Next Article in Journal
Research on SOC Prediction of Lithium-Ion Batteries Based on OLHS-DBO-BP Neural Network
Previous Article in Journal
Life Cycle and Water Footprint Assessment in the Geothermal Energy Sector
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Analysis for the Implementation of Surplus Hydropower for Green Hydrogen Production in Ecuador

Departamento de Ingeniería Mecánica, Escuela Politécnica Nacional, Quito 170517, Ecuador
*
Author to whom correspondence should be addressed.
Energies 2024, 17(23), 6051; https://doi.org/10.3390/en17236051
Submission received: 11 October 2024 / Revised: 7 November 2024 / Accepted: 15 November 2024 / Published: 2 December 2024
(This article belongs to the Section A: Sustainable Energy)

Abstract

:
This study investigates the feasibility of utilizing surplus hydropower from Ecuador’s major hydroelectric plants to produce green hydrogen, a clean energy source that can be used to meet a large percentage of energy needs. Given Ecuador’s significant hydropower infrastructure, this approach leverages untapped energy resources for hydrogen production, with potential impacts on decarbonization strategies. A Pareto analysis identified five key hydroelectric plants that contribute the most to the national surplus. Using historical data from 2019 to 2023, a stochastic model was applied to estimate future surplus availability through 2030. The findings indicate that although Ecuador’s surplus hydropower peaked in 2021, the general trend shows a decline, suggesting an urgent need to capitalize on these resources efficiently. The results indicate a projected annual surplus of hydroelectric energy in Ecuador, ranging from 7475 to 3445 GWh over the next five years, which could be utilized for green hydrogen production. Ecuador thus has promising potential to become a green hydrogen producer, enhancing both regional energy security and carbon reduction goals. The reduction in energy availability for hydrogen production is attributed to the increasing energy demand and variable climatic conditions.

1. Introduction

The escalating challenges of climate change and the increasing urgency for sustainable energy solutions have accelerated the development of green technologies worldwide [1]. The Paris Agreement, aimed at limiting global warming to 1.5 °C, underscores the critical need for decarbonization across all sectors, with a particular emphasis on reducing greenhouse gas emissions from energy production [2,3]. Achieving these ambitious goals requires a shift from fossil fuels to renewable sources, along with scalable energy storage solutions that can support the stability of power grids heavily integrated with renewable energy [1]. Green hydrogen produced through electrolysis powered by hydropower has gained substantial attention as a carbon-neutral fuel that can help meet these decarbonization targets [4,5,6].
Hydropower-based green hydrogen production not only reduces greenhouse gas emissions, but also maximizes the efficiency of existing renewable infrastructure, positioning it as a promising strategy for large-scale decarbonization [7]. Practical implementations in countries like Norway and Canada demonstrate the feasibility of integrating hydrogen production with hydropower infrastructure as part of national clean energy strategies. These examples highlight the potential of hydropower-derived hydrogen to enhance grid stability by serving as a flexible energy storage and supply medium that can address fluctuations in both demand and generation. Moreover, green hydrogen production from surplus hydropower avoids energy waste, extending the utility of hydropower beyond direct electricity generation to sectors that are challenging to electrify, such as transportation and certain industrial processes [8]. This synergy establishes hydropower-based hydrogen production as a strategic solution for achieving sustainability goals and meeting climate commitments, underscoring its potential to significantly reduce global carbon footprints and enhance energy resilience across diverse regions.
Green hydrogen stands out for its ability to decarbonize hard-to-electrify sectors, such as heavy industry and transportation, where direct electrification remains challenging [9,10,11]. Unlike conventional hydrogen production, which relies on fossil fuels and emits significant CO₂, green hydrogen emits zero carbon emissions in its production phase, making it a crucial component in the transition to cleaner energy systems [12,13,14,15,16]. Additionally, as an energy carrier, hydrogen offers unique advantages for storing surplus renewable energy, particularly during periods of low demand or high generation. Studies indicate that green hydrogen’s potential to balance fluctuations in supply and demand enhances grid resilience and supports the integration of renewables, reducing the need to curtail excess energy during peak generation [3,17,18]. Thus, in the broader pursuit of carbon neutrality, green hydrogen is increasingly seen as an indispensable solution, bridging gaps in current energy infrastructure and enabling a more flexible, sustainable energy landscape. Ecuador, with its abundant hydropower resources, is well-positioned to explore green hydrogen as an innovative solution for sustainable energy [17,19,20,21].
Among the technological options for green hydrogen production, proton exchange membrane (PEM) electrolysis, alkaline electrolysis, and Solid Oxide Electrolysis (SOEC) stand out. PEM technology is particularly attractive due to its high hydrogen purity (99.99%) and efficiency, although it requires a significant initial investment [22]. Previous studies have assessed the Net Present Value (NPV) and Internal Rate of Return (IRR) of these technologies in different industrial contexts. In the case of PEM, an estimated NPV of USD 1.1 to USD 2 million and an IRR of 22.6% to 32.97% support its economic viability for large-scale industrial applications. In comparison, alkaline electrolysis and pyrolysis are viable alternatives but offer lower purity and efficiency levels, making them less profitable in the Ecuadorian context, given the country’s limited industrial infrastructure for hydrogen production [23,24].
Numerous studies have investigated the feasibility of producing green hydrogen from surplus renewable energy. Walker [25] demonstrated that electrolysis is an efficient method for converting surplus energy into hydrogen, identifying it as a viable storage solution during periods of low electricity demand. Liu et al. [26] explored solar-driven hydrogen production, focusing on photovoltaic (PV) and photoelectrochemical (PEC) cells. They discuss recent improvements that enhance the feasibility of solar hydrogen as a sustainable alternative, noting its potential in large-scale applications. Baykara [27] examined solar thermal hydrogen production, analyzing thermochemical cycles using concentrated solar energy. This study identifies solar thermal as a promising hydrogen production method, especially in regions with abundant sunlight, although it faces challenges with cost efficiency and technology readiness for large-scale implementation. Olateju and Kumar [28] evaluated wind energy-based hydrogen production in Canada, emphasizing the economic benefits of combining wind turbines with electrolysis. Their findings demonstrate that wind-based systems can produce hydrogen cost-effectively under favorable wind conditions. Zamfirescu and Dincer [29] conducted a study on geothermal energy for hydrogen production, highlighting that high-temperature electrolysis driven by geothermal heat can reduce hydrogen production costs. Their work suggests that geothermal resources offer a stable and clean hydrogen production pathway. Alizadeh et al. [30] focused on hydrogen production from geothermal energy, exploring how high-temperature geothermal sources can drive efficient hydrogen electrolysis. Their analysis suggests that geothermal energy provides a stable, continuous source for hydrogen production, making it economically feasible in geothermally rich regions. Similarly, Hunt et al. [31] analyzed hybrid systems that combine hydropower and green hydrogen production, concluding that existing hydropower infrastructure is well-suited for hydrogen generation. Other research by Quin Yu et al. [16] has highlighted green hydrogen’s potential to stabilize electrical grids, as hydrogen can serve as a flexible storage medium to mitigate fluctuations in renewable energy supply. Studies, such as those by Han et al. [32], highlight that hydrogen storage enhances grid resilience by managing renewable energy fluctuations, particularly during peak generation periods.
Technical and economic studies have been carried out to implement the production of green hydrogen. Naqvi et al. [33] analyzed advanced green hydrogen production methods, emphasizing the techno-economic progress in electrolysis, biomass gasification, and solar water splitting as sustainable pathways toward carbon reduction. Abbas et al. [22] examined the economic feasibility of hydrogen production using solar energy in Iraq, demonstrating its potential in regions with high solar availability. The study finds that solar hydrogen production can be both scalable and economically viable, positioning it as a key clean energy solution for solar-rich countries. Cook and Hagen [34] analyzed biomass gasification for hydrogen production in the U.S., showing how biomass delivery costs and local conditions impact economic feasibility. Their findings support biomass gasification as a viable low-emission hydrogen source, influenced significantly by site-specific factors. Nouwe Edou and Onwudili [35] compared thermochemical biohydrogen technologies focused on public transportation in the UK. Their analysis reveals strong economic potential for these technologies, especially for large-scale production in regions like the Midlands, contributing to a sustainable transport system. Hardana et al. [36] present a financial analysis of green hydrogen production using excess power from Indonesia’s small hydropower plants, showing it as a viable method for decarbonization. The study highlights the potential for integrating green hydrogen in national energy strategies through a cost-effective electrolyzer system. Reksten et al. [37] provide a cost prediction model for electrolyzer plants, considering factors like scale, technology improvements, and production volumes. Their findings underscore the importance of optimizing the levelized cost of hydrogen (LCOH) for green hydrogen competitiveness. Zwickl-Bernhard and Auer [38] analyzed the business potential of green hydrogen production from hydropower, emphasizing that excess hydropower is a viable renewable energy (RE) source for scalable green hydrogen production. They also explored the market opportunities for green hydrogen derived from hydropower. Abdin [39] explored the role of green hydrogen co-firing with natural gas as a sustainable option to reduce greenhouse gas emissions in power generation, showcasing co-firing as a pathway to decarbonize conventional energy systems while enhancing energy efficiency. Other studies on the carbon market are present. Idowu et al. [40] analyzed how industrialization affects CO₂ emissions differently in OPEC and developed nations. While emissions typically rise with industrial growth in developed countries, OPEC nations may reduce emissions through efficiency gains, informing region-specific sustainable policies. Cheng and Jiang [41] analyzed the dynamic links among China’s carbon, green bond, clean energy, and electricity markets, revealing that while carbon markets drive renewable energy growth long-term, events like COVID-19 heighten short-term volatility. Findings guide policies for strengthening market integration to support China’s low-carbon goals.
However, existing research predominantly focuses on developed nations, where renewable infrastructure and energy demand differ substantially from those in developing countries [20]. There is limited literature addressing the potential for green hydrogen production in Latin America, particularly in countries like Ecuador, which has significant hydropower resources but limited hydrogen initiatives [42,43,44,45,46]. Despite this potential, no studies have assessed Ecuador’s capacity to use its surplus hydropower for green hydrogen production, highlighting a research gap that this study aims to address.
The present works aims at the following: (1) Identification of Ecuador’s main hydroelectric plants using a Pareto analysis to determine the largest contributors to national energy production. (2) Calculation of surplus hydropower from the past five years that could be stored as hydrogen. (3) Projection of future surplus hydropower availability through to 2030 using a stochastic model. (4) Estimation of potential green hydrogen production based on identified surplus energy.

