Carbon Credit Earned by Rooftop PV Systems: Assessing Opportunities for Carbon Market Adoption in the Ecuadorian Context

Abstract

This study assessed the techno-economic and environmental feasibility of a grid-connected PV system on a university building, with a focus on potential revenue from carbon credit sales. The analysis assumes a regulated CO₂ emissions market in Ecuador and references carbon credit prices from the European Union, New Zealand, China, and the Republic of Korea. Seven PV system configurations, varying in size and capacity, were modeled using Homer Pro and assessed for their techno-economic feasibility and environmental performance. The results indicated that the 166 kWp system was the most promising, supplying approximately 74% of the building’s electricity demand. Thus, this system was selected as the baseline for evaluating potential revenues from carbon credit sales in international markets, based on average carbon prices in 2022. The selected markets generated annual revenues of USD 4410.68, USD 2587.55, USD 446.34, and USD 958.37, respectively. While these additional revenues improved the Net Present Value (NPV) of the 166 kWp system, the overall NPV remained negative due to the high initial investment costs.

1. Introduction

Despite ongoing efforts to improve energy efficiency and reduce power consumption, the building sector continues to experience a yearly increase in both direct and indirect CO₂ emissions [1]. During building operations, direct emissions are generated by equipment based on coal, oil, and natural gas combustion [2]. Meanwhile, indirect emissions result primarily from electricity generation in fossil fuel-based power plants. As a result, combined direct and indirect CO₂ emissions from the building sector (both residential and non-residential) accounted for 28% of total global emissions in 2019 [3]. Moreover, energy consumption in this sector remained stable from year to year. However, there was a significant increase in emissions due to using electricity from fossil fuels [4]. In 2022, direct emissions reached 3 Gt, while indirect emissions were approximately 6.8 Gt, totaling 9.8 Gt CO₂, a level comparable to total emissions in 2021 [5]. China and the USA were the major polluting countries in 2012 and 2022, jointly contributing over 40% of global emissions in both years [6]. In South America, Brazil, Argentina, and Venezuela are the primary contributors to CO₂ emissions from fossil fuel combustion in energy consumption and production [7]. According to statistics from the Emissions Database for Global Atmospheric Research (EDGAR), these three countries accounted for 1.29%, 0.5%, and 0.28% of total global emissions in 2021 [8]. These emissions reached around 783 Mt CO₂. In Ecuador, CO₂ emissions increased from 17.59 Mt in 1990 to 41.14 Mt in 2021. Meanwhile, Latin America and the Caribbean collectively emitted around 1438 Mt CO₂ in 2020, according to World Bank statistics [9].

The electricity production sector is one of the fastest-growing contributors of CO₂ emissions and plays a crucial role in supporting various societal sectors, including buildings, industry, and transportation. High levels of CO₂ are a key factor in global warming and cause permanent damage to the natural environment [10]. Electricity generation facilities emit significant amounts of CO₂, largely depending on the type of primary energy source used, such as coal, oil, and natural gas. Notably, buildings (residential and commercial) account for over half of global electricity consumption. Electricity generation facilities emit significant amounts of CO₂, largely depending on the type of primary energy source used, such as coal, oil, and natural gas. Notably, buildings (residential and commercial) account for over half of global electricity consumption [11]. A considerable portion of a building’s electricity use is dedicated to heating and cooling systems, with demand steadily increasing each year. In the United States, 25% of greenhouse gas (GHG) emissions in 2021 originated from the electricity production sector [12]. That same year, a key factor contributing to the resurgence of coal-based electricity generation was the record-high price of natural gas [13]. In Ecuador, power plants accounted for 6.2% of GHG emissions in 2022, with per capita emissions reaching 2.3 tCO₂/inhabitant, significantly lower than the rate observed in developed countries such as the United States (17.1 tCO₂/inhabitant) [14]. On a global scale, CO₂ emissions from the electricity and heat production sector increased by over 900 Mt in 2021 compared to the previous year, while emissions from the building sector rose by 167 Mt [15]. Additionally, global CO₂ emissions from fossil fuels and industry increased by 5.17% in 2021 [16]. Between 2019 and 2022, average annual emissions from power production were approximately 14.17 Gt, while the building sector contributed an average of 2.94 Gt during the same period [17].

As a major contributor to CO₂ emissions in most countries, the electricity production sector is well suited for inclusion in emissions trading systems [18]. Carbon markets provide a framework in which electricity producers, whether companies or individuals, can offset their GHG emissions by purchasing carbon credits from organizations that actively reduce or remove GHG emissions through renewable energy projects [19]. Carbon markets serve as a mechanism for various stakeholders, including individuals, companies, and governments, to mitigate climate change by financially compensating entities that contribute to reducing atmospheric GHG accumulation [20]. Within these markets, carbon credits, which represent verified emission reductions, are traded under specific regulations established by governments or corporate compliance policies. These systems may operate under mandatory emission reduction frameworks or voluntary initiatives aimed at minimizing fossil fuel emissions [21]. In this context, participating stakeholders collectively agree to limit their total carbon emissions to a predefined cap. The system allows flexibility, as entities emitting more than their allocated share can purchase credits from those emitting less, provided the collective target is not exceeded [20]. Entities can acquire credits directly from CO₂ mitigation or absorption project developers or generate credits by implementing such projects themselves [22]. Carbon markets are generally classified into two categories: compliance markets and voluntary markets [23,24]. Compliance markets are established through national, regional, or international policies and regulations, requiring companies and governments to account for their emissions. In contrast, voluntary markets operate independently of regulatory frameworks, allowing public or private organizations to trade carbon credits at their discretion. Notable examples of compliance markets include the European Union, the California-Quebec market, and the systems in New Zealand, China, and the Republic of Korea. In terms of volume and value, compliance markets are significantly larger. In 2019, the regulated market accounted for approximately 3 billion tCO₂ with a market value of USD 23 billion, whereas the voluntary market traded 104 million tCO₂ with a value of USD 282.3 million [25].

This study assesses the techno-economic and environmental feasibility of a grid-connected PV system installed on a university building in Guayaquil, Ecuador. This city, characterized by a hot climate and substantial year-round solar potential, offers favorable conditions for PV deployment. The study modeled seven PV system scenarios based on the available physical space on three building rooftops, with installation capacities of 40 kWp, 60 kWp, and 66 kWp. Each scenario was evaluated in terms of renewable electricity penetration, along with its techno-economic and environmental performance. These analyses are obtained from the engineering simulation tool Homer Pro [26] with a project planning horizon of 25 years and an interest rate of 10%. For the environmental assessment, the reduction in indirect CO₂ emissions was calculated for each scenario using Ecuador’s Energy Matrix emission factor for 2023. Among the modeled configurations, the 166 kWp PV system demonstrated the most substantial reduction in indirect CO₂ emissions from the building. Consequently, this scenario was selected to assess its economic feasibility under a compliance carbon credit market framework.

The next section discusses the literature review. Methodology is demonstrated in Section 3. The results and discussion are summarized in Section 4. Finally, Section 5 is devoted to the conclusion.

2. Literature Review

Renewable energy projects are effective solutions for reducing indirect CO₂ emissions across various electricity-consuming sectors, including transportation, buildings, and industry. Several studies have examined the potential of these projects to prevent CO₂ emissions and generate carbon credits. Among renewable technologies, PV systems stand out as the most viable option for on-site electricity generation. On-grid PV systems are particularly advantageous for reducing grid electricity consumption and lowering a building’s carbon footprint due to their scalability, ease of operation, and steadily declining implementation costs [27,28]. The increasing electricity demand is driving the transition of buildings towards utilizing microgrid electricity to reduce their dependence on the grid [29].

Susilowatti et al. [30] estimated the Net Present Cost (NPC) and internal rate of return (IRR) for a solar and biomass-based power plant by modeling its operation across various locations in Indonesia. The project achieved an annual emission reduction of 22,371.32 tCO₂, equivalent to USD 447,426.32 per year, based on a carbon credit price of USD 20 per tCO₂. In a separate study, a simulated model presented in [31] demonstrated that a solar thermal plant and a PV plant achieved GHG emission reductions of 93,924 tCO₂ and 50,812 tCO₂, respectively. The primary distinction between these systems was the higher capital cost and greater installation complexity of the solar thermal plant compared to the PV system. Additionally, a large-scale grid-connected PV plant in a hot climate region achieved a reduction of 19,000 tCO₂ in 2018, based on evaluations using both actual data and simulations [32]. Buragohain et al. [33] evaluated the carbon reduction potential of a hybrid system, combining a solar PV plant and a biogas-fired generator, to assess the impact of a constant load. The net CO₂ mitigation achieved by the plant and generator were estimated at 35.97 tCO₂ and 68.62 tCO₂, respectively, resulting in a carbon credit value of USD 2090.31 (equivalent to EUR 16.32/tCO₂ or USD 19.91/tCO₂). Similarly, a project aimed at reducing diesel generator use was conducted in [34], where the authors estimated an annual emissions reduction of 187 tCO₂. In [35], a 200 kWp grid-connected PV plant in India mitigated 421.1 tCO₂ per year compared to thermal plants. The payback period for the project, including carbon credit revenues, was 10.7 years, 4.8 years shorter than the scenario without considering carbon credits. In the context of buildings, Hamzah and Go et al. [36] analyzed a PV system applied to a high-rise building, utilizing both the roof and facades. The system achieved total carbon savings of 10,367.66 tCO₂ per year, with a total renewable electricity production of 679.72 MWh. The study in [37] presents an economic analysis of a PV plant on a university campus in Italy, with installed capacities of 115 kW and 210 kW. For the 210 kW plant, the emission reduction reached 184.9 tCO₂ per year, generating approximately EUR 15,768 annually, based on a carbon credit rate of EUR 85.27/tCO₂. Agarwal et al. [38] modeled a PV plant for a university building with a planning horizon of 25 years. The optimal size of the plant was determined to be 42 kWp, yielding carbon credits of 47.96 tCO₂ per year, equivalent to USD 779 annually, at a rate of USD 16.24/tCO₂. It is important to note that many university campuses are adopting photovoltaic power systems to meet their decarbonization goals [39]. Carbon credits enhance the economic viability of renewable energy projects by providing additional financial revenue. These funds can be reinvested into new projects and initiatives aimed at further reducing emissions.

