent droughts and the construction of large hydroelectric and thermoelectric power plants, thus, contributing to initiatives that prioritize the energy transition and actions that promote the mitigation of climate events, of which socially vulnerable populations are the most affected.

We conclude that the use of tradable solar energy can contribute to the autonomy of socio-environmentally vulnerable communities in an inclusive, equitable, and sustainable way. Additionally, we suggest the adoption of this idea by international development agencies in nations of the Global South, aligning with the global commitments to Sustainable Development Goals (SDGs), particularly SDG 7, which focuses on ensuring access to affordable, reliable, sustainable, and modern energy for all.