2. Methods

This study employs a systematic approach to analyze the energy landscape of Ecuador, with a particular focus on identifying surplus hydroelectric power for the production of green hydrogen. The first step involves determining the energy generation capacity of the main hydroelectric plants in the country. The data for this analysis were sourced from the annual reports of the national electric sector issued by the National Energy Control Center (CENACE) [42,43,44,45,46], and from National Energy Balance (BNE) reports from 2019 to 2023 [47,48]. Subsequently, a Pareto analysis is applied to identify the major plants contributing the most to the overall energy production. Statistical and energy modeling techniques are then employed to project surplus energy availability and assess its potential for green hydrogen production.

2.1. Identification of the Main Contributors to the Generation of Hydroelectric Power in Ecuador

The Pareto principle, widely applied in economics to optimize resource allocation, enables this study to concentrate on hydroelectric plants with the highest energy surpluses. This approach prioritizes high-impact plants, reducing costs and maximizing efficiency by identifying key contributors to green hydrogen production [49,50]. The hypothesis underlying this approach is that focusing on primary surplus-producing plants optimizes returns and offers a competitive advantage in the energy transition [51,52].
To evaluate the hydroelectric production landscape of the county, a Pareto chart was utilized as a statistical tool to identify the most significant contributors. The analysis focused on 2022, as it was the most recent year with comprehensive data available for all hydroelectric plants included in the study [42,43,44,45,46]. Annual production data from each major facility were collected, ranked in descending order based on output, and plotted to display their cumulative contribution to Ecuador’s total hydroelectric production.

2.2. Analysis of Surplus Energy Potential for Green Hydrogen Production in the Main Hydroelectric Plants

The analysis of surplus energy potential begins with the collection and verification of monthly data on the inflow (Qi), measured in m3/s, and the net energy (Et), in GWh, produced by the main hydroelectric plants from 2019 to 2023. This period was selected to reflect the stable operational phase of these plants. The data were sourced from annual energy reports to ensure accuracy and representativeness [42,43,44,45,46]. The assessment then considers Qi as the volumetric flow rate of water available to power the turbines, which is essential for calculating the maximum theoretical energy (Eteo) [53]. The next step involves evaluating the vertical distance between the water in the reservoir and the turbine outlets, knows as H (m). For the five hydroelectric plants selected through the Pareto analysis, the respective H values are 620 m, 667 m, 361.9 m, 213.4 m, and 54.62 m [54]. The assessment then incorporates constants such as the density of water (1000 kg/m3) and the acceleration due to gravity (9.81 m/s²) [53]. Additionally, average efficiency values for turbines (ηtr) and generators (ηg) were set at 90% and 96%, respectively. These averages are based on typical ranges for modern and efficient plants but may vary due to factors such as plant age, operational conditions, and maintenance [55,56]. The evaluation accounts for monthly operational time. Finally, the annual theoretical energy was calculated using Equation (1),
E t e o = η · ρ · g · H · t · i = 1 n = 12 Q i
where Qi is the average monthly flow rate in cubic meters per second for month i, and the summation from i = 1 to 12 represents the total inflow for the year.
Subsequently, the surplus energy (Esurplus) was determined as the difference between the available theoretical energy (Eteo) and the energy actually generated by the turbines (Et), as shown in Equation (2).
E s u r p l u s = E t e o E t
This analysis identified additional energy that was not converted into electricity. This surplus energy represents a valuable opportunity, as it can be utilized for various strategic purposes, including the production of green hydrogen. Leveraging this excess energy for green hydrogen production not only optimizes the utilization of available energy resources, but also supports the diversification of energy sources and the advancement of sustainable energy alternatives within the country [57,58].

