Analysis of the Availability Curve of the 15 kW Wind–Solar Hybrid Microplant Associated with the Demand of the Power-to-Gas (PtG) Pilot Plant Located at University of La Guajira

Abstract

This article presents a detailed analysis of the energy availability of a 15 kW hybrid wind–solar photovoltaic microplant, designed to supply the electricity demand of the power-to-gas (PtG) pilot plant located at the University of La Guajira, Colombia. The study addresses the lack of specific data on the energy availability curve, which is essential for quantifying the production percentages of green hydrogen from wind and solar photovoltaic sources. To this end, continuous data were collected over a seven-month period, recording the daily power output from both sources. Additionally, the energy requirements of the PtG pilot plant, which relies on the microplant for its electrical supply, were determined. The results indicated that during certain periods, such as specific days in November 2022 and February and March 2023, it was necessary to rely on the conventional electrical grid for backup. Moreover, it was observed that solar photovoltaic energy contributed the most electricity to the system for green hydrogen production. In the study area, although green hydrogen production is predominantly supported by the solar photovoltaic source, it is crucial to have the backup of an additional source, such as wind, due to the intermittent nature of the climatic conditions affecting these technologies.

1. Introduction

All societies require energy services to supply basic human needs, such as lighting, comfort, climate control, mobility, and communication, and to support productive processes. For sustainable development, these energy services must be safe and have a low environmental impact. Sustainable social and economic development aims to provide secure and affordable access to the resources necessary for energy generation, targeting both basic and sustainable needs. Achieving this requires different strategies across the various stages of economic development.

Alternative energy sources are identified as clean, inexhaustible, and increasingly competitive. These sources differ from conventional fossil fuel-based energies mainly in their diversity, abundance, and potential for utilization anywhere on the planet. Most importantly, they do not generate greenhouse gases (GHGs), which are a major cause of climate change, or other polluting emissions. Furthermore, the costs of alternative energies are consistently decreasing, unlike conventional energy sources, which generally experience increasing trends in fossil fuel costs despite temporary fluctuations. The growth in alternative energy is significant, as evidenced by statistics from the International Energy Agency (IEA), which forecasts: “The share of renewable energies in global electricity supply will transition from 26% in 2018 to 44% in 2040 and could provide two-thirds of the increase in electricity demand recorded during this period, mainly through the use of alternative energies such as solar and wind systems” [1].

Renewable energy generation, which is obtained through the use of renewable resources, focuses primarily on wind and solar energy. Wind energy is produced by capturing wind through turbines, converting kinetic energy into electrical energy. In contrast, solar energy is harnessed through solar panels that convert solar radiation into electricity [2,3].

Hybrid systems integrate two or more energy generators, typically used off the electrical grid depending on the consumption conditions and requirements. A conventional diesel generator is often combined with a renewable energy source, such as solar, wind, or even a combination of both. While the initial costs of solar or wind energy systems are higher compared to diesel generators, the maintenance and operational costs are significantly lower for renewable systems. Hybrid systems must supply criteria of modularity, robustness, and simplicity and require low maintenance. These systems combine alternative energy sources with batteries for energy storage and power conditioning equipment to maintain power quality. A key condition for the use of hybrid systems is that the existing conditions in the planned installation locations must be utilized [4,5,6,7]. The most common configuration for these systems, given the increasing priority on obtaining electricity without greenhouse gas emissions, is to use the consumer’s own energy source(s) as much as possible, with the remaining demand met by the electrical grid, thereby reducing grid reliance.

The research draws on previous studies that explore the same research area as this project, along with terms related to the problem statement.

According to [7], a study was conducted on energy transfer between renewable energy hybrid systems and the electrical grid to supply power demand. The system was analyzed to supply two types of demand, a home and a small industry, using small-scale renewable systems located near the user and connected to the electrical grid. Each system was modeled and simulated, including both solar and wind resources and the small-scale photovoltaic system and wind turbine, as well as the demands, factoring in effects not previously considered in the literature. A simulation platform was developed for each element, allowing for better resource utilization and grid dependence analysis across different configurations, based on the relationship between demands and renewable resources. This also facilitated the analysis of resource availability. The evaluation criteria were energy transfer with the grid and the grid’s contribution to demand (buy–sell), along with the corresponding expenses and associated losses.