The carbon credit markets have evolved since the Kyoto Protocol, which established them as a mechanism for reducing or limiting GHG emissions [40]. However, their importance was further emphasized with the signing of the Paris Agreement, which set the goal of limiting the global average temperature increase to “well below” 2 °C above pre-industrial levels [41]. Since then, several carbon credit markets have been established worldwide to mitigate the impacts of climate change. In contrast, Latin America has yet to fully harness this potential. Mexico is the only country actively developing a voluntary carbon market since 1998. Following a reform to the General Law on Climate Change in 2018, Mexico became the first country in Latin America to initiate the development of an Emission Trading System [42]. Other countries have made limited efforts in the form of taxes, but comprehensive policies like a carbon credit market are still lacking. These markets present an opportunity for the region, as projects to mitigate emissions or contamination can generate additional revenues if an appropriate country or regional carbon market is established.

Ecuador currently lacks policies and regulations that support public or private organizations in generating carbon credits. Additionally, the country has no agreements with other nations for transferring CO₂ mitigation outcomes through renewable energy projects. However, in response to the severe energy crisis Ecuador has faced since 2023, the government is promoting the large-scale deployment of renewable energy projects, particularly PV systems, through new legislative developments [43]. Consequently, Ecuador presents potential opportunities for participating in international carbon credit markets.

3. Methodology

3.1. Description of City and Climate

Guayaquil, a port city situated in southwestern Ecuador, is the country’s largest urban center, with a population nearing 3 million inhabitants [44]. Due to its geographical location near the equator, Guayaquil experiences a tropical climate classified as Aw (tropical savannah) under the Köppen–Geiger system [45]. This climate results in minimal daily temperature fluctuations and two distinct seasons: the wet season (December to April) and the dry season (May to November). As depicted in Figure 1, the wet season exhibits the highest average monthly temperatures and solar irradiation levels, with April recording the peak average daily solar horizontal irradiation (5.17 kWh/m²/day) and March reaching the highest average ambient temperature (26.9 °C). Whereas the lowest average ambient temperature and solar horizontal irradiation are reached within the dry season, in August (24.7 °C) and October (3.64 kWh/m²/day), respectively.

Regarding wind potential, Guayaquil’s average annual wind speed is approximately 3 m/s during daytime and below 4 m/s at night (Figure 2b), which is relatively low to effectively utilize wind turbines for on-site electricity generation. Conversely, Guayaquil’s favorable solar resources (Figure 2a) present significant potential for developing PV solar energy projects.

3.2. Reference Building Description and Selected Areas for PV System Installation

The reference building, hereinafter referred to as 2A, is located on the “Escuela Superior Politecnica del Litoral (ESPOL)” campus in Guayaquil, Ecuador (2°11′21.89 S, 79°53′20.64 W) [47]. This three-story mixed-use facility (Figure 3) houses lecture classrooms, offices, and common spaces, covering a total floor area of approximately 3089 m². Building 2A serves as ESPOL’s College Admission Office and experiences its highest occupancy levels during three key periods of the academic calendar: February to April, May to August, and October to January. Meanwhile, office activities are consistent throughout the year, occurring on weekdays (Monday to Friday) from 08:00 to 16:30.

Building 2A has three unobstructed rooftops, which offer optimal conditions for PV module installation. As shown in Figure 4, the rooftops have the following effective areas: A1 = 280 m², A2 = 450 m², and A3 = 480 m². The total effective area for the installation of the PV modules was equivalent to 70% of the total rooftop area, as the spacing between the mounting metal structures and electrical connections was also considered.

3.3. Definition of Building Load Profile

The baseline energy demand profile for the building was established using data recorded by a digital energy meter installed at the case study site. Energy consumption was monitored for five months during the first semester of 2023 (February to June). To estimate the building’s total annual energy consumption, data for the remaining seven months were extrapolated from the measured data, adjusted according to the building’s operational schedule for offices and classrooms. Consequently, the building’s total annual electricity consumption was calculated as 297,699 kWh/year.

Figure 5 shows the estimated hourly power consumption for the building, representing the entire electricity demand profile of the building, i.e., the overlapped electricity consumption of the office spaces and classrooms. The profiles account for typical daily consumption patterns observed during the wet and dry seasons, reflecting seasonal variations in energy use.

3.4. Description of Proposed Solar PV System for Electrification in Building 2A

The installed capacity of the PV modules was determined based on the standard size of a selected commercial PV module (2.31 m² = 0.45 kWp) and the estimated available rooftop areas are presented in Section 3.2.

Table 1. The installed capacity of the PV modules in the estimated areas for mounting on the building’s rooftops.

Areas	Estimated Area for PV Modules (m2)	Module Number	Installed Capacity (kW)
A1	196	85	40
A2	315	136	60
A3	336	146	66

outlines the installed PV capacities for each rooftop (A1, A2, and A3), accounting for 70% of the total available area on each rooftop to ensure adequate spacing for mounting structures and electrical connections.

Figure 6 illustrates the schematic of the proposed grid-connected PV power system to supply electricity to building 2A.

3.5. Modeling in Homer Pro

Homer Pro^® is a simulation tool designed for modeling and optimizing renewable and non-renewable power systems [26]. HOMER Pro is a powerful tool for energy system optimization, especially in the analysis of microgrids and hybrid systems. Its advantages include the ability to model a wide variety of energy configurations, ease of use, and the integration of multiple energy sources, storage, and generators. It also allows for detailed analyses of the levelized cost of energy and the Net Present Cost, facilitating informed decision-making. The results obtained from Homer Pro are based on key equations that account for various system parameters.

The power output of a PV power system (P_{out_PV}) is given by Equation (1). This expression considers the effect of the temperature on the PV modules.

$$P_{out\_PV}=Yf{\displaystyle \frac{G_T}{G_{T,STC}}}\left(1+{\alpha }_p\left(T_c-T_{c,STC}\right)\right)$$

(1)

where $Y$ is the power output of PV modules under Standard Test Conditions (STC); f is the derating factor of PV modules; G_T is the incident radiation in the current timestep (kW/m²); G_T,STC is the irradiation under STC; α_p is the temperature coefficient of power (%/°C); T_c is the cell temperature of PV modules in °C; and T_c,STC is the temperature of the PV modules under STC.

The renewable fraction (RF), representing the proportion of energy supplied to the electrical load by renewable sources in microgrids or other systems, is calculated as follows:

$$RF=1-{\displaystyle \frac{E_{gen}}{E_{aec}}}$$

(2)

where E_gen represents the annual non-renewable electricity production [kWh/year] and E_aec corresponds to the electricity consumed by the load, including the electricity sold to the grid [kWh/year]. This equation does not consider thermal loads or energy production of this type.

The economic feasibility analysis determines whether a project is financially viable. To assess this, the Net Present Value (NPV) is employed as key evaluation criterion [48]. This metric is defined as follows:

$$NPV=\sum _{t=1}^n{\displaystyle \frac{A_t}{{\left(1+r\right)}^t}}-C{I}_0$$

(3)

where $A_t$ represents a specific flow in period $t$, n is the horizon planning, ${\left(1+r\right)}^t$ represents the discount factor, and $C{I}_0$ is the initial capital or investment at t = 0. A project is considered profitable if its NPV is above 0, this means that the benefits surpass the costs. In addition, among the different projects considered profitable (NPV > 0), the one with the highest NPV is always chosen.

Figure 7 shows the layout for each scenario in the Homer Pro environment. Since the primary objective of this analysis is to assess the investment required to electrify building 2A using PV energy, the scenarios in Figure 7 depict different combinations of PV module areas based on Table 1.

3.6. Techno-Economic Specifications for Modeling Proposed Scenarios

Table 2. Techno-economic specifications of components used in each PV power system.

Component	Description
PV module	Capacity, 0.45 kW; Area, 2.31 m2; efficiency, 20.3%; type, monocrystalline; annual degradation, 0.55%; temperature coefficient, −0.35%/°C; operating temperature, 45 °C; lifespan, 25 years; capital cost, USD 300; O&M, USD 20/year; replace cost, USD 250
DC/AC Power converter	Efficiency, 98%; lifespan, 10 years; capital cost = replacement cost, USD 150 per kW

shows the techno-economic specifications of the components of each scenario.

The interest rate applied in this study was set at 10%, representing the effective rate for passive operations in the Ecuadorian financial system for credits exceeding one year [49]. The project’s planning horizon was established at 25 years, with replacement costs for system components assumed to be equivalent to their initial capital costs. To estimate these capital costs, component prices available in the Ecuadorian market were utilized. The operation and maintenance (O&M) costs for the PV modules also include expenses related to the power converter. Additionally, each proposed scenario accounts for fixed costs and control/monitoring equipment for the PV system. Fixed costs encompass expenses for equipment transportation, assembly, electrical panel construction, and component wiring.

ESPOL was classified as a Public Benefit entity by the Ecuadorian Public Electricity Company, which grants it access to a subsidized electricity tariff distinct from the standard residential rate [50]. Specifically, ESPOL is categorized as a medium voltage-regulated consumer (greater than 0.6 kV and less than 40 kV).

Table 3. Electricity tariffs applicable to ESPOL [50].

Schedule	Demand USD/kW/Month	Tariffs USD/kWh
From 08:00 to 22:00	2.622	0.060
From 22:00 to 08:00		0.050

summarizes the primary grid electricity tariffs applicable to ESPOL based on this classification.

In Ecuador, consumers can reduce their grid energy consumption by injecting electricity generated from PV power systems. When electricity consumption from the grid exceeds the electricity generated by the PV modules, the consumer pays the difference to the distribution company based on their respective tariff category [51]. Similarly, surplus electricity from these systems can be injected into the grid, with compensation based on the same rates and time bands outlined in Table 3. However, the electricity injected into the grid is credited to the consumer, reducing the following month’s electricity bill.

3.7. CO₂ Emission Factor for Renewable Projects in Ecuador

HOMER Pro^® calculates the indirect CO₂ emissions from primary power plants by multiplying the electricity consumed by the electrical load (building) from the grid by an emission factor (EF). This factor represents the CO₂ emissions per unit of energy generated (e.g., tCO₂/MWh, kgCO₂/kWh) and can vary slightly over time or between countries [52]. For Ecuador’s National Interconnected System, the expression to quantify the EF for PV power projects $\left({FE}_{CM}\right)$ is as follows [53]:

$${FE}_{CM}={FE}_{OP}·{\beta }_{OP}+{FE}_{CN}·{\beta }_{CN}$$

(4)

where ${FE}_{OP}$ and ${FE}_{CN}$ are the emission factors during the operation and construction stages of the project, respectively. ${\beta }_{OP}$ and ${\beta }_{CN}$ are their respective weighting factors. The present project considers ${\beta }_{OP}$ and ${\beta }_{CN}$ of 0.75 and 0.25 for the operation and construction phases, respectively. Factors ${FE}_{OP}$ and ${FE}_{CN}$ are 0.5015 tCO₂/MWh and 0.00 tCO₂/MWh, respectively. Finally, the EF for the grid used by the university building was 0.3761 tCO₂/MWh in 2022.

3.8. Carbon Market Approach

In 2023, there were 28 regulated carbon markets worldwide in the form of emissions trading systems [54]. These markets covered 17% of global emissions, equivalent to 9 Gt. In these markets, the price of carbon credits is determined by supply and demand specific to each market [55]. However, prices vary significantly from scheme to scheme. Figure 8 shows the price evolution of carbon credits in regulated carbon markets from 2018 to 2023 [56]. During this period, prices reached approximately USD 100/tCO₂, with the EU market having the highest prices, followed by New Zealand, while other markets remained below USD 40/tCO₂. Figure 9 shows the carbon price evolution in these markets during 2022. The average carbon credit prices in these compliance markets were USD 85.28/tCO₂ for the EU, USD 50.03/tCO₂ for New Zealand, USD 8.63/tCO₂ for China, and USD 18.53/tCO₂ for the Republic of Korea.

In this context, and following the studies of [30,33,35,38], an analysis of four additional scenarios was conducted to evaluate the economic feasibility of selling the carbon emission reductions generated by the project. Given that Ecuador is not currently participating in any carbon markets, the present work considers the average carbon prices in 2022 of the EU, New Zealand, China, and the Republic of Korean markets, as shown in Figure 9. SC-7, with an installed capacity of 166 kWp, was chosen as the base scenario for receiving revenues from carbon credit sales in the aforementioned international markets. The economic feasibility of the following scenarios is then analyzed:

–

SC-7 (non-market): Economic feasibility of SC-7 without accounting for any carbon credit revenue.

–

New Zealand: Economic feasibility of SC-7, including carbon credit sales at the average price of the New Zealand market.

–

EU: Economic feasibility of SC-7, including carbon credit sales at the average price of the EU market.

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China: Economic feasibility of SC-7, including carbon credit sales at the average price of the China market.

–

Republic of Korea: Economic feasibility of SC-7, including carbon credit sales at the average price of the Republic of Korea market.

4. Results and Discussion

This section presents the analyses, optimizations, and simulations of SC-1 through SC-7 scenarios performed in Homer Pro^®. SC-7 was then chosen as the baseline to evaluate the economic feasibility, considering scenarios with carbon credit prices within four international markets.

4.1. Sizing of Power Converter and Its Annual Operation in Each Scenario

Table 4. Sizing and average annual operation of power converter in each scenario under study.

	Scenarios
	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
Characteristics	PV modules
Installed capacity (kW)	40	60	66	100	106	126	166
Characteristics	Power converter
Nominal capacity (kW)	50.00	65.00	70.00	110.00	120.00	130.00	175.00
Mean output (kW)	5.95	8.92	9.82	14.90	15.8	18.7	24.70
Maximum output (kW)	35.60	53.3	58.7	88.9	94.2	112.00	148.00
Hours of Operation	4380.00	4380.00	4380.00	4380.00	4380.00	4380.00	4380.00
Energy out (kWh/year)	52,122.00	78,183.00	86,001.00	130,305.00	138,123.00	164,184.00	216,306.00
Energy in (kWh/year)	53,186.00	79,778.00	87,756.00	132,964.00	140,942.00	167.535.00	220,720.00
Losses (kWh/year)	1064.00	1596.00	1755.00	2659.00	2819.00	3351.00	4414.00

shows the results of the sizing and average annual operation of the power converter in each scenario under study. The installed capacity of the PV modules for each scenario was previously established in Figure 7. Regarding the power converter, all scenarios demonstrate that the equipment operated for approximately half of the time, as it functioned only during daylight hours. Additionally, its nominal capacity varies across scenarios due to the increased installed capacity of PV modules in each rooftop. It is worth noting that the DC-to-AC conversion process carried out by the power converter resulted in losses in all scenarios.

4.2. Distribution of Electricity Production in Each of the Scenarios

The total electrical load for each scenario is 297,699 kWh/year. In this context, Figure 10 illustrates the distribution of electricity from both the grid and the PV modules to meet the electrical load demand, while also accounting for the renewable electricity injected into the grid. For electricity from the grid, it refers to the energy billed by the distribution utility to the user (building 2A). As shown in the figure, increasing the module area leads to a reduction in grid electricity usage, which is essential for lowering the carbon footprint of the proposed building. The electricity generated by the PV modules is converted into usable power via a power converter. The output of this converter determines the amount of renewable electricity supplied in each scenario.

As shown in Figure 10, the electricity above the dotted line corresponds to the surplus electricity of the PV module system in each scenario. These surpluses are injected into the grid, corresponding to “electricity sales to the grid” [57]. This injection of electricity reduces the consumption of electricity billed by the distribution company, thereby lowering the user’s electricity bill (building 2A). In SC-1, 18% of the total consumption was covered, with minimal grid injections, and this pattern remained consistent as the PV module area increased in each scenario. SC-7, on the other hand, covered 74% of the total building load consumption; however, the increase in the module area also significantly increased the amount of electricity injected into the grid.

Table 5. Electricity injected into grid from solar PV modules in each scenario.

Scenarios	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
kWh/year	7757	15,516	18,116	35,567	38,952	50,929	78,787

presents the average annual surpluses in each scenario that were injected into the main grid from the PV modules.

Table 6. Average annual renewable fraction in each proposed scenario.

Scenarios	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
FR (%/year)	17.1	25.0	27.2	39.1	41.0	47.1	57.5

presents the annual penetration levels of renewable electricity (given through RF) in each scenario.

4.3. Economic Feasibility of the Scenarios

Figure 11 shows the initial capital investment values for each scenario. It should be noted that these values include the costs of the equipment, as well as the costs detailed in Section 3.6. As the area of PV modules increases, the costs associated with mounting additional structures and monitoring equipment on the rooftops also rise.

Table 7. Building 2A’s average annual electricity payment in each scenario.

Scenarios	SC-0	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
Electricity (USD/year)	17,413.25	14,304.45	12,750.05	12,283.73	9641.24	9174.92	7620.52	4511.72
Demand (USD/year)	3644.19	3457.13	3388.48	3368.18	3264.91	3247.12	3189.22	3085.98
Total (USD/year)	21,057.44	17,761.58	16,138.53	15,651.91	12,906.15	12,422.04	10,809.74	7597.70
Reduction (%)	-	15.65	23.36	25.67	38.71	41.01	48.69	63.91

depicts the consumer’s average annual electricity payment in each scenario. These payments include the reduction in kWh injected into the grid, i.e., the difference between the electricity consumed from the grid minus the electricity injected into the grid by the PV modules, which is the electricity bill by the distribution company. In addition, the price of the power demand was also considered in the billing. The scenario with the highest PV capacity, SC-7, paid approximately 64% less electricity than the scenario without PV modules (SC-0). Likewise, the table shows the reductions in electricity bills for the other scenarios, considering SC-0 as a baseline.

Table 8. Summary of annual costs for each scenario.

	Scenarios
	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
Capital	−6325.00	−8934.63	−9565.34	−14,761.60	−15,454.91	−18,309.93	−23,641.15
Replacement	−441.38	−573.79	−617.93	−971.03	−1059.31	−1147.58	−1544.82
O&M	−19,539.00	−18,805.19	−18,585.24	−17,350.60	−17,133.16	−16,409.74	−14,975.47
Salvage	38.13	49.57	53.38	83.89	91.51	99.14	133.46
Total (USD/year)	−26,267.25	−28,264.04	−28,715.13	−32,999.34	−33,553.87	−35,768.11	−40,027.98

summarizes the total costs (revenues and expenses) for each scenario, considering capital, replacement, O&M, and salvage costs (Cash Flows of Scenarios SC-1 to SC-7 are provided in Supplementary Material S1). The capital required for larger PV module areas increases across different scenarios due to higher investments in equipment and fixed costs. Also, larger PV module areas demand more resources and infrastructure to ensure efficient operation and maintenance. O&M costs include the purchase of electricity from the grid as well as the revenue on the bill due to electricity injections to the grid from the PV modules.

Table 9. Summary of NPV profitability indicator for each scenario.

	Scenarios
	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
NPV (USD)	−238,433.58	−256,552.12	−260,646.20	−299,540.36	−304,568.63	−324,670.99	−363,331.70

summarizes the NPV profitability indicator. This indicator has negative values, indicating no return on investment in the scenarios presented, meaning each scenario results in a deficit. The high initial capital costs, combined with the need for competitive tariffs for renewable electricity generation, reduce the profitability of each scenario.

4.4. Annual CO₂ Emissions in Each Scenario

The results of the annual CO₂ emissions in each scenario can be seen in Figure 12. As mentioned in Section 3.7, this analysis uses Ecuador’s Energy Matrix, which applies an EF of 0.3761 tCO₂ per MWh of electricity consumed from the grid. This factor reflects the country’s primary electricity generation sources, including hydro, thermal, and non-conventional energy (such as solar, bioenergy, and wind energy). The electricity consumption of the total target electrical load for each scenario is 297,699 kWh/year, and considering the EF, the scenario without a renewable system (SC-0) produced 111,964.00 kg.CO₂ (111,964 tCO₂) annually. In comparison, SC-1 reported an emission of 95,279 kg CO₂, reflecting the highest carbon footprint due to the greatest reliance on conventional energy among all scenarios. However, as renewable electricity generation increases across the scenarios, emissions decrease significantly, with SC-7 achieving an annual emission value of 60,243 kg CO₂.

Table 10. Average annual CO₂ emission reductions in each scenario.

Scenarios	SC-1	SC-2	SC-3	SC-4	SC-5	SC-6	SC-7
Reductions (tCO2/year)	16.69	23.57	25.53	35.63	37.30	42.60	51.72

shows the average annual reductions of CO₂ emissions in each scenario, i.e., the emissions that were prevented from entering the atmosphere using a grid-connected PV power system, considering SC-0 the most polluting one. These reductions were calculated by subtracting the emissions from each scenario (as shown in Figure 12) from the emissions of SC-0, the highest emitter.

4.5. Economic Feasibility of SC-7 Considering Revenues from Carbon Markets

As indicated in Table 9, the profitability indicators show that the scenarios are not economically feasible. In this section, the economic feasibility of SC-7 is re-evaluated, incorporating additional revenues from the sale of carbon credits at average prices from international carbon markets. SC-7 was selected for this analysis because it achieves the greatest reduction in carbon emissions, making it the most suitable scenario to assess the potential profitability of carbon credit sales. In addition, the markets considered for analysis are the EU, New Zealand, China, and the Republic of Korea.

Table 11. Average prices of carbon credits during 2022 of selected markets.

Markets	EU	New Zealand	China	Republic of Korea
Price (USD/tCO2)	85.28	50.03	8.63	18.53

shows the average prices of these markets during 2022, which were obtained in Section 3.8. Based on the application of renewable energy to building 2A, considering the high, medium, and low prices of these markets, this analysis explores the impact of these prices on the economic profitability of SC-7.

Table 12. Additional annual cash flows for SC-7 generated by carbon prices from different carbon markets.

		Markets
	SC-7	UE	New Zealand	China	Republic of Korea
Annual revenues (USD/year)	0	4410.68	2587.55	446.34	958.37

provides a summary of the cash flows generated by SC-7 based on carbon prices from different carbon markets (Cash Flows of Carbon Market Scenarios are provided in Supplementary Material S2). Column 1 presents the scenario without accounting for any carbon credit prices, while the subsequent columns show the results for SC-7 with carbon credit prices from the markets under consideration. These results were derived by multiplying the emission reductions from SC-7, as shown in Table 10, by the average carbon credit prices presented in Table 11. The sale of the tons of CO₂ not emitted into the atmosphere in each scenario generates an annual cash flow, with the highest economic revenue coming from the EU carbon credit price, and the lowest revenue from the Chinese market price.

Table 13. Indicator of economic feasibility of SC-7 considering carbon credit prices in different markets.

	Scenarios
	SC-7	UE	New Zealand	China	Republic of Korea
NPV	−USD 363,331.70	−USD 323,304.84	−USD 339,853.46	−USD 359,289.29	−USD 354,641.60
Rd. (%) *	-	11.02	6.45	1.12	2.39

* Reduction in NPV of SC-7 considering revenue from sale of carbon credits.

shows the results of the economic feasibility analysis across the different carbon markets. The NPV results indicate that SC-7 was not profitable even if revenues from the sale of carbon credits in each market are considered. However, these revenues have produced different reductions in the negative NPVs, reaching the highest reduction in the EU market (11.02%) and the lowest in the Chinese market (1.12%). One of the causes of SC-7’s non-profitability was its high initial investment (USD 214,592.00) required to purchase PV modules and activities related to their assembly.

5. Conclusions

This study presents a techno-economic and environmental analysis of an on-grid solar PV power system designed to supply energy to a university building in Guayaquil-Ecuador. Firstly, we assessed seven scenarios based on varying PV module areas across the three available rooftops of building 2A. This analysis included economic profitability indicators, such as NPV, for each scenario, considering all revenues and expenses throughout the project’s lifecycle. Overall, the solar radiation level of the site, along with the system size, were found to be key factors influencing the economic performance of the PV system. This study demonstrated the potential for reducing the building’s grid dependence through the installation of various-sized PV systems, offering valuable insights for developers and stakeholders when evaluating investment options for similar solar PV projects.

It is worth noting that the purpose of this study was not to oversize the PV plant in order to maximize the selling of surpluses back to the grid. Instead, the proposed scenarios were evaluated to identify their potential to cover the largest possible electricity share based on the rooftop area restriction. In this regard, the 166 kW installed capacity scenario met 74% of the building’s annual electricity demand but also injected a considerable share of electricity into the grid. As a result, any system larger than 166 kW would primarily contribute to grid injections rather than fully meeting the building’s electricity demand. In contrast, the scenario with the lowest installed capacity reduced electricity consumption from the grid by 18% with minimal grid injections. The electricity bill also reflected the reductions related to renewable electricity use across each scenario, ranging from 15.65% to 63.91%.

From an environmental standpoint, the study evaluated the potential reduction in indirect CO₂ emissions during the building’s operational phase. In the absence of a renewable power system, the building emitted 111.96 tCO₂ annually. From this baseline and estimated CO₂ emissions from grid electricity use, we calculated the CO₂ emission reduction in each scenario, which reflects the emissions avoided by the grid-connected PV system. These reductions ranged from 16.69 tCO₂/year to 51.72 tCO₂/year, based on an emission factor of 0.3761 tCO₂ per MWh for Ecuador’s energy grid.

The results indicated that the seven scenarios were not financially feasible due to high initial investment costs and limited revenue streams. However, the inclusion of carbon credit revenues in SC-7 significantly improved its economic feasibility. Specifically, the NPV improvements ranged from 11% in the EU carbon credit market to 1% in the Chinese market. This suggests that Ecuador could enhance the economic viability of renewable energy projects by participating in carbon credit markets. These findings lead to two key economic and policy implications: (i) the need for carbon credit markets in developing countries, either at the national or regional level, and (ii) the importance of economic incentives for environmental protection. These incentives should aim to internalize the external costs of environmental pollution. Despite the availability of some incentives, we recommend the application of subsidies and grants to support the initial investment in clean energy projects. The initial investment costs across the scenarios ranged from USD 57,000 to nearly USD 215,000. Governments should thus play a role in stimulating clean energy projects by offering subsidies for acquiring PV system components or incentivizing the sale of surplus electricity to the grid. These initiatives are essential, as previous research has shown that consumer subsidies (e.g., feed-in tariffs and purchase price reductions) significantly impact demand. Additionally, subsidies encourage innovation and the improvement of PV module efficiency. By implementing such incentives, such as emission trading systems and subsidies, the government can foster innovation, attract investment in the green sector, help consumers and businesses reduce costs, promote greenhouse gas emissions reduction, and support environmental protection.

The main advantage of this paper lies in the fact that, so far, no studies have been conducted on carbon markets for renewable energy projects in educational buildings in Ecuador. This work is a roadmap to promote the widespread adoption of grid-connected PV systems in such buildings, aiming to facilitate potential carbon credit sales. However, a limitation is that the analysis focuses solely on three buildings, despite the university under study having many more constructions with rooftops that offer significant potential for PV system installation. Economies of scale in projects with larger PV module areas can significantly reduce initial investment costs. Purchasing equipment in large quantities allows for better price negotiations, optimization of material and infrastructure utilization, and more efficient allocation of fixed costs such as design, permits, and labor. Furthermore, advanced logistics and installation techniques can be implemented in larger-scale projects to enhance operational efficiency and reduce associated execution costs.