2.3. Application of the Autoregressive Model for Projecting Surplus Energy

This section outlines the application of the AR(1) autoregressive model to analyze and project surplus energy trends at the five main hydroelectric plants in Ecuador. To project these trends, the AR(1) autoregressive and stochastic model, widely used for time series analysis in fields such as energy production, was employed [59]. This model is a fundamental tool for analyzing and forecasting time series behavior based on historical data [60]. A key characteristic of the AR(1) model is that prediction uncertainty increases as the forecast horizon extends. This is reflected in the widening prediction intervals, which account for the accumulation of uncertainty over time. Typically, confidence intervals quantify this uncertainty, offering a range within which future values are likely to fall. As with most statistical models, a 95% confidence level is commonly applied, providing a high probability that the true values will lie within the estimated range. The AR(1) model is represented in Equation (3):
X t = c + ϕ 1 X t 1 + ϵ t
where X t is the series value at time t, c is a constant (the model’s intercept), ϕ 1 is the autoregressive coefficient that quantifies the impact of the series’ first lag on the current value, and ϵ t is a random error term, assumed to follow a normal distribution with zero mean and constant variance, representing fluctuations that the linear model cannot explain.
In this case, the ϕ 1 value was estimated using the least squares method, which ensures model accuracy by minimizing the total difference between observed values and model-predicted values [55,56]. The terms c and ϵ t provide a comprehensive framework for modeling the time series, c adjusts the overall level of the series, while ϵ t   accommodates random and unpredictable factors affecting the data [60]. With ϕ 1 estimated, the AR(1) model equation was applied to predict surplus energy through 2030, focusing on the most recent data and replicating the pattern established by the AR(1) method [56,61].

2.4. Estimation of Potential Green Hydrogen Production

The potential for green hydrogen production from surplus energy can be determined using three key methods: proton exchange membrane (PEM) electrolysis, alkaline electrolysis, and Solid Oxide Electrolysis (SOEC). Each of these technologies has distinct efficiency levels and energy consumption rates, which directly influence the amount of hydrogen that can be generated from a fixed amount of surplus energy. Table 1 establishes these rates.

3. Results

This section presents a detailed analysis of surplus energy production at the five main hydroelectric plants in Ecuador. First, a Pareto analysis was conducted to identify the facilities with the highest impact on surplus generation, allowing for the prioritization of key plants for potential green hydrogen production. Subsequently, the levels of produced and potential surplus energy at each plant were analyzed, providing a comprehensive view of the current and future utilization of these resources. Finally, the total surplus energy generated by the five plants was estimated, highlighting their strategic contribution to supporting the country’s energy transition and sustainability goals.

3.1. Pareto Analysis Findings

Figure 1 presents a Pareto chart displaying the contributions of the main hydroelectric plants of Ecuador during 2022 in terms of energy generation (GWh). The blue bars represent each plant’s annual energy output, while the black dashed line shows the cumulative contribution as a percentage. This analysis allows us to identify the most impactful plants in hydroelectric energy production. As shown, Coca Codo Sinclair and Paute stand out, collectively accounting for a significant portion of the total output, followed by Sopladora, San Francisco and Marcel Laniado de Wind. These five plants generate the majority of the energy produced, indicating that they are key facilities for leveraging potential green hydrogen production. This prioritization approach is essential for optimizing energy resources and strategically planning the use of surplus energy in sustainability projects.
The analysis reveals that the Coca Codo Sinclair plant is by far the most prolific, generating an impressive 6828.15 GWh. Its dominant position within Ecuador’s energy landscape underscores its critical role as a cornerstone of the country’s hydroelectric infrastructure. Closely following is the Paute facility, with an annual production of 5150.65 GWh. Together, Coca Codo Sinclair and Paute form the backbone of Ecuador’s hydroelectric output, contributing substantially to the national energy supply and shaping the country’s generation profile.
Beyond these leading facilities, other plants like Sopladora, San Francisco, and Marcel Laniado de Wind also make significant contributions. Sopladora produces approximately 2544.99 GWh, while San Francisco and Marcel Laniado de Wind generate 1137.17 GWh and 1025.45 GWh, respectively [48]. Including these plants in the analysis provides a more comprehensive view of Ecuador’s generation capacity. Collectively, these top five plants account for over 80% of the country’s total hydroelectric production, as shown by the cumulative percentage line on the chart, which quickly reaches this threshold with the top-ranking facilities.
This distribution pattern, illustrated through Pareto analysis, confirms that a small subset of plants (five out of fifteen) produces the majority of hydroelectric power. The cumulative contribution line demonstrates how these key facilities’ substantial output optimizes the country’s energy resources. This concentration of production in a few installations is strategic for Ecuador, as it allows the energy sector to focus efforts and resources on these core plants for future initiatives, such as green hydrogen production. Leveraging the surplus energy from these main facilities could significantly enhance Ecuador’s energy diversification, and support its sustainability and energy transition goals.
Therefore, the Pareto chart not only identifies the most productive hydroelectric plants, but also enables a more efficient, targeted approach to surplus energy utilization. Coca Codo Sinclair, Paute, Sopladora, San Francisco, and Marcel Laniado de Wind stand out as strategic facilities that not only sustain the current energy infrastructure, but also present substantial opportunities for the development of sustainable energy projects.

3.2. Assessing the Potential of Surplus Energy at Hydroelectric Plants of Ecuador

This section, by means of Figure 2, presents a series of graphs depicting the annual energy production profiles of Ecuador’s five main hydroelectric plants: Coca Codo Sinclair, Paute, Sopladora, San Francisco, and Marcel Laniado de Wind. Each graph illustrates three critical metrics over the period from 2019 to 2023, as follows: the theoretical potential energy ( E t e o ) , which represents the maximum energy output each year based on water inflow and plant capacity; the actual energy generated by turbines ( E t ) ; and the surplus energy, or the energy not utilized in electricity generation. The combination of these metrics allows for a comprehensive analysis of each plant’s operational efficiency and surplus energy potential, highlighting opportunities to leverage unused energy in support of sustainable initiatives, such as green hydrogen production.
The analysis of energy production and surplus from Ecuador’s major hydroelectric plants (2019–2023) reveals valuable insights into operational efficiency and opportunities for improved energy utilization. Coca Codo Sinclair (Figure 2a) has the highest potential energy, peaking at 16,321.8 GWh, though turbine-generated energy consistently falls below this level, resulting in a surplus of 9722.2 GWh over the period. This gap indicates substantial untapped capacity, suggesting Coca Codo Sinclair could redirect surplus energy toward sustainable uses, such as hydrogen production. Paute (Figure 2b) also shows a notable difference between potential energy, peaking at 9420.3 GWh, and the actual output of 5315.5 GWh, producing a surplus of 4104.8 GWh. Paute thus emerges as another prime candidate for repurposing surplus energy. Sopladora, with potential energy around 2956.1 GWh, shows a moderate but consistent surplus of 348.3 GWh over five years, making it suitable for local-scale sustainability initiatives. San Francisco (Figure 2d) has relatively steady production with limited surplus (127.2 GWh), operating near its theoretical capacity and leaving minimal energy for additional projects. Finally, Marcel Laniado de Wind (Figure 2e) has potential energy of 1195.6 GWh, with actual output at 1052.0 GWh and a surplus of 143.6 GWh, representing a small but valuable reserve for targeted sustainability efforts.
A notable peak in surplus energy was observed in 2021 across multiple plants, attributable to unusually high rainfall that year, which increased water inflows into reservoirs. According to data from the National Energy Control Center (CENACE) [42,43,44,45,46], these exceptional conditions significantly boosted potential energy. Operational adjustments allowed for continuous turbine operation, maximizing energy capture. This peak highlights the impact of variable hydrological conditions on hydroelectric production and underscores the potential for generating surplus energy during atypical weather events. This observation further strengthens the case for adaptive management strategies to optimize energy use in response to environmental variability, supporting the repurposing of surplus energy for sustainable applications like green hydrogen production.
In light of these findings, Ecuador’s main hydroelectric plants, particularly Coca Codo Sinclair and Paute, hold significant untapped energy potential. Redirecting this surplus toward green hydrogen production or other renewable initiatives could play a pivotal role in diversifying Ecuador’s energy portfolio, advancing sustainability goals, and supporting a resilient energy infrastructure. Focusing on high-surplus plants would maximize resource utilization, positioning these facilities as key contributors to Ecuador’s energy transition and sustainable development.
Finally, Figure 3 illustrates the energy dynamics from 2019 to 2023 at Ecuador’s five main hydroelectric plants, showing both the energy generated by turbines (green bars) and the surplus energy (blue segments). This visual comparison highlights annual fluctuations in surplus energy, reflecting opportunities for enhanced resource utilization.
Figure 3 provides an overview of energy utilization at Ecuador’s main hydroelectric plants from 2019 to 2023. During this period, turbine-generated energy remained relatively stable, with a noticeable peak in 2021, likely due to favorable hydrological conditions such as above-average rainfall and increased water inflow, enabling higher operational capacity. This peak was followed by a decline in 2022 and 2023, likely reflecting a return to typical hydrological conditions or reduced water availability.
Surplus energy also varied significantly, peaking in 2021, which underscores that year’s exceptional environmental conditions. This surplus could not be fully converted to electricity, suggesting an underutilized resource. The recurring presence of surplus energy across all years highlights the potential for alternative applications, especially in high-surplus years like 2021 when surplus could have supported initiatives like green hydrogen production. This represents a missed opportunity for Ecuador to leverage surplus energy in alignment with its renewable energy goals.
The consistent surplus energy also suggests that Ecuador’s hydroelectric plants may operate below their theoretical maximum capacity due to design limitations, maintenance needs, or variability in water flow and demand. Optimizing operational factors, such as storage solutions or secondary energy conversion facilities, could capture this excess energy, especially during periods of high inflow, thereby enhancing resource utilization and reducing energy losses.

3.3. Adjustment and Projection Using the AR Model

Figure 4 illustrates the trend in surplus energy over time, based on historical data from 2019 to 2023 and projecting values up to 2030. The black data represent the actual surplus energy recorded each year, while the blue line shows the projected surplus energy using an exponential AR(1) model [59]. This projection highlights the anticipated decline in surplus energy availability over the coming years, emphasizing the potential challenges in maintaining surplus levels.
The historical data from 2019 to 2023 show variability in surplus energy levels, peaking in 2021 at 14,446.12 GWh, likely due to favorable hydrological conditions such as increased rainfall that boosted water inflows. After 2021, a downward trend is observed, with surplus energy declining to 13,292.94 GWh in 2019, 11,494.13 GWh in 2020, 9621.09 GWh in 2022, and 7620.36 GWh in 2023. This decline may reflect a combination of reduced rainfall, operational constraints, and increased demand placed on hydroelectric resources, limiting surplus generation.
Based on this context, the blue line in Figure 4, generated using the AR(1) autoregressive model, projects surplus energy availability from 2024 to 2030, assuming the downward trend continues. The model anticipates a steady decline, with surplus energy dropping below 7000 GWh by 2024 and trending toward 4000 GWh by 2030. This reduction suggests limited surplus energy for alternative uses, such as green hydrogen production or other renewable initiatives, underscoring the challenges Ecuador may face in sustaining surplus energy for its sustainability and diversification goals.
The projected decline has several important implications for Ecuador’s energy strategy. As surplus levels decrease, it becomes increasingly critical to implement strategies that maximize resource efficiency. The effective management and repurposing of surplus energy will be essential for supporting renewable projects. Additionally, Ecuador could benefit from investing in energy storage solutions, such as battery systems or pumped hydro storage, to capture and store surplus energy during peak periods, thereby mitigating fluctuations in supply.
The historical data also show that surplus energy levels fluctuate with hydrological conditions. By focusing on capturing and utilizing surplus energy during high-surplus years, Ecuador could enhance its capacity to support renewable energy projects, including green hydrogen production. However, the anticipated decline in surplus may require a strategic shift, potentially reducing reliance on hydroelectric surplus as a stable source for hydrogen production. This trend suggests that Ecuador may need to explore other renewable or alternative energy sources to sustain progress toward its sustainability and decarbonization goals.