The study by [8] described the simulation of a proposed solar–wind hybrid system on the island of San Andrés with a predictive controller to enhance the system’s efficiency. One of the challenges in implementing renewable energies is their intermittency and the difficulty of estimating delivered power. Therefore, a simulation of the system was conducted based on a model obtained through fundamental equations describing the system’s behavior. The energy potential of the area was characterized so that the simulated energy output reflected the conditions of San Andrés. Commercial devices were considered, and each stage of electricity production was simulated, from aerodynamic and radiation transformation to electrical energy to reactive and active power according to a known demand. Two scenarios were simulated: with and without the predictive controller. The results provided an important starting point for implementing the system and replicating it in other areas of Colombia where needed.

In the work by [9], a hybrid generation system combining solar and wind energy was proposed for isolated areas where access to the electrical distribution grid was difficult. The microgrid consisted of a wind turbine, four photovoltaic panels, two batteries, and their respective control elements, providing users with a daily consumption of 1468 Wh. Additionally, the microgrid monitored climatic and electrical variables involved in the generation process, creating a database that could be visualized through a graphical interface developed in LabView.

The research by [10] developed a methodology for conducting a technical-economic analysis of a low-power generation system using renewable energy resources connected to the electrical grid. The first step was determining the energy demand. For this work, a case study was chosen involving a user who wanted to implement renewable energy sources as a means of energy supply. After calculating the energy demand, a steady-state analysis was performed to evaluate the available energy potential in the area. Using meteorological data on solar radiation and wind speed, system components were selected, and calculations for sizing the wiring and electrical protections of the system were carried out.

Energy availability is crucial for performing any daily activity (as it must be known whether electrical energy is available to do something; otherwise, it cannot be done). This is even more critical in industrial settings, where electrical energy is essential for any process. Therefore, a rigorous study of energy availability is necessary, especially when using renewable resources, which are often inconsistent or erratic and require extensive monitoring and constant data collection to optimally supply the required demand for various actions or processes. If the renewable system cannot guarantee the energy capacity, the conventional electrical grid can be used. Without monitoring the energy availability of these renewable systems, which are unpredictable, they may not supply the energy demand required for different processes, affecting outcomes and potentially causing equipment lifespan reductions and accidents.

Given the above, the purpose of this article was to create an availability curve for a 15 kW wind–solar microplant relative to the demand of a power-to-gas pilot plant. This was to determine when the pilot plant could operate for green hydrogen production without interruption and without relying on the university’s electrical grid backup.

2. Methodology

The methodological approach of this research was structured into five stages. The first stage involved recognizing the equipment present in the PtG pilot plant, powered by the 15 kW hybrid wind–solar microplant. This recognition was crucial to understanding the energy sources within the system. The second stage focused on collecting output power data from this microplant over a period of seven (7) months. The collected data were used to analyze energy production patterns and assess the reliability of the hybrid system. In the third stage, the theoretical power of the photovoltaic solar system was calculated, considering the connection restrictions to the university’s electrical grid. This calculation helped determine the theoretical power of this system. The fourth stage centered on the energy balance of the PtG pilot plant components powered by the hybrid wind–solar microplant. In this stage, the hybrid system’s ability to supply the energy demands of the plant was evaluated using the data and calculations from the previous stages. Finally, in the fifth stage, the availability curve of the system was developed for the mentioned period, identifying the days when the hybrid microplant could supply the energy demands of the PtG pilot plant, thereby determining the system’s reliability and the need for backup energy. These stages are interconnected as shown in Figure 1.

2.1. Equipment Recognition

The pilot plant is structured into distinct subsystems: one for production of electrical energy from renewable sources, another dedicated to electrolysis for hydrogen production, and a third for hydrogen utilization as an energy resource. Electrical energy is harnessed through a 15 kW wind–solar microplant, comprising a wind system that includes an Aeolos-H 5 kW wind turbine connected to the university grid via an independent inverter [11,12]. The specifications of the wind turbine are detailed in

Table A1. Aeolos-H 5 kW wind turbine technical specifications.

Specification	Concept
Nominal power	5 kW
Maximum power	6.5 kW
Efficiency	95%
Startup speed	2.5 m/s
Cut-in speed	11 m/s
Survival speed	59.5 m/s
Lifespan	20 years
Rotor speed	240 RPM
Tower height	18 m
Rotor diameter	5.6 m
Swept area	24.6 m2

, and a photograph of the installed equipment is shown in Figure A1.

The microplant also incorporates a photovoltaic solar energy system, consisting of 34 polycrystalline photovoltaic panels. Of these, 26 are connected to the electrical grid through microinverters, while the remaining 8 are connected to two batteries via an inverter-charger. Detailed technical specifications of the photovoltaic panels are provided in

Table A2. Technical specifications of the photovoltaic solar panel ZXP6-LD72-330/p.

Specification	Concept
Nominal Power	330 Wp
Efficiency	16.82%
Operating voltage	37.6 V
Maximum power current	8.91 A
Operating temperature	∼40 °C to +85 °C
Module dimensions (height × width × depth)	1978 mm × 992 mm × 30 mm
Weight	25.5 kg

, and an aerial view illustrating the layout of these panels is shown in Figure A2 [11,12].

It is important to note that the photovoltaic solar system of the hybrid microplant is currently subject to restrictions regarding connection to the energy operator, as it is in the process of being legalized. Consequently, the system is currently only generating the demand required by the PtG pilot plant.

The configuration of the microplant, combining photovoltaic solar and wind energy systems, is justified by the enhanced reliability it offers in electricity generation. This combination addresses the inherent reliability issues associated with wind and solar energy, which are affected by the intermittency due to variable weather conditions. Integrating both energy sources significantly helps to mitigate challenges related to energy supply compared to relying on a single renewable energy source.

In the PtG pilot plant, the main components are two AEM electrolyzers from the ENAPTER brand, originating from Italy, used for green hydrogen production. These devices employ the process of electrolysis to generate on-site hydrogen using excess electrical energy from the hybrid microplant, along with water supplied within the plant’s premises. The water undergoes a purification process to ensure the quality of the electrolyzers and to prevent damage to the membranes, through an auxiliary system integrated into the equipment. The two electrolyzers produce 0.5 Nm³/h each at a power of 2400 W and a pressure of 35 bar. The details of the technical specifications can be found in

Table A3. Technical specifications of the Enapter EL 2.1 electrolyzer.

Specification	Concept
Hydrogen production capacity	0.5 Nm3/h (500 NL/h) per electrolyzer
Hydrogen purity	At 35 bar: ∼99.90% (impurities: ∼1000 ppm H2O) At 8 bar: >1500 ppm H2O
Outlet pressure	Up to a maximum of 35 barg
Nominal power	2400 W
Electrical power consumption in “Stand-By”	15 W
Power supply	200–240 Vac, 50/60 Hz
Operating ambient temperature range	5 °C to 45 °C
Operating ambient humidity range	Up to 95% humidity, non-condensing
Water consumption	∼400 mL/h
Water inlet pressure range	1–4 barg
Module dimensions (W× D × H)	482 mm × 634 mm × 307 mm
Weight	55 kg

, and Figure A3 depicts the arrangement and installation of the electrolyzers along with their auxiliary systems [11,12].

The microplant also includes essential auxiliary components, such as inverters and a battery bank. The electrical energy generated by the wind turbine is integrated into the grid via an inverter from Aeolos, ensuring efficient integration. For further details, please refer to our previous work [11,12].

It is important to clarify that the 15 kW hybrid wind–solar photovoltaic microplant and other components of the PtG pilot plant were sized considering the requirements and costs of these systems, which are part of a larger project funded by the Ministry of Science and Technology (Minciencias) in Colombia.

2.2. Data Collection

The data collection for the 15 kW wind–solar photovoltaic hybrid microplant was conducted daily over a period of seven (7) months, considering the energy and power generated by both systems. Wind energy data were manually recorded on weekdays (Monday to Friday) using the wind turbine inverter display, as weekends are non-working days at the university. Since the photovoltaic solar system was not yet integrated with the university’s electrical grid operator, the power output was calculated using algebraic equations available in the literature. Furthermore, due to the university’s inactivity on Saturdays and Sundays, the power data for the wind system on these days were also estimated using algebraic equations.

2.3. Calculation of the Theoretical Power of the Photovoltaic Solar System

Due to the restriction on injecting energy into the university’s electrical grid, as the photovoltaic solar system was not legalized with the energy operator at the time, the power of the panels was calculated using algebraic equations available in the literature. These equations were essential for simulating the daily power of the photovoltaic solar system of the microplant. The equations used are presented below [11,12]:

$$P_{PV}=N_{PV}{\eta }_{inv}{P}_{PV,rated}{\displaystyle \frac{G}{G_{ref}}}\left[\left(1+{\alpha }_T\left(T_c-T_{ref}\right)\right)\right]$$

(1)

where $P_{PV}$ is the total power of the photovoltaic solar system (W), $N_{PV}$ is the number of solar panels, ${\eta }_{inv}$ is the inverter efficiency, $P_{PV,rated}$ is the nominal power of a solar panel (Wp), G is the solar radiation of the day (W/m²), $G_{ref}$ is the solar radiation under reference conditions (1000 W/m²), ${\alpha }_T$ is the temperature coefficient (−3.7 × 10⁻³ 1/°C), $T_{ref}$ is the temperature under reference conditions (25 °C), and $T_c$ is the cell temperature (°C), which is calculated using the following equation:

$$T_c=T_{amb}+(0.0256·G)$$

(2)

where $T_{amb}$ is the average ambient temperature of the day (°C).

The power of the wind turbine was manually recorded using the inverter display. However, it was necessary to calculate the theoretical power of the wind system, as it was not possible to access the pilot plant to perform this measurement during non-working days at the university. In light of this, the algebraic equation used to calculate the theoretical power of the wind turbine is presented below [11,12]:

$$P_{WT}={\displaystyle \frac{1}{2}}{\rho }_{air}{C}_{p}A{V}^3{\eta }_m{\eta }_g{\eta }_{aux}$$

(3)

where $P_{WT}$ is the total power of the wind system (W); ${\rho }_{air}$ is the air density at a given temperature (kg/m³); $C_p$ is the efficiency of the wind turbine, which depends on the wind speed and will not exceed 0.59 due to the Betz limit; A is the swept area of the wind turbine (m²); V is the wind speed (m/s); and ${\eta }_m$, ${\eta }_g$, and ${\eta }_{aux}$ are the efficiencies of the gearbox, generator, and auxiliary systems, respectively, of the wind turbine.

The variables V, $T_{amb}$, and G were obtained through the databases of the Information System for Hydrology and Meteorology Data Management (DHIME) of the Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM) [13], which has records from multiple terrestrial weather stations throughout the Colombian territory. However, due to limitations of this database in the availability of information for certain days and months, the satellite database from the Data Access Viewer of the National Aeronautics and Space Administration (NASA) was used as an alternative [14]. This way, the theoretical power of the wind and solar system was calculated on days when the actual power of the system could not be obtained in situ.

2.4. Energy Balance

The energy balance specifies the load of the components present in the PtG pilot plant, where the wind–solar hybrid microplant supplies the energy demand.

Table 1. Energy balance of the consumption elements associated with the PtG pilot plant.

Equipment	Quantity	Power (W)	Hours of Use (h)	Total Energy (Wh/Day)
Electrolyzers	2	4800	12	115,560
Purification system	1	80	12	960
Water storage tank	1	35	12	456
LED lamps	6	240	12	17,280
Total		5155		123,456
Conversion		5.155 kW		123.456 kWh

details these components:

2.5. Availability Curve

After consolidating and constructing the database on the availability of the hybrid system, the development of a demand curve for the pilot plant proceeded. For this analysis, probability analysis and descriptive statistics were used as the main tools to assess the variability and reliability of the output power generation from both the wind and photovoltaic solar systems. Through this methodology, key statistical measures such as mean, standard deviation, and percentiles were calculated, enabling the characterization of the temporal distribution of energy generation and its ability to supply the plant’s demand.

Additionally, a probability analysis was applied to determine the likelihood that the hybrid system could supply the required load under different operating conditions. These results not only facilitated real-time monitoring of the system’s availability but also helped identify moments when it was necessary to rely on the electrical grid backup to ensure a continuous and stable energy supply. This statistical approach was essential for optimizing the operation of the hybrid system and maximizing its efficiency within the context of the pilot plant.

3. Analysis and Discussion

In this section, the main results of the study conducted over a seven-month period, based on data generated by the wind–solar microplant, are presented. The analysis focused on evaluating the individual performance of the solar and wind systems, as well as their combined behavior in a hybrid configuration, with the aim of determining their ability to supply the power requirements of the power-to-gas (PtG) pilot plant.

The collected data allowed for the observation of the solar and wind system performance separately. Figure 2 illustrates the behavior of each system to determine which one was better suited to supply the demand of the PtG plant components between the last quarter of 2022 and the first quarter of 2023, as detailed in Table 1. The results indicated that the photovoltaic solar system could nearly fully cover the demand of the pilot plant, requiring only a minimal amount of energy from the university’s electrical grid to supplement the energy needs. The high efficiency of the photovoltaic solar system was attributed to its greater peak power capacity compared to the wind system.

This differentiated behavior between the two systems could be explained by the variability in the availability of natural resources: while solar generation is more constant and predictable, wind generation relies on more volatile factors, such as wind speed and consistency.

In the analysis of each system individually, it was observed that certain climatic variables affected their output power. For instance, in Figure 3, it is evident that an increase in solar radiation led to a higher output power from the photovoltaic solar system, demonstrating a direct relationship between these two variables, as shown in Equation (1). However, other variables depended on the specific climatic conditions of the location and could negatively influence the output power of the panels. This was the case with ambient temperature, as illustrated in Figure 4: as the temperature increased, the output power of the photovoltaic solar system decreased. This occurred because solar panels were tested under standard conditions of 1000 W/m² and an ambient temperature of 25 °C [15,16]. In La Guajira, Colombia, where this study was conducted, these variables tended to have significantly higher averages, especially ambient temperature, which reduced the efficiency of the photovoltaic solar panels, consequently lowering their output power significantly. Another factor affecting panel performance was wind speed. As shown in Figure 5, at low wind speeds, the system’s output power behaved similarly, while at higher speeds, the increase in output power was minimal.

On the other hand, when analyzing the variables that directly affected the output power of the wind energy system, it can be observed in Figure 6 that wind speed was directly proportional to the output power; that is, the higher the wind speed, the greater the power output. However, this behavior was not always consistent because air density also affected power output, as shown in Figure 7. When comparing the output power with ambient temperature, we observed an inversely proportional relationship: as temperature increased, the wind system’s power output decreased. This occurred because air density is influenced by ambient temperature, decreasing as temperature rises, which can be explained by the ideal gas law.

When analyzing the solar and wind systems in a hybrid configuration, as illustrated in Figure 8, it was evident that this combination could fully supply the demand of the power-to-gas (PtG) pilot plant components. The hybrid configuration maximized the utilization of available resources, resulting in optimized energy generation.

In this configuration, the solar photovoltaic system remained the primary contributor due to its higher generation capacity and greater stability compared to the wind system. However, the wind system played a crucial role in supplementing generation when solar production was insufficient. This complementarity significantly reduced the plant’s dependence on the university’s electrical grid, thereby ensuring greater autonomy and operational efficiency.

Figure 8 illustrates that the need to use electric power backup from the university’s electrical grid was minimal in this hybrid configuration. In fact, not only was reliance on the grid reduced, but energy surpluses were also generated. These surpluses could be fed back into the university’s grid, contributing to a more efficient and sustainable use of energy resources.

Furthermore, an analysis of the hybrid configuration’s performance highlighted the system’s resilience. The combination of solar and wind energy sources mitigated the individual limitations of each system. While solar generation may decrease on cloudy days or at night, the wind system could compensate for these variations, ