Photovoltaic System for Residential Energy Sustainability in Santa Elena, Ecuador

Abstract

The instability of the energy supply, growing demand and the need to reduce carbon emissions are priority challenges in developing countries such as Ecuador, where power outages affect productivity and generate economic losses. Therefore, solar energy is positioned as a sustainable alternative. The objective of this study is to evaluate a pilot photovoltaic (PV) system for residential housing in coastal areas in the Santa Elena province, Ecuador. The methodology included the following: (i) criteria for the selection of three representative residential housings; (ii) design of a distributed generation system using PVsyst software; and (iii) proposal of strategic guidelines for the design of PV systems. This proposed system proved to be environmentally friendly, achieving reductions of between 16.4 and 32 tonnes of CO₂ in the first 10 years. A return on investment (ROI) of 16 years was achieved for the low-demand (L) scenario, with 4 years for the medium-demand (M) scenario and 2 years for the high-demand (H) scenario. The sensitivity analysis showed that the Levelized Cost of Energy (LCOE) is more variable in the L scenario, requiring more efficient designs. It is proposed to diversify the Ecuadorian energy matrix through self-supply PV systems, which would reduce electricity costs by 6% of consumption (L scenario), 30% (M scenario), and 100% (H scenario). Although generation is concentrated during the day, the net metering scheme enables compensation for nighttime consumption without the need for batteries, thereby improving the system’s profitability. The high solar potential and high tariffs make the adoption of sustainable energy solutions a justifiable choice.

1. Introduction

The increase in CO₂ emissions is linked to the growing global population and rising energy demand [1,2]. In 2019, electricity generation alone accounted for 36.4 billion tons of CO₂ emissions [3]. Considering both the emissions generated and the initiatives outlined in the 2030 Agenda, by the end of 2024, the installed capacity of renewable energy sources had reached approximately 3870 GW [4], with solar power representing the largest share worldwide at 1141 GW [5,6], indicating a key energy alternative that can decrease carbon emissions for a sustainable future.

Renewable energies are obtained from inexhaustible natural resources or from resources that regenerate naturally and continuously [7,8]; they are essential in the fight against climate change [9]. They also foster economic development by creating new jobs and making it easier to supply electricity to remote areas, improving quality of life [10]. By diversifying the energy mix, renewable sources reduce dependence on a single source, take advantage of natural resources, and strengthen resilience to energy crises, thus contributing to environmental and economic development and helping countries adapt to global change [11,12].

Renewable sources include (i) solar energy, which is converted directly into electricity [13]; (ii) wind energy, which is produced through uneven atmospheric heating [14]; (iii) hydrogen, a clean fuel that still requires a high energy intensity to produce; (iv) geothermal energy, originating from the planet’s internal heat [15]; (v) tidal energy, produced by the gravitational effect exerted by the Moon and the Sun on the oceans; and (vi) biomass, which is produced from biodegradable organic matter [16] and requires careful management to avoid environmental impacts [17,18]. Although these sources are reliable, they depend on specific geographic and climatic conditions. By 2030, they are expected to provide nearly 40% of global electricity [19].

Renewable energies are crucial to achieving the four pillars of sustainable development: economic, social, environmental, and institutional [20,21]. It is, therefore, crucial to adopt an energy model that satisfies current needs without compromising those of the future [22,23]. Renewable energies also contribute to the achievement of the Sustainable Development Goals (SDGs) [24], by promoting access to clean sources (SDG 7) [25], boosting urban sustainability (SDG 11), promoting efficient use of resources (SDG 12), and reducing carbon emissions (SDG 13) [26].

Globally, the installed solar power capacity equals 9.8% of total energy generation. In Asia, it stands at 838 GW, more than two-thirds of which is in China (307 GW), followed by Japan and India (70 GW each), and South Korea and Vietnam (21 GW and 16.5 GW, respectively) [27]. In Europe, Germany leads with 41.22 GW, followed by Italy (19.27 GW), France (7.13 GW), and Spain (5.4 GW) [28].

In Latin America, Brazil is the main supplier of renewable energy, with 32 GW [29,30], followed by Mexico (12 GW) and Chile (9.5 GW). Argentina and Colombia each have less than 2 GW of installed capacity [31,32]. Costa Rica, Panama, Peru, Ecuador, and Paraguay depend heavily on hydropower and have electricity mixes that are almost entirely renewable [33]. Even so, droughts in Ecuador underscore the need to diversify energy sources and to integrate the interconnected approach of the water, energy, and food (WEF) nexus for the efficient management of territories [34,35].

Ecuador, due to its geographical location, has a diverse range of natural energy resources that can be utilized for electricity generation. [36,37]. In 2024, the country generated roughly 33,143.05 GWh of electricity from the following: (i) hydropower, 92%; (ii) thermal plants, 4%; (iii) imports, 3%; and (iv) solar and wind, less than 1% [38]. According to data from the Ministry of Energy and Mines, national electricity demand amounts to approximately 31,035.39 GWh per year [39,40].

PV solar energy can diversify the energy mix, enhance grid stability, and reduce emissions [41]. As an environmentally friendly source, PV also encourages small-scale generation, reducing the need for large infrastructure and cutting distribution losses [42] while lowering reliance on imported fossil fuels that emit greenhouse gases [43]. The balance between net metering and net billing allows for the use of energy surpluses. It remunerates differentiated rates [44], together with the use of bifacial modules that capture radiation on both sides with only 5–10% more cost [45], and transforms the PV scenario by improving production per square meter and allowing the dynamic adjustment of energy and installation costs [46], opening the way to more efficient, economical, and adaptable PV systems to different tariff and climatic contexts. The IEC 61727:2004 standard [47], Ecuador’s Organic Law on Energy Efficiency, and regulation ARCERNNR 008/23 stipulate the requirements and procedures for designing and installing grid-connected PV systems [48]. Efficient use and energy security in households ensure that consumers become not only producers but also responsible actors within the grid. According to data from the 2024 energy balance, between 2013 and 2023, Ecuador’s per capita energy use increased by 5.1%, and electricity consumption rose by 28.8% from 1304 kWh to 1680 kWh per person [39].

In terms of the benefits of PV systems, China’s Tengger Desert Solar Park (1.5 GW) stands out for using desert land without competing with agriculture [49]. Germany has pioneered residential PV through its Renewable Energy Sources Act (EEG), while France’s Cestas solar plant (300 MW) demonstrates how public–private partnerships spur investment [50,51]. In Mexico, policies such as the Electricity Industry Law and renewable energy auctions have led to projects like the Villanueva solar park (828 MW), one of the largest in Latin America [52].

According to 2024 statistics from the Ministry of Energy and the Agency for the Regulation and Control of Energy and Non-Renewable Natural Resources (ARCENNR) [53], energy consumption in Ecuador is distributed as follows: (i) 40–45% on the coast; (ii) 35–40% in the highlands; (iii) 10–15% in the Amazon; and (iv) 1–2% in the insular region. Our case study focuses on Santa Elena Province on the coast, where abundant hydropower is limited by climate variability, infrastructure problems, and a lack of maintenance [54], triggering nationwide power crises [55]. Ecuador suffered major blackouts in 1982, 1992, 2009, and 2024, the latter lasting up to 16 h amidst the worst drought in 61 years [56,57]. Solar and wind energy sources have become viable alternatives for households and high-demand sectors [58], offering practical and sustainable solutions [59,60].

This study addresses an underexplored gap in the national literature: the lack of energy models adaptable to rural areas within the cantons of Santa Elena province, despite their high solar potential. Its application is geared toward rural areas facing structural and economic constraints, including higher electricity rates despite recording consumption levels similar to those analyzed [61]. This is because, although the actual consumption time may be shorter, as many rural residents work in urban areas and spend much of the day away from home, distribution costs increase the value per kWh due to geographic dispersion and the connection type, among other factors. Furthermore, rural populations often face greater difficulties in accessing basic services, such as drinking water, connectivity, and formal employment, which exacerbates energy inequality. Consequently, this model offers a replicable solution that, in addition to improving access to clean and reliable energy, can reduce the economic burden on these households, narrow territorial equity gaps, and strengthen the social and environmental resilience of the territory. Therefore, the design of pilot PV systems represents a viable and efficient way to meet the energy demand [62]. The following research question is established: how a pilot proposal for PV systems would impact meeting residential energy demand in a rural coastal area.

The study also enables the establishment of strategic guidelines that will inform the design of public policies toward a more equitable and sustainable energy transition, where community participation is crucial. The objective of this study is to analyze the technical and environmental feasibility of a grid-connected PV system with net metering, designed for different levels of residential demand. Based on this pilot, the aim is to generate replicable net metering guidelines in rural areas with high solar potential, where structural and economic barriers persist. Additionally, a SWOT analysis (strengths, weaknesses, opportunities, and threats) was conducted, and the results were ranked using AHP (Analytic Hierarchy Process), a tool that assigns weights to criteria based on expert assessments [63].

2. Materials and Methods

This research analyzes the energy consumption of residential housings in the Santa Elena province. Given the high energy demand, this study proposes pilot PV systems as a sustainable alternative for the diversification of the energy matrix. A mixed qualitative–quantitative methodology was used, with a correlational approach to variables [64,65]. Key stages in PV panel design were analyzed by selecting three distinct consumption scenarios ranging from 200 to 2500 kWh per month on average, each drawn from a representative neighborhood in the province’s three cantons. Electricity bills were reviewed, their values were recorded, and patterns, trends, and relationships were identified [66]. This research followed the methodological framework shown in Figure 1, which comprises three stages: (i) determining case selection criteria; (ii) designing the distributed-generation system with PVsyst software (version 8.0.4) [67], which allows the simulation, sizing, and performance analysis of PV solar systems [68]; and (iii) identifying strategies for PV system design based on sustainability and environmental aspects, including a SWOT analysis conducted through focus group interviews to determine acquisition and installation costs for the PV system and potential savings on electricity bills. It is essential to validate the qualitative results of the SWOT analysis; therefore, the AHP method, a valuable tool for complex decision-making, was applied to compare strategic factors by assigning weights under expert criteria [69]. This methodological integration strengthens the objectivity of the analysis, prioritizes priorities, and reduces the subjectivity of individual criteria.

2.1. Selection Criteria for Case Study and Pilot Area

The location for this case study is Santa Elena Province, Ecuador (Figure 2b), which has roughly 98,230 occupied housings, 56.3% of which are in urban areas. According to Ecuador’s 2024 tariff schedule, the average monthly household electricity consumption reached 143.36 kWh, and Santa Elena Province recorded an annual demand of 446 GWh [70]. The study area was chosen using the following criteria:

• Prevailing solar radiation: Data based on the Solar Atlas published by the Ministry of Energy and Mines of Ecuador [71].
• Energy use: The region with the highest electricity use was selected [71].
• Solar potential of Santa Elena Province: Climatic data for 2025 for the pilot area were drawn from the PVsyst database [72].
• Pilot housings (scenarios): The housing selection considered residential consumption and economic factors (e.g., self-financing or government incentives) to represent different levels of household demand in a grid-connected design. Three residential homes—one in each canton—were selected (Figure 2c). In Santa Elena Canton, the high-demand (H) scenario has 14,542 housing units in 31 neighborhoods. Salinas Canton represents the medium-demand (M) scenario with 8715 housing units in 90 neighborhoods, and La Libertad Canton represents the low-demand (L) scenario with 29,377 housing units in 107 neighborhoods [73].

Characterization of Residential Consumption Scenarios and Tariff Structure

When characterizing consumption, only domestic use was considered, without distinguishing between the sizes of connected loads [74]. The residential tariff includes a fixed marketing charge in USD per consumer per month, along with variable charges based on energy consumption in USD/kWh [75]. The L scenario corresponds to energy consumption between 200 and 250 kWh/month, as lower values would not be economically viable. The M scenario ranges between 1001 and 1500 kWh/month, aligned with the provincial average consumption of 1079.06 kWh [76]. The H scenario covers consumption from 1501 to 2500 kWh/month (

Table 1. Identification of scenarios and residential consumer rate values. Source: adapted from the tariff schedule [74].

Voltage Level	Energy (USD/kWh)	Voltage Level	Energy (USD/kWh)
1–50	0.091	351–500	0.105
51–100	0.093	501–700	0.1285
101–150	0.095	701–1000	0.145
151–200	0.097	1001–1500 (M)	0.1709
201–250 (L)	0.099	1501–2500 (H)	0.2752
251–300	0.101	2501–3500 *	0.436
301–350	0.103	>3500	0.6812

Note: * shows the electric energy consumption considered in the three scenarios for residential buildings: (L) low-demand scenario; (M) medium-demand scenario; and (H) high-demand scenario.

). This classification, based on energy use, allows for an evaluation of the technical and economic feasibility of solar power, considering the actual demand and local economic conditions.

Using the established scenarios (L, M, and H), monthly electricity bill data from the year 2024 were used to calculate the energy demand and size in each scenario according to its specific conditions. This data was obtained from the National Electricity Corporation (CNEL, acronym in Spanish) [77]. Subsequently, the number of solar panels and inverters required in each case was determined to estimate the initial cost, electricity bill savings, and return on investment (

Table 2. Consumption and billing for scenarios. Source: adapted from CNEL [77].

Scenario	Jan *	Feb *	Mar *	Apr *	May *	Jun *	Jul *	Aug *	Sep *	Oct *	Nov *	Dec *	Total *
L	149	124	138	202	208	180	201	167	180	134	137	126	1946
M	1000	900	850	800	750	900	1000	950	850	800	900	1000	10,700
H	2700	2609	2490	2475	2400	2200	2490	2491	2480	2486	2500	2600	29,921

Note: unit: * kWh/months.

).

Hourly energy consumption profiles were also constructed for the three dwellings, using daily electricity consumption data to determine peak and off-peak hours. The validation was performed with residential consumption data extracted from the Open Energy Data Initiative (OEDI) platform, which provides representative information on residential energy consumption in areas similar to the study area [78]. Cross-validation was applied with data from the National Renewable Energy Laboratory (NREL) [79,80,81].

2.2. Proposed Design of PV System

This section outlines the design of a customized pilot PV system for each scenario, utilizing PVsyst software (version 8.0.4), which takes into account the location, Incidence Angle Modifier (IAM), panel tilt, and shading conditions [82]. This software was selected for its high accuracy in hourly simulation of PV systems, its regulatory support (IEC 61724), 3D modeling, orientation analysis, and adaptation to local climate data [83,84]. Additionally, PVsyst has a good calibration capability for specific conditions in Ecuador, making it an ideal tool for assessing the feasibility of PV systems in the contexts evaluated in this study. The use of other tools, such as HOMER Pro, SAM, and RETScreen, was discarded because they are more oriented toward the analysis of hybrid systems or applications in isolated rural areas [85,86]

The pilot PV design meets the energy requirements of residential dwellings proposed by Zhong Q and Tong D [87]:

• Sizing the PV system: according to the actual energy demand of the users.
• Optimization of panel layout: considering the orientation, inclination and possible obstructions to maximize solar gain.
• Incorporation of solar exposure time and daily electricity generation patterns: obtained from simulations in the PVsyst software, improving energy production as a function of the solar radiation available during the day.
• Evaluation of the performance of the modules: based on the angle of incidence of solar radiation, using the IAM index as an efficiency parameter that emphasizes the precise sizing of the photovoltaic system.

The layout of the panels was optimized to maximize performance, considering solar time and daily energy generation. The IAM quantifies how the efficiency of a solar panel varies depending on the angle at which sunlight strikes its surface. It is presented as a percentage indicating variations in the angle at which light reaches the panel (

Table 3. Influence of IAM on system performance losses.

0°	30°	50°	60°	70°	75°	80°	85°	90°
1	0.999	0.987	0.962	0.892	0.816	0.681	0.44	0

) [88]. For instance, an IAM of 0.95 means that the panel operates at 95% of its maximum efficiency when sunlight hits it at a given angle.

2.2.1. Determination of the PV System Configuration

The pilot PV systems will be installed on the roofs of the selected housings, instead of the ground installation due to technical and practical factors such as the following: (i) Santa Elena is an urban area with limited space availability at ground level, while rooftops offer underutilized surfaces ideal for solar collection; (ii) rooftop installation minimizes the risk of shading caused by surrounding obstacles, such as walls, vegetation, or pedestrian and vehicular traffic; (iii) vulnerability to physical damage and vandalism is reduced, an important aspect in residential areas; and (iv) additional costs related to support structures and civil works required for ground-mounted installations are avoided [89,90].

Several factors were analyzed to optimize the system design according to energy needs. These first three parameters were used as input data and entered into the PVsyst software, which then determined the required number of panels and inverters.

• Orientation of solar panels: Determines the amount of sunlight captured and the system’s efficiency relative to the sun and the horizon.
• Panel tilt angle: Optimizes energy capture relative to a horizontal plane. For maximum efficiency, sunlight should strike the panels perpendicularly at 90 degrees [91].
• Shading: Reduces panel performance and causes power loss in the system [92].
• Solar panels: Convert sunlight into electrical energy through silicon-based PV cells, generating direct current (DC) [13]. There are several types of solar panels: monocrystalline—highest efficiency, requires less space; polycrystalline—lower cost, slightly less efficient; thin-film—lower efficiency, but flexible and lightweight [93].
• Inverter: Transforms direct current (DC) into alternating current (AC), suitable for domestic use [94].
• Direct solar radiation: Solar energy that reaches the earth’s surface without being scattered in the atmosphere, which occurs when the sun is fully visible [95].
• Diffuse radiation: Reaches a surface after being scattered in the atmosphere or reflected in various directions. It accounts for a larger share in winter and represents approximately 55% of global radiation annually [96].
• Albedo solar radiation: Refers to the fraction of solar irradiance reflected by a surface. Horizontal surfaces receive minimal reflected radiation, while vertical surfaces capture the most [97].
• Global solar radiation: Corresponds to the combination of direct and diffuse radiation [98]. The PVsyst software incorporates a location-specific radiation database, which improves the accuracy of the simulations.

2.2.2. Matriz de Sensibilidad

This technique is used to evaluate the impact of different climatic and operational parameters on the performance of PV systems. Baseline values obtained from the PVsyst software were used: Global Horizontal Irradiance (GHI) (4574 kWh/m²/day), Cloudiness (33%), Temperature (24 °C), soiling and degradation. From these data, variation scenarios were introduced for solar radiation (±10%), Cloudiness (±20% of cloudy days), ambient Temperature (±5 °C), soiling losses (+5% and +10%), and annual degradation rates (1.0% and 1.5%, against a baseline of 0.5%). These data were obtained from the adjusted PVsyst technical model and validated with scientific literature [99,100], which ensures consistency and relevance in Ecuadorian climatic contexts.

2.3. Strategies for PV System Design

This section presents a technical–environmental analysis considering parameters such as the investment cost, return on investment (ROI), Energy Payback Time (EPBT), Levelized Cost of Energy (LCOE), Relative Energy Efficiency (REE), and project sustainability through a Life Cycle Assessment (LCA). Additionally, a SWOT matrix was applied, consisting of internal factors (strengths and weaknesses) and external factors (opportunities and threats), which supports strategic planning [101] to evaluate the project’s viability.

2.3.1. Technical–Environmental Analysis

The ROI was estimated using the energy consumption data in kWh captured by the PV system and multiplied by the applicable electricity tariff. ROI was calculated using Equation (1), provided by the PVsyst software [83,102]:

$$\mathrm{R}\mathrm{O}\mathrm{I}={\mathrm{R}}_{\mathrm{t}}+{\mathrm{S}\mathrm{e}\mathrm{l}\mathrm{f}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{u}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{s}\mathrm{a}\mathrm{v}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{f}\mathrm{o}\mathrm{r} \mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}_{\mathrm{t}}+{\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{e}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{l}\mathrm{o}\mathrm{a}\mathrm{n} \mathrm{f}\mathrm{o}\mathrm{r} \mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}_{\mathrm{t}}$$

(1)

In the above equation:

R_t (net balance of year): obtained by subtracting the expenses from the income generated by the PV system in a given year after taxes;

Self-consumption saving for the year: the portion of income or benefit generated during a period that is not distributed or spent;

Redemption part of the loan for the year: refers to the repayment of the principal sum, not including the interest associated with the annuity [102].

The sustainability of the PV system was assessed by conducting an LCA, a comprehensive environmental approach for evaluating PV systems. The LCA includes the following phases: (i) panel manufacturing, (ii) inverters, (iii) mounting structures, (iv) transportation, and (v) end-of-life disposal. Each phase contributes differently to the system’s overall environmental footprint [103]. PVsyst software was used to analyze each phase of the life cycle, from resource extraction to final disposal, allowing for a comprehensive assessment of environmental impacts. Potential environmental impacts were evaluated considering factors such as the reduction in CO₂ using the REE, the EPBT, and the LCOE.

REE is defined as the ratio between the energy generated by the system and the energy consumed in its operation and maintenance phases [104]. This parameter was calculated to assess the system’s performance in terms of energy use, allowing for a comparison across the three scenarios (L, M, and H) and identifying opportunities for improvement. REE also helps determine whether the system meets efficiency standards and justifies potential adjustments in operation or maintenance, thus evaluating the system’s energy performance over its useful life.

The EPBT was calculated as the ratio between the total energy used in the Life Cycle Assessment (LCA) stages and the energy produced during operation [105]. The energy incorporated in manufacturing was included, as it represents the largest energy consumption, with estimated values ranging from 500 to 800 kWh per installed kW [106]. The EPBT calculation enables the determination of the time required to recover the energy invested in the manufacturing and operation of the system. Finally, the LCOE represents the value of all costs associated with the installation, operation, maintenance, and financing of a PV system, divided by the total amount of energy expected to be generated over its lifetime [107]. This indicator allows different technologies or generation projects to be compared under homogeneous conditions, as it reflects the average cost per kilowatt-hour produced.

2.3.2. SWOT and AHP Analysis

The CO₂ emissions balance was performed to quantify the emissions generated at each stage, offering a detailed view of the carbon footprint and associated climate impacts. The strategic sustainability guidelines for the pilot PV system in residential housing were established using a qualitative matrix (SWOT). This analysis enables the identification of internal factors (strengths and weaknesses) and external factors (opportunities and threats) [78], within the energy sector framework of the study area.

This methodology was complemented with the application of the AHP approach, which allowed a quantitative characterization of the main SWOT strategies. For this purpose, the criteria of seven experts from the energy sector were considered. The selection of the panel of experts was based on the following three criteria: (a) minimum ten years of professional experience in the energy sector; (b) fourth-level academic training in renewable energies; and (c) working in public, private, or academic institutions. These criteria ensured a multidisciplinary and sectoral representation for the proposal of strategic guidelines in these systems. The information was collected through an online focus group with 11 questions, applied online through Microsoft Forms (Table S1), aimed at identifying efficient renewable sources, as well as their impact on economic savings, efficiency, and sustainability. The experts assigned scores to the selected factors on a scale of 1 to 5, where 1 represents low importance and 5 represents high relative relevance among the elements compared. This evaluation allowed the generation of a weighting matrix, identifying the most decisive factors for the sustainability of the proposed PV system [69].

3. Results

3.1. Characteristics of Pilot Area

Figure 3 shows areas with predominant solar resources, which facilitate the planning and design of PV projects in the study region. The annual Global Horizontal Irradiance (GHI) in continental Ecuador averages 4.574 kWh/m²/day [108]. The Santa Elena province was selected as a study area due to its favorable climatic conditions: (i) high solar radiation (4.5–5.5 kWh/m²/day) [109], (ii) an average annual temperature of 25.4 °C, and (iii) an average of six to eight hours of direct sunlight per day [110]. These characteristics make this case study a favorable environment for PV development. The PVsyst software features a geo-referenced, monthly meteorological database, enabling more accurate modeling of the energy yield in each scenario. These data were validated with the Solar Atlas of Ecuador [111], ensuring the reliability of the solar potential represented (Table S2). This condition favors a high yield of solar panels in the region [112]. Solar time varies throughout the year: the dry season (June to December) typically offers the most favorable conditions for solar generation, and during the rainy season, although there are fewer hours of sunlight, solar generation remains favorable due to the high levels of radiation on cloudy days [113]. However, the adoption of solar energy in Santa Elena is still incipient due to the following factors: (i) unmet energy needs in coastal areas and (ii) climate variability, which affects the sole energy supply source—hydropower and thermoelectricity—from the National Interconnected System (NIS).

3.1.1. Energy Consumption Profiles

In the elaboration of the hourly load profiles, three key consumption ranges were identified: (i) low consumption during daylight hours (06:00–14:00), associated with the absence of people for work or study; (ii) medium load in the afternoon (14:00–18:00), linked to the return home; and (iii) night peak (18:00–22:00), due to the use of lighting, household appliances, and air conditioning equipment (Figure 4). Although this peak occurs outside the hours of maximum solar generation (10:00–14:00), the mismatch is compensated for by the grid connection. With net metering schemes, surplus energy generated during the day can be fed into the grid and offset against nighttime consumption, eliminating the need for batteries, reducing costs, and improving cost-effectiveness. This model is feasible in urban areas with an electricity grid, provided that there is a regulation that recognizes the value of the energy injected and encourages citizen participation in the energy transition.

3.1.2. Analysis of Solar Generation Profile

The highest solar generation occurs between 11:00 and 14:00 [114], with peaks exceeding 660 Wh in March and April. In contrast, July and August see a decrease due to cloud cover (Figure 5). This diurnal profile enables the application of net metering schemes, compensating for nighttime consumption without requiring batteries, thereby improving the system’s profitability. By integrating the hourly demand and generation profiles, the technical design is optimized, estimating surpluses and improving the viability of the residential system. Using data from the Solar Atlas of Ecuador [115], an hourly and monthly generation profile was obtained to compare energy supply and demand throughout the day.

3.2. Proposed Design of PV Systems

The energy yield was estimated using climatic data for the study area, along with energy consumption and available sunshine hours, simulated using PVsyst software to account for both the electricity delivered to the house and fed into the grid. The PV modules were designed to be installed on the roofs of houses, oriented to the north, and with optimal tilt angles between 20° and 30°, as determined by simulations in PVsyst. This configuration optimizes solar gain without occupying additional ground. The available surfaces (35 m² to 102 m²) were sufficient for the three scenarios (L, M, and H), ensuring the physical feasibility of the system in the rural coastal environment of Santa Elena, with proximity to urbanized zones (

Table 4. Technical specifications and losses of the proposed PV system.

Solar Panel		Inverter
Technology	Mono-crystalline bifacial module with (half-cell twin) technology	Technology	Generic
Unit power	500 Wp	Nominal Power	7.5 kWac
Design Specifications		System Design Losses (%)
DC/AC ratio	1.07	Temperature	6.00
System inclination	20°	Module mismatch	2.00
Orientation (azimuth)	0° north	DC wiring	1.00
		Module quality	0.40
Shading	not present	Irradiance	0.60
		Total global	11.70

).

The values considered respond to local climatic conditions, such as moderately high temperatures and the high presence of dust or salinity. For maintenance costs, a variable annual operating cost was included, depending on the scenario, which encompassed tasks such as cleaning the modules. This study recognizes the need to strengthen the sensitivity analysis by incorporating financial variables, such as inflation, discount rates, and variability in installation costs, which will be integrated into future research to improve the accuracy and realism of the long-term economic assessment.

Table 5. Sizing results for the three scenarios (L: low; M: medium; H: high).

Parameter	L	M	H	Unit
Azimuth	20	20	20	°
N° panels	5	16	35	units
Inverter	1	1	3
Annual energy	1946.16	10,700	35,080	kWh/year
Energy prod annual	2241.5	12,481	38,172
Pnom total of panels	1.50	8	25	kWp
Pnom total of inverter	1.80	7.5	18.8	kWac
Modules (string × in series)	1 × 5	1 × 8	5 × 7	-
Panels area	7.1	35	102	m2
Perf ratio (Pr)	83.42%	87.10%	86.96%	%
Solar fraction (SF)	41.79%	41.55%	41.25%	%

shows the system sizing for the three scenarios. The L scenario represents an average national household consumption level. It has the lowest tariff compared to the other scenarios and is ideal for assessing how the system performs under low-yield conditions and whether it is economically viable. The M scenario reflects a realistic condition for PV system design, in which both energy production and grid injection are significantly higher and more profitable. The H scenario represents an extreme energy-consumption case that only a few households reach monthly, typically due to proximity to small businesses or micro-enterprises.

Impact of Variables on PV System Viability

This approach allowed us to analyze how these factors affect energy production, such as LCOE, EPBT, and ROI, in the three proposed scenarios. Scenario L showed higher sensitivity to climatic and operational variations, highlighting the importance of maintenance, proper siting, and the use of appropriate technologies to maximize the performance of the PV system. In Figure 6a, solar radiation (GHI ± 10%) was the factor with the greatest impact, generating variations of up to 13% or reductions of more than 11% in production. The LCOE was particularly sensitive to fouling, increasing costs by up to 10% (Figure 6b), and was also affected by cloud cover and annual degradation. In general, PV generation is strongly dependent on radiation and cloud cover, while temperature and other factors such as dust or wear and tear have a lesser impact. This analysis enables the anticipation of risks and optimization of system design.

The EPBT measures the years required for the system to generate energy equivalent to that used in its manufacture and is more sensitive to fouling (+10%) and annual degradation (+1.5%), reaching up to 2.5 years in the L scenario. In contrast, in the M and H scenarios, it remains below two years (Figure 7a). Regarding the ROI, the lower-consumption systems have longer payback periods (15–18 years), while in the H scenario, it is reduced to less than 5 years, even under adverse conditions (Figure 7b). It demonstrates that PV systems are more cost-effective and efficient on a larger scale and that proper maintenance is key to optimizing their long-term performance.

3.3. Benefits of PV System Design

An efficient design of PV systems requires consideration of the initial investment in line with Ecuadorian conditions. This includes costs for panels, inverters, mounting structures, installation, permits, environmental licenses, and annual maintenance, the latter depending on the installation area, particularly whether it experiences low or high levels of particulate matter accumulation and regular rainfall (Table S3). This analysis allowed for projections of potential electricity bill savings, as given below.

In low-consumption scenarios (L), a 6% reduction in electricity bills was observed, with a 16-year payback period. In medium-consumption scenarios (M), savings reached 30%, with a 4-year ROI. In high-consumption scenarios (H), savings rose to 103%, with a 2-year payback period, demonstrating superior economic efficiency, achieving LCOE values of 0.02 USD/kWh. The H scenario also generates additional income, improving the system’s financial feasibility. In contrast, the M scenario and L scenario showed higher LCOE values (0.0567 and 0.0556 USD/kWh, respectively), though they maintained low operating costs across all cases, supporting long-term sustainability (

Table 6. Total data of the proposed PV system in Santa Elena Province.

System Summary	L	M	H	Unit
Total installation cost	4038.8	7985.6	16,182	USD
Operating costs	100	200	250	USD/year
Useful energy from solar	813	891	14,500	Kwh/year
Energy sold to the grid	1428	8036	23,700	Kwh/year
Cost of produced energy (LCOE)	0.0567	0.0556	0.020	USD/kWh

Note: LCOE: Levelized Cost of Energy.

).

In the L scenario (Figure 8a), the system shows an REE of 56.03, indicating a low level of utilization of input energy and a large margin for improvement in converting sunlight to electricity. In the M scenario (Figure 8b), the REE increases to 78, reflecting better energy efficiency. Finally, in the H scenario (Figure 8c), with an REE of 80, the system makes optimal use of input energy, resulting in a lower carbon footprint.

PV systems, which do not rely on fossil fuels, have a lower environmental footprint and contribute to energy savings in households. The net emissions balance, which is positive in all analyzed cases, reveals a significant reduction in CO₂ emissions over the system’s life cycle, confirming PV technology as a sustainable and effective option for mitigating climate change (

Table 7. CO₂ emissions balance in the PV system design scenarios.

Data for Emissions Balance	L Scenario	M Scenario	H Scenario	Unit
Required capacity	2	8	24	kWp
Embodied energy	1000	4000	12,000	kWh
Manufacturing emissions	100	400	1200	Kg CO2
Energy generated over 25 years	56,038.25	312,000	954,250	kWh
Emissions avoided	2.60	99.5	304.4	t CO2
System output	2241.53	12,480	38,170	kWh/yr
Grid life cycle emissions	319	319	319	gCO2/kWh
Lifespan	25	25	25	years
Annual degradation	1	1	1	%
EPBT	0.44	0.32	0.31	years
Net balance	13.3	83	265.1	t CO2

). The EPBT analysis across the three scenarios yielded an average of 0.36 years (less than 5 months), highlighting the high efficiency of this technology—even when accounting for manufacturing, transportation, installation, and end-of-life disposal stages. Over the lifetime (25 years), PV systems generate between 56,025 and 954,250 kWh [116], with a considerably smaller environmental footprint compared to fossil-fuel-based energy sources.

3.4. Proposed Strategic Guidelines

A SWOT matrix was applied by integrating the results of the technical–environmental analysis conducted in Santa Elena Province. This interconnected approach ensures the feasibility of the design, making it replicable in other regions, and supports both the energy transition and climate change mitigation. The SWOT analysis provided insights into the current status of the study, highlighting areas for improvement and identifying key factors that influence system performance, which are crucial for informed decision-making. The identified strengths should be leveraged to advance the decarbonization of the electricity sector and to differentiate PV systems from other renewable or conventional energy sources, as well as to guide strategies associated with the sustainability of residential housing (

Table 8. SWOT analysis and housing sustainability strategies for PV systems.

Strengths (Internal, Positive)	Opportunities (External, Positive)
S1: Interest in PV energy projects for sustainable housing in Santa Elena Province. S2: Harnessing solar energy as a long-term sustainable power source. S3: Reduction in dependence on the conventional power grid and increased energy autonomy.	O1: Reduction of carbon footprint and improvement of air quality. O2: Development of strategic plans for sustainable residential energy consumption. O3: Dissemination and support for PV system training by academia, technicians, and companies.
Weaknesses (Internal, Negative)	Threats (External, Negative)
W1: High initial investment required for PV systems. W2: Limited training for technicians and the general public on PV systems. W3: Economic limitations for purchasing PV equipment and software for analyzing complex hybrid systems.	T1: Public resistance to training in PV system design. T2: Climate–technical limitations that may affect the performance of PV systems. T3: High taxes on PV system equipment.

).

The experts ranked the SWOT analysis factors using the AHP method, highlighting strengths (4.30) and opportunities (4.30) (SO = 8.60), such as high solar potential and interest in reducing the carbon footprint, over weaknesses (4.30) and threats (4.20) (WT = 8.50), centered on the initial investment and tax burden. The higher weights reflect a favorable environment for implementing PV systems in Ecuador, provided economic barriers are addressed. A FO strategy that leverages local advantages is recommended to drive a sustainable energy transition in Santa Elena (

Table 9. AHP analysis and housing sustainability strategies for PV systems.

SWOT Categories	Factor Weight	Factor Intensity	Total Intensity
S1: Interest in PV energy projects for sustainable housing in Santa Elena Province.	30	4	1.2
S2: Harnessing solar energy as a long-term sustainable power source.	50	5	2.5
S3: Reduction in dependence on the conventional power grid and increased energy autonomy.	20	3	0.6
O1: Reduction of carbon footprint and improvement of air quality.	50	5	2.5
O2: Development of strategic plans for sustainable residential energy consumption.	30	4	1.2
O3: Dissemination and support for PV system training by academia, technicians, and companies.	20	3	0.6
W1: High initial investment required for PV systems.	50	5	2.5
W2: Limited training for technicians and the general public on PV systems.	30	4	1.2
W3: Economic limitations for purchasing PV equipment and software for analyzing complex hybrid systems.	20	3	0.6
T1: Public resistance to training in PV system design.	15	2	0.3
T2: Climate–technical limitations that may affect the performance of PV systems.	35	4	1.4
T3: High taxes on PV system equipment.	50	5	2.5

).

This integration of qualitative (SWOT) and quantitative (AHP) methods allows for the reduction of biases in the criteria considered for the proposed strategic guidelines, which are aligned with efficient decision-making, considering the priority needs of the study in the Ecuadorian energy context, with an emphasis on sustainability and the incorporation of clean energy, as detailed below:

• Implement net-metering tariffs for the national electric grid, adapting the existing regulatory framework for residential users.
• Promote strategic alliances between public and private entities, taking advantage of financial resources and technical capacities for the development of PV projects.
• Consider the integration of hybrid energy sources, such as solar-wind and solar-biomass combinations, in order to generate employment and strengthen resilience to energy crises.
• Develop an energy contingency plan that includes risk assessments, environmental solution design, and community training.
• Reduce taxes on solar PV equipment to improve the market supply and accessibility of solar panels.
• Encourage training programs in PV system design for both technicians and the general public to reduce technical limitations.

4. Discussion

This study analyzed how a pilot proposal for grid-connected PV systems can meet the energy demand in areas with residential dwellings, located in rural coastal environments, using a technical and environmental approach. The Santa Elena province has an average solar radiation of more than 5.3 kWh/m²/day and over 4.5 solar peak hours per day [111], which enables high PV generation. This model, applicable in grid-connected rural regions, can be replicated in areas that share similar consumption patterns and frequently experience power outages. Grid connection with net metering schemes enables the energy injected during the day to be offset by nighttime consumption, eliminating the need for batteries and increasing the cost-effectiveness of the system, while encouraging its adoption [55,117].

This proposal integrates a sustainable energy model that reduces emissions, promotes energy autonomy, and strengthens local resilience, responding to the need to diversify the energy matrix in vulnerable areas. This energy policy, although not yet officially implemented in Ecuador, has proven effective in promoting the adoption of solar technologies by allowing users to reduce their energy costs and maximize the use of self-generated energy. Given this regulatory gap, it is proposed that the national regulatory framework be updated to include net metering tariffs for grid-connected residential users. In addition, the development of these systems requires promoting strategic alliances between the public and private sectors, leveraging financial resources, technical capacities, and existing distribution networks to reduce costs and facilitate the implementation of clean technologies [118,119].

One of the main priorities is to implement net metering tariffs in the national power grid by adapting the existing regulatory framework for residential users [55]. These partnerships would allow for the development of replicable solar microgrid models in residential areas of Santa Elena, contributing to the modernization of the electricity sector and facilitating the transition to clean energy sources in the province. Thirdly, it is recommended to incorporate hybrid energy sources (solar–wind, solar–biomass) in order to diversify the energy matrix and strengthen resilience to crises caused by droughts or supply disruptions.

Given that climate variability in Santa Elena affects hydropower generation and has led to the installation of polluting thermal plants, hybrid systems represent a long-term sustainable solution. This integration not only enables a more constant supply but also creates green jobs and promotes energy autonomy, as demonstrated by models implemented in Mexico [120], it has been shown that distributed solar generation must be complemented by other renewable sources to diversify the energy mix and Argentina and Brazil serve as clear examples of the impact of distributed solar generation [121].

This study proposes integrating PV systems in homes near rural areas, with an estimated coverage of 60–90% of demand through clean energy, which would reduce up to 85% of annual CO₂ emissions and guarantee operational continuity in the event of grid failures. Unlike hydropower, PV systems do not have a negative impact on ecosystems [122]. Additionally, the energy transition fosters smart communities through employment, training, and local autonomy (SDG 11). Even if savings do not exceed 90%, the model remains viable thanks to an optimized design based on consumption patterns, local tariffs, net metering, and efficiency.

The creation of an energy contingency plan that includes risk assessments, environmental solution design, and community training processes is essential in the face of extreme events such as droughts. Such a plan would enable efficient responses to energy emergencies without resorting to fossil fuels, thereby mitigating greenhouse gas emissions and strengthening local energy security. Dey B, Bhattacharyya B, and Márquez FPG [123] point out that during such events, backup power plants are often installed, but at the cost of increased emissions. For this reason, solar PV-based solutions remain preferable due to their low environmental impact and adaptability to various scenarios.

It is also important to consider reducing taxes on solar PV equipment to enhance accessibility and competitiveness in the national market. Despite the high solar potential in the coastal city of Guayaquil, Guayas Province (5.3 kWh/m²/day), the high initial cost of the systems and the absence of tax incentives limit their large-scale adoption [124].

Net metering enabled a 1:1 offset to the retail price, significantly improving the economic viability of PV systems compared to net billing [125]. Cost reductions of 20% to 45%, efficiency improvements of 15% to 30%, and ROI acceleration by up to 40% reinforce its adoption. Experiences in Poland, Mexico, and Spain validate this policy, provided that incentives, local cooperation, and a clear legal framework are implemented [44,126,127]. In Ecuador, where it is not yet formalized, it is proposed as a strategic pillar, particularly in regions such as Santa Elena, a national policy design with the following: (i) fair compensation tariffs, (ii) simplified regulatory framework, and (iii) promotion of energy communities [124].

It is estimated that solar PV can cover 70–100% of the residential demand, depending on system size and consumption habits worldwide [128]. That is demonstrated in the case of the Caribbean, where grid-connected systems compensate for more than 100% of annual consumption through net metering, without requiring batteries. Although a detailed hourly analysis was not applied, local profiles were used to show the generation–demand gap [129]. PV panels have a lifetime of more than 25 years and an EPBT that ranges from 1 to 1.5 years, generating between 6 and 25 times the energy used in their manufacture [130,131,132], which validates their long-term sustainability [103,133]. This model is applicable in low-demand urban and rural areas, offering a resilient and viable solution, especially with community support. However, its adoption of residential PV systems faces key challenges, such as low energy literacy, which can lead to user rejection or misuse [134]. Additionally, many urban electricity grids are not equipped to handle bi-directional energy redirection, necessitating infrastructure upgrades [135]. In areas with a high concentration of PV systems, overloads and stability problems can also occur if adequate control mechanisms are not implemented [136].

From a technical–economic standpoint, initial PV system costs in Santa Elena are lower than in Guayaquil, where urban restrictions can raise installation costs by up to 25%. In Santa Elena, thanks to a favorable geography, lower population density, and simplified logistics, the average cost of PV systems ranges between 850 and 1000 USD/kWp [137], compared to 1100–1300 USD/kWp in Guayaquil [138]. Moreover, compared to Andean cities in Ecuador, such as Loja (4.5 kWh/m²/day) [109] or Cuenca (4.7 kWh/m²/day) [139], Santa Elena exceeds 5.3 kWh/m²/day, improving the annual energy output [108]. A policy of exemptions or subsidies could replicate successful cases like those in La Guajira (Colombia), Arequipa, and Tacna (Peru), where such fiscal incentives have helped achieve LCOE values between 0.025 and 0.035 USD/kWh [140,141]. The use of renewable energy reduces dependence on thermal and hydroelectric sources, lowers CO₂ emissions, and minimizes water usage. By generating electricity without burning fossil fuels, solar PV helps mitigate climate change, protect ecosystems, and encourage energy decentralization.

The LCOE allows a comparison of different technologies, such as solar, wind, geothermal, and biomass (Figure 9). LCOE values for these technologies depend on several factors: (i) for solar PV, costs vary by system location and size; (ii) wind power is less viable in areas with irregular wind patterns; (iii) geothermal energy requires specialized infrastructure; and (iv) biomass involves high operational costs and is less common for residential applications. The integration of multiple renewable technologies is essential to ensure a sustainable and efficient energy transition [35,142]. Laboratory-scale studies on CO₂ can help understand the behavior of carbon emissions [143].

Lastly, it is essential to promote technical training for the design of PV systems, targeting both technicians and the general public. This will reduce existing technical limitations and allow for more efficient implementation. In cities like Loja and Cuenca, training initiatives have improved the use of solar radiation and allowed systems to be adapted to local consumption patterns [109,139]. Urban growth and the intensive use of air conditioning systems in both the industrial and residential sectors in Brazil are leading to an increase in energy consumption [145], making the incorporation of efficient inverters indispensable to guarantee stability of the supply [146].

The system proposed in this study is designed for residential homes in Santa Elena, considering the high solar potential (above 5 kWh/m²/day), local energy consumption profiles, economic conditions, and demographic characteristics. The methodology used includes calculations of ROI, EPBT, and LCOE, expert interviews, and SWOT analysis (Table 7).

In Ecuador, important differences are observed among provinces: in Loja, low energy consumption results in high PV performance, whereas in Esmeraldas, the intensive use of inefficient appliances requires higher capacity systems [147,148]. These differences highlight the need to adapt designs to each specific context.

The design of the pilot PV system was based on 500 Wp bifacial modules, capable of capturing radiation on both sides, which increases electricity generation by up to 20% compared to monofacial panels, depending on the albedo, mounting type, and height from the ground [149]. This technology is ideal for coastal areas such as Santa Elena, where light surfaces, concrete, and high diffuse radiation enhance the collection of reflected radiation. Giuseppe et al. (2021) confirm that these modules significantly improve performance in urban environments with similar characteristics [149].

For future studies, comparisons with monofacial modules are recommended, considering the additional production costs, as the generation gain of bifacials may vary depending on factors such as the soil albedo, system orientation, and presence of shading. In addition, by analyzing the impact on the LCOE, it can be determined whether the increased initial investment associated with bifacials is compensated for by increased energy production over their lifetime [150]. Within the structural aspects, installing solar panels on residential roofs was considered because in urban areas, such as Santa Elena, ground space is limited, and roofs represent available and efficient surfaces for solar gain. This option reduces the risk of shading, physical damage, or vandalism, and avoids the costs associated with additional structures. In addition, modeling of the three consumption scenarios confirmed that the area required for installation is smaller than the available roof area of each house, validating the technical feasibility of the design [151,152,153].

A detailed analysis of energy data in Santa Elena, combined with lessons learned from national and international case studies, could establish a solid strategic and regulatory framework to support energy diversification and investment in clean technologies. Therefore, the strategies proposed in this study were oriented towards the following: (i) net metering to improve cost-effectiveness and facilitate adoption; (ii) reduction of up-front costs; (iii) public–private partnerships to finance and modernize the system; (iv) hybrid systems (solar–wind, solar–biomass) to improve resilience to crises; (v) energy contingency plans to mitigate the effects of droughts or other extreme events; (vi) community technical training to ensure efficient implementation and maintenance; and (vii) designs adapted to the local consumption and climate profile: allowing for greater efficiency.

5. Conclusions

Solar energy has established itself as a leading alternative for sustainable generation worldwide, contributing to a reduction in CO₂ emissions. In this study, the PV system proved to be environmentally viable due to the following: (i) the high level of local solar radiation, which guarantees stable generation with a capacity factor of 22.7%, higher than the national average (18.4%); (ii) an optimized technical design, with a northward orientation, a 20° to 30° inclination, and shading considerations that minimize losses; (iii) community participation, which strengthens energy sustainability by reducing the environmental impact, economic savings, and resilience; and (iv) grid connection, which enables efficient management, surplus marketing, and sustainable development. The evaluation was supported by local time profiles, simulations in PVsyst, and a hierarchical SWOT analysis with AHP, in which strengths and opportunities reached a value of 4.30, surpassing weaknesses and threats (4.20). The SW and OT combinations obtained scores of 8.60 and 8.50, respectively, thus supporting the viability of the system in areas with high solar potential and high electricity rates.

The PV system proposed in this study is efficient, allowing CO₂ emissions to be reduced by 32 tons in the L scenario, 28.6 tons in the M scenario, and 16 tons in the H scenario during the first 10 years of operation. Furthermore, the estimated payback periods are 16, 4, and 2 years, respectively. In the evaluated scenarios, it was observed that 2 kWp systems (201–250 kWh/month) recover investment in 14–16 years, 8 kWp systems (approx. 1000 kWh/month) in 4–6 years, and 24 kWp systems (1500 kWh/month) in 2–3 years.

Given these findings, there is a growing interest in solar projects in Santa Elena, with the aim of promoting energy autonomy and reducing emissions. However, the province still faces obstacles such as high start-up costs, limited technical training, and an unfavorable regulatory framework. To boost adoption, the following strategies are proposed: net-metering implementation; tax reduction; public–private partnerships; diversification of hybrid sources (e.g., solar–wind, solar–biomass); and development of energy contingency plans. These strategic guidelines focus on diversifying Ecuador’s energy mix through a self-supply PV system, which would reduce household power bills by 6%, 30%, and 103% for low, medium, and high consumption levels, respectively. Residential PV systems can be tailored to local conditions, helping to reduce greenhouse gas emissions, strengthen energy resilience, and lower household electricity costs. The proposed system presents a replicable model for clean energy transition in similar coastal regions with high solar potential.

For future research, the following lines of inquiry are proposed: (i) the effective implementation of PV systems with community participation through technical training; (ii) the development of governance tools, such as technical guidelines, monitoring platforms, and incentive policies, to facilitate investment; (iii) the optimization of solar energy use in the residential sector; (iv) the optimization of solar energy use in the residential sector; (v) the incorporation of innovative technologies to optimize the efficiency of PV systems; and (vi) promoting efficient architectural designs using renewable energy to reduce energy consumption in homes.