3.4. Green Hydrogen Production from Surplus Energy Projection

The bar chart in Figure 5 projects annual hydrogen production from surplus hydroelectric energy in Ecuador from 2024 to 2030. Each bar represents the estimated hydrogen output (in tons), based on the energy consumption range for proton exchange membrane (PEM) electrolysis, as specified in Table 1. The error bars reflect this range, capturing potential variability in hydrogen production due to efficiency differences.
PEM electrolysis, which requires between 0.0500 and 0.0550 GWh per ton of hydrogen [23,61,62,63], has been selected for its efficiency and suitability for large-scale hydrogen production [61,63]. Figure 5 shows a gradual decline in hydrogen production potential, starting at over 140,000 tons in 2024 and decreasing to about 80,000 tons by 2030. This trend mirrors the anticipated reduction in surplus energy, suggesting that Ecuador may face challenges in relying solely on hydroelectric surplus for sustained hydrogen production in the future. The focus on PEM electrolysis underscores the need to maximize efficiency in the use of available surplus energy. As surplus levels decline, Ecuador may need to consider supplementary renewable sources or energy storage solutions to stabilize hydrogen output. This projection suggests that while PEM technology can support Ecuador’s short-term hydrogen goals, additional measures, such as energy diversification and storage, will be necessary to maintain consistent output and support Ecuador’s broader energy transition strategy [23,61,62,63].

4. Discussion

The results of this study provide crucial insights into the untapped potential of surplus hydropower for green hydrogen production in Ecuador, emphasizing the role hydro-energy can play in advancing sustainability. The analysis reveals that although surplus energy peaked in 2021, as a particular case, a general decline has been observed. This trend mirrors global challenges related to fluctuating water availability in hydroelectric plants, underscoring the need for improved management strategies to fully harness surplus energy resources. In this sense, the application of the AR(1) model offers a reliable projection of surplus energy availability through 2030. Widely recognized for its ability to analyze and predict time series data, this model underscores the potential of the hydroelectric infrastructure to maintain a stable surplus energy supply in the coming years, albeit with some uncertainty. The 95% confidence interval of the projections enables decision-makers to rely on these forecasts for planning investments in green hydrogen production infrastructure.
As Hunt et al. [31] note, hydroelectric facilities are particularly well-suited for hydrogen production during periods of low electricity demand, making them ideal candidates for supporting sustainable hydrogen generation. Therefore, these findings demonstrate that surplus energy from major hydroelectric plants like Coca Codo Sinclair, Paute, Sopladora, San Francisco, and Marcel Laniado de Wind presents a valuable opportunity for Ecuador to harness this renewable energy for hydrogen production, increasingly recognized as a critical component of global decarbonization efforts. In this manner, tapping into this surplus energy for hydrogen production offers a unique opportunity to position the hydroelectric resources of Ecuador as a key driver in the transition to renewable energy, particularly in sectors such as transportation, where green hydrogen could play a transformative role [19,20,54]. Furthermore, leveraging green hydrogen offers strategic advantages by supporting grid stability, as noted by Quin Yu et al. [31], allowing Ecuador to generate clean energy while also stabilizing its electricity supply.
Thus, this study is highly significant, as it demonstrates the availability of surplus energy for green hydrogen production using the existing hydroelectric infrastructure. Leveraging this pre-established network not only reduces the financial burden of building new facilities, but also accelerates the transition toward hydrogen as a sustainable fuel source. By capitalizing on its surplus hydropower, Ecuador could strategically position itself as a leader in renewable energy within Latin America, supporting both national energy independence and international decarbonization goals. This aligns with the insights of Walker [25] and Hunt et al. [31], who emphasized the economic and environmental benefits of adopting hydrogen technology.
Furthermore, as global challenges around fluctuating water availability and renewable integration continue to grow, Ecuador’s efforts to implement energy storage and management strategies, such as hydrogen production, could serve as a model for other developing countries with similar resources. A long-term strategy that includes storage solutions or complementary renewable sources could help Ecuador maximize its surplus energy in years with higher water availability, as Cheng and Jiang [41] noted in their study of the renewable sector growth supported by carbon markets.

5. Conclusions

The study investigates the potential of utilizing surplus hydroelectric energy in Ecuador for green hydrogen production, focusing on the feasibility and sustainability of this approach as part of Ecuador’s energy transition strategy. In this regard, the study identifies and discusses the following key findings:
  • Identification of high-impact hydroelectric plants through Pareto analysis, which determined that Coca Codo Sinclair, Paute, and other major plants account for the majority of Ecuador’s surplus energy. These plants represent key resources for supporting green hydrogen initiatives, given their substantial surplus capacity;
  • Projection of surplus energy availability using an AR(1) stochastic model, which indicates a gradual decline in surplus energy up to 2030. The results estimate an annual hydroelectric energy surplus in Ecuador, ranging from 7475 to 3445 GWh over the next five years, which could be allocated for green hydrogen production. This decline highlights the importance of developing adaptive management strategies and integrating complementary renewable resources to sustain hydrogen production levels over time;
  • The estimation of hydrogen production potential based on PEM electrolysis reveals a viable opportunity to convert surplus energy into green hydrogen. However, the analysis highlights challenges posed by the anticipated reduction in surplus energy, emphasizing the need for further investments in energy storage and infrastructure to maximize resource utilization.
Therefore, this study provides actionable insights for developing countries with significant hydropower resources, illustrating how green hydrogen can serve as a viable pathway for diversifying the energy mix and advancing decarbonization goals. Ecuador has the opportunity to leverage its surplus hydropower for hydrogen production, reducing reliance on fossil fuels and supporting energy resilience. By integrating surplus hydropower with hydrogen production, Ecuador could emerge as a leader in sustainable energy within Latin America, contributing to global decarbonization efforts.
Looking forward, this study suggests several avenues for further research, including assessing the technical and economic feasibility of large-scale green hydrogen production in Ecuador and exploring storage solutions to mitigate fluctuations in surplus energy. Future studies could also examine the environmental impact of expanded hydrogen production and its potential to contribute to Ecuador’s carbon neutrality. By addressing these research areas, Ecuador can build on its existing hydropower assets and strengthen its position as a regional pioneer in green hydrogen technology.

Author Contributions

Conceptualization, E.C.; methodology, E.C. and A.T.; software P.P.; validation, E.C., A.T. and S.R.; formal analysis, P.P., E.C. and A.T.; investigation, P.P., E.C. and A.T.; resources, M.Y. and P.P.; data curation, E.C. and A.T.; writing—original draft preparation, A.T. and P.P.; writing—review and editing, E.C., S.R., M.Y. and P.P.; visualization, P.P. and A.T.; supervision, E.C., A.T. and S.R.; project administration, S.R. and E.C.; funding acquisition, S.R. and E.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was developed by means of the Project Number PIGR-23-08, funded by the Escuela Politécnica Nacional.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abreviations

AR(1)First-Order Autoregressive Model
CENACECentro Nacional de Control de Energía (National Energy Control Center)
BNEBalance Energético Nacional (National Energy Balance)
EteoTheoretical energy
EsurplusSurplus energy
QiVolumetric flow rate of water available (m3/s)
EtNet energy produced by turbines (GWh)
HVertical distance between the reservoir and turbine outlets (m)
ηtr% Efficiency of turbines
ηg% Efficiency of generators
ρDensity of water (kg/m3)
gAcceleration due to gravity (m/s²)
XtSeries value at time t
ϕ1Autoregressive coefficient
ϵtRandom error term
cConstant

References

  1. Uday, S.; Arindam, B. Energy and Sustainability. In The Oxford Handbook of Environmental and Natural Resources Law in India; Oxford Academic: Oxford, UK, 2024; pp. 767–782. [Google Scholar]
  2. Knobloch, F.; Pollitt, H.; Chewpreecha, U.; Daioglou, V.; Mercure, J.-F. Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5 °C. Energy Effic. 2018, 12, 521–550. [Google Scholar] [CrossRef]
  3. Züttel, A.; Mauron, P.; Kato, S.; Callini, E.; Holzer, M.; Huang, J. Storage of Renewable Energy by Reduction of CO₂ with Hydrogen. CHIMIA 2014, 69, 264–268. [Google Scholar] [CrossRef] [PubMed]
  4. Ahmed, O.; Nha, M.; Ahmed, E.; Mahmoud, H.; Amer, A.-H. Hydrogen production, storage, utilization, and environmental impacts: A review. Environ. Chem. Lett. 2022, 20, 153–188. [Google Scholar]
  5. Martino, M.; Ruocco, C.; Meloni, E.; Pullumbi, P.; Palma, V. Main Hydrogen Production Processes: An Overview. Catalysts 2021, 11, 50547. [Google Scholar] [CrossRef]
  6. Sharma, M.; Tyagi, V.V.; Kouser, R.; Kumari, K.; Chopra, K.; Kothari, R. Green Hydrogen and Climatic Change: Current Status and Future Outlook. Green Hydrog. Econ. Environ. Sustain. 2024, 2, 31–54. [Google Scholar]
  7. Li, Z.; Huang, Z.; Su, Y. New media environment, environmental regulation and corporate green technology innovation: Evidence from China. Energy Econ. 2023, 119, 106545. [Google Scholar] [CrossRef]
  8. Yilmaz, F. Design and performance analysis of hydro and wind-based power and hydrogen generation system for sustainable development. Sustain. Energy Technol. Assess. 2024, 64, 103742. [Google Scholar] [CrossRef]
  9. Rabiee, A.; Keane, A.; Soroudi, A. Green hydrogen: A new flexibility source for security constrained scheduling of power systems with renewable energies. Int. J. Hydrogen Energy 2021, 46, 37. [Google Scholar] [CrossRef]
  10. Zalamea, J. Despacho Hidrotérmico de Mediano Plazo aplicado al Complejo Hidroeléctrico Paute Integral. Energía 2021, 18, 95–105. [Google Scholar] [CrossRef]
  11. Simoes, F.; Santos, D.M. A SWOT Analysis of the Green Hydrogen Market. Energies 2024, 17, 3114. [Google Scholar] [CrossRef]
  12. Ingale, G.U.; Kwon, H.-M.; Jeong, S.; Park, D.; Kim, W.; Bang, B.; Lim, Y.-I.; Kim, S.W.; Kang, Y.-B.; Mun, J.; et al. Assessment of Greenhouse Gas Emissions from Hydrogen Production Processes: Turquoise Hydrogen vs. Steam Methane Reforming. Energies 2022, 15, 8679. [Google Scholar] [CrossRef]
  13. Ministerio de Energía y Minas. Hoja de Ruta del Hidrógeno Verde en Ecuador; La Incre S.A.: Quito, Ecuador, 2023. [Google Scholar]
  14. Stoica, D.; Mihaescu, L.; Lazaroiu, G. Green Hydrogen, a Solution for Replacing Fossil Fuels to Reduce CO₂ Emissions. Processes 2024, 12, 1651. [Google Scholar] [CrossRef]
  15. Karayel, G.K.; Dincer, I. A study on green hydrogen production potential of Canada with onshore and offshore wind power. J. Clean. Prod. 2024, 437, 1501. [Google Scholar] [CrossRef]
  16. Yu, Q.; Dai, S.; Shen, P.; Deng, W. Hydrogen Energy in Electrical Power Systems: A Review and Future Outlook. Electronics 2024, 13, 3370. [Google Scholar] [CrossRef]
  17. Wenchao, C.; Xin, D.; Chen, R.; Zhang, J.Z.Y.; Fu, H. Thermodynamic destabilization and kinetic optimization for the de-/hydrogenation of Mg85Ni15 alloy by tailoring Mg(In) and Mg2Ni(In) double solid solution. Int. J. Hydrogen Energy 2023, 960, 170551. [Google Scholar]
  18. Hosseini, S.E.; Abdul Wahid, M. Hydrogen production from renewable and sustainable energy resources: Promising green energy carrier for clean development. Renew. Sustain. Energy Rev. 2016, 57, 850–866. [Google Scholar] [CrossRef]
  19. Ansoleaga Villegas, I. El Mercado del Hidrógeno en Noruega; ICEX España Exportación e Inversiones: Oslo, España, 2022. [Google Scholar]
  20. Tholen, L.; Leipprand, A.; Kiyar, D.; Maier, S.; Küper, M.; Adisorn, T.; Fischer, A. The Green Hydrogen Puzzle: Towards a German Policy Framework for Industry. Sustainability 2021, 13, 12626. [Google Scholar] [CrossRef]
  21. Valdez Ibarra, J.J.; De la Salinas, L.R.; García Cedeño, J.A.; Maldonado Ibarra, G.E. Transporte de Hidrógeno: Energía limpia para Latinoamérica. Reincisol 2024, 3, 953–971. [Google Scholar] [CrossRef]
  22. Abbas, M.; Hassan, Q.; Sohrabi, V.; Tohidi, S.; Jaszczur, M.; Abdulrahman, I.S.; Salman, H. Techno-Economic Analysis for Clean Hydrogen Production Using Solar Energy Under Varied Climate Conditions. Int. J. Hydrogen Energy 2023, 48, 2929–2948. [Google Scholar] [CrossRef]
  23. Denk, K.; Kodým, R.; Hnát, J.; Paidar, M.; Zitka, J.; Bouzek, K. Alkaline Water Electrolysis—Investigation of the Charge Transport Limitations Across the Separator Under Low KOH Concentration. ECS Meet. Abstr. 2023, MA2023-01, 1750. [Google Scholar] [CrossRef]
  24. Shokrollahi, M.; Teymouri, N.; Ashrafi, O.; Navarri, P.; Khojasteh-Salkuyeh, Y. Methane Pyrolysis as a Potential Game Changer for Hydrogen Economy: Techno-Economic Assessment and GHG Emissions. Int. J. Hydrogen Energy 2024, 66, 337–353. [Google Scholar] [CrossRef]
  25. Walker, G. Hydrogen Storage Technologies; Woodhead Publishing Series in Electronic and Optical Materials; Woodhead Publishing: Sutton, UK, 2008; pp. 3–17. [Google Scholar]
  26. Liu, Q.; Hong, H.Y.J.; Jin, H.; Cai, R. Experimental Investigation of Hydrogen Production Integrated with Methanol Steam Reforming and Middle-Temperature Solar Thermal Energy. Appl. Energy 2009, 155, 155–162. [Google Scholar] [CrossRef]
  27. Baykara, S.Z. Hydrogen Production by Direct Solar Thermal Decomposition of Water, Possibilities for Improvement of Process Efficiency. Int. J. Hydrogen Energy 2004, 29, 1451–1458. [Google Scholar] [CrossRef]
  28. Olateju, B.; Kumar, A. Hydrogen Production from Wind Energy in Western Canada for Upgrading Bitumen from Oil Sands. Energy 2011, 36, 6326–6339. [Google Scholar] [CrossRef]
  29. Zamfirescu, C.; Dincer, I.; Stern, M.; Wagar, W. Exergetic, Environmental and Economic Analyses of Small-Capacity Concentrated Solar-Driven Heat Engines for Power and Heat Cogeneration. Int. J. Energy Res. 2011, 35, 397–408. [Google Scholar] [CrossRef]
  30. Alizadeh, S.; Parhizi, Z.; Alibak, A.; Vaferi, B.; Hosseini, S. Predicting the Hydrogen Uptake Ability of a Wide Range of Zeolites Utilizing Supervised Machine Learning Methods. Int. J. Hydrogen Energy 2022, 47, 21782–21793. [Google Scholar] [CrossRef]
  31. Hunt, J.D.; Lima, G.M.; Belchior, F.N.; Villena, J.E.N.; Domingos, J.L.; Freitas, M.A.V. Hybrid electrical energy generation from hydropower, solar photovoltaic and hydrogen. Int. J. Hydrogen Energy 2024, 53, 602–612. [Google Scholar]
  32. Han, J.; Wang, J.; He, Z.; An, Q.; Song, Y.; Mujeeb, A.; Tan, C.-W.; Gao, F. Hydrogen-powered smart grid resilience. Energy Convers. Econ. 2023, 4, 89–104. [Google Scholar] [CrossRef]
  33. Naqvi, S.; Tariq, R.; Hameed, Z.; Ali, I.; Taqvi, S.; Naqvi, M.; Niazi, M.; Noor, T.; Farooq, W. Pyrolysis of High-Ash Sewage Sludge: Thermo-Kinetic Study Using TGA and Artificial Neural Networks. Fuel 2018, 222, 529–538. [Google Scholar] [CrossRef]
  34. Cook, B.; Hagen, C. Techno-Economic Analysis of Biomass Gasification for Hydrogen Production in Three US-Based Case Studies. Int. J. Hydrogen Energy 2024, 49, 202–218. [Google Scholar] [CrossRef]
  35. Nouwe, E.; Onwudili, J. Comparative Techno-Economic Modelling of Large-Scale Thermochemical Biohydrogen Production Technologies to Fuel Public Buses: A Case Study of West Midlands Region of England. Renew. Energy 2022, 177, 704–716. [Google Scholar] [CrossRef]
  36. Hardana, H.; Adiwibowo, P.; Sunitiyoso, Y.; Kurniawan, T. Financial Viability Analysis for Green Hydrogen Production Opportunity from Hydropower Plant’s Excess Power in Indonesia. Int. J. Renew. Energy Dev. 2024, 13, 846–863. [Google Scholar] [CrossRef]
  37. Reksten, A.; Thomassen, M.; Moller-Holst, S.; Sundseth, K. Projecting the Future Cost of PEM and Alkaline Water Electrolysers; A CAPEX Model Including Electrolyser Plant Size and Technology Development. Int. J. Hydrogen Energy 2022, 47, 38106–38113. [Google Scholar] [CrossRef]
  38. Zwickl-Bernhard, S.; Auer, H. Green Hydrogen from Hydropower: A Non-Cooperative Modeling Approach Assessing the Profitability Gap and Future Business Cases. Energy Strategy Rev. 2022, 39, 100912. [Google Scholar] [CrossRef]
  39. Abdin, Z. Bridging the Energy Future: The Role and Potential of Hydrogen Co-Firing with Natural Gas. J. Clean. Prod. 2024, 140, 140724. [Google Scholar] [CrossRef]
  40. Idowu, A.; Ohikhuare, O.M.; Chowdhury, M.A. Does Industrialization Trigger Carbon Emissions Through Energy Consumption? Evidence from OPEC Countries and High Industrialised Countries. Quant. Financ. Econ. 2023, 7, 165–186. [Google Scholar] [CrossRef]
  41. Cheng, J.; Jiang, Y. How Can Carbon Markets Drive the Development of Renewable Energy Sector? Empirical Evidence from China. Data Sci. Financ. Econ. 2024, 4, 249–269. [Google Scholar] [CrossRef]
  42. Cenace. Operador Nacional de Electricidad. Informe Anual Producción Energética 2019; Cenace: Quito, Ecuador, 2020. [Google Scholar]
  43. Cenace. Operador Nacional de Electricidad. Informe Anual Producción Energética 2020; Cenace: Quito, Ecuador, 2021. [Google Scholar]
  44. Cenace. Operador Nacional de Electricidad. Informe Anual Producción Energética 2021; Cenace: Quito, Ecuador, 2022. [Google Scholar]
  45. Cenace. Operador Nacional de Electricidad. Informe Anual Producción Energética 2022; Cenace: Quito, Ecuador, 2023. [Google Scholar]
  46. Cenace. Operador Nacional de Electricidad. Informe Anual Producción Energética 2023; Cenace: Quito, Ecuador, 2024. [Google Scholar]
  47. Ministerio de Energía y Minas. Balance Energético Nacional 2019; Ministerio de Energía y Minas: Quito, Ecuador, 2020. [Google Scholar]
  48. Ministerio de Energía y Minas. Balance Energético Nacional 2023; Ministerio de Energía y Minas: Quito, Ecuador, 2024. [Google Scholar]
  49. Newman, M.E.J. Power Laws, Pareto Distributions and Zipf’s Law. Contemp. Phys. 2005, 46, 323–351. [Google Scholar] [CrossRef]
  50. Juran, J.M. Juran on Quality by Design: The New Steps for Planning Quality into Goods and Services; The Free Press: New York, NY, USA, 1992. [Google Scholar]
  51. Samuelson, P.A.; Nordhaus, W.D. Economics; McGraw-Hill: New York, NY, USA, 2009. [Google Scholar]
  52. Porter, M.E. Competitive Advantage: Creating and Sustaining Superior Performance; Free Press: New York, NY, USA, 1985. [Google Scholar]
  53. Cobaner, M.; Haktanir, T.; Kisi, O. Prediction of Hydropower Energy Using ANN for the Feasibility of Hydropower Plant Installation to an Existing Irrigation Dam. Water Resour. Manag. 2008, 22, 757–774. [Google Scholar] [CrossRef]
  54. Susilowati, Y.; Irasari, P.; Susatyo, A. Study of Hydroelectric Power Plant Potential of Mahakam River Basin East Kalimantan Indonesia. In Proceedings of the 2019 International Conference on Sustainable Energy Engineering and Application (ICSEEA), Tangerang, Indonesia, 23–24 October 2019. [Google Scholar]
  55. Dimas, M.; Etanto, K.; Wijayanto, H.; Pranoto, S.; Hermawan, I.; Idris, M. Analysis of the effect of high falling water on the performance of hydroelectric power plants using whirpool type turbines. JTTM 2024, 5, 149–157. [Google Scholar]
  56. Khayal, O.M.E.S. Review and Technical Study of Hydroelectric Power Generation. In ResearchGate Preprints; Nile Valley University: Atbara, Sudan, 2019. [Google Scholar] [CrossRef]
  57. Barragán Escandón, A.; Arostegui Gutiérrez, S.; Zalamea León, E.; Serrano Guerrero, X. Green Hydrogen from Hydroelectric Energy: Assessing the Potential at the Abanico Power Plant in Morona Santiago Province. Renew. Energy Power Qual. J. 2024, 22, 1. [Google Scholar] [CrossRef] [PubMed]
  58. Viola, L.; De Queiróz Lamas, W.; Silveira, J.L. Environmental studies of green hydrogen production by electrolytic process: A comparison of the use of electricity from solar PV, wind energy, and hydroelectric plants. Int. J. Hydrogen Energy 2023, 48, 36584–36604. [Google Scholar]
  59. Jafarova, H.; Aliyev, R. Applications of Autoregressive Process for Forecasting of Some Stock Indexes. In Studies in Fuzziness and Soft Computing; Springer: Cham, Switzerland, 2022; pp. 271–278. [Google Scholar]
  60. Takalo, R.; Hytti, H.; Ihalainen, H. Tutorial on Univariate Autoregressive Spectral Analysis. J. Clin. Monit. Comput. 2005, 19, 6. [Google Scholar] [CrossRef] [PubMed]
  61. Krone, T.; Albers, C.J.; Timmerman, M. A comparative simulation study of AR(1) estimators in short time series. Qual. Quant. 2016, 51, 1–21. [Google Scholar] [CrossRef] [PubMed]
  62. Campbell-Stanway, C.; Becerra, V.; Pranbhu, S.; Bull, J. Investigating the Role of Byproduct Oxygen in UK-Based Future Scenario Models for Green Hydrogen Electrolysis. Energies 2024, 17, 281. [Google Scholar] [CrossRef]
  63. Carmo, M.; Fritz, D.; Mergel, J.; Stolten, D. A Comprehensive Review on PEM Water Electrolysis. Int. J. Hydrogen Energy 2013, 38, 4901–4934. [Google Scholar] [CrossRef]
Figure 1. Pareto chart of energy generation by the main hydroelectric plants of Ecuador during 2022 (GWh).
Figure 1. Pareto chart of energy generation by the main hydroelectric plants of Ecuador during 2022 (GWh).
Energies 17 06051 g001
Figure 2. Annual energy production and surplus analysis (2019–2023) for major hydroelectric plants in Ecuador: (a) Coca Codo Sinclair, (b) Paute, (c) Sopladora, (d) San Francisco, and (e) Marcel Laniado de Wind.
Figure 2. Annual energy production and surplus analysis (2019–2023) for major hydroelectric plants in Ecuador: (a) Coca Codo Sinclair, (b) Paute, (c) Sopladora, (d) San Francisco, and (e) Marcel Laniado de Wind.
Energies 17 06051 g002
Figure 3. Summary of turbine-generated and surplus energy (2019–2023) for major hydroelectric plants in Ecuador: Coca Codo Sinclair, Paute, Sopladora, San Francisco, and Marcel Laniado de Wind.
Figure 3. Summary of turbine-generated and surplus energy (2019–2023) for major hydroelectric plants in Ecuador: Coca Codo Sinclair, Paute, Sopladora, San Francisco, and Marcel Laniado de Wind.
Energies 17 06051 g003
Figure 4. Surplus energy projection (GWh) using the AR(1) model (2019–2030) at 95% confidence interval.
Figure 4. Surplus energy projection (GWh) using the AR(1) model (2019–2030) at 95% confidence interval.
Energies 17 06051 g004
Figure 5. Projected green hydrogen production from surplus hydroelectric energy in Ecuador (2024–2030).
Figure 5. Projected green hydrogen production from surplus hydroelectric energy in Ecuador (2024–2030).
Energies 17 06051 g005
Table 1. Energy consumption of methods for green hydrogen production.
Table 1. Energy consumption of methods for green hydrogen production.
MethodsEnergy Consumption 1 (GWh/ton)
Proton exchange membrane (PEM) electrolysis0.0500–0.055
Alkaline electrolysis0.0550–0.060
Solid Oxide Electrolysis (SOEC)0.0400–0.050
1 References: [23,62,63].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Pinchao, P.; Torres, A.; Yánez, M.; Reina, S.; Cando, E. Analysis for the Implementation of Surplus Hydropower for Green Hydrogen Production in Ecuador. Energies 2024, 17, 6051. https://doi.org/10.3390/en17236051

AMA Style

Pinchao P, Torres A, Yánez M, Reina S, Cando E. Analysis for the Implementation of Surplus Hydropower for Green Hydrogen Production in Ecuador. Energies. 2024; 17(23):6051. https://doi.org/10.3390/en17236051

Chicago/Turabian Style

Pinchao, Paul, Alejandra Torres, Marco Yánez, Salvatore Reina, and Edgar Cando. 2024. "Analysis for the Implementation of Surplus Hydropower for Green Hydrogen Production in Ecuador" Energies 17, no. 23: 6051. https://doi.org/10.3390/en17236051

APA Style

Pinchao, P., Torres, A., Yánez, M., Reina, S., & Cando, E. (2024). Analysis for the Implementation of Surplus Hydropower for Green Hydrogen Production in Ecuador. Energies, 17(23), 6051. https://doi.org/10.3390/en17236051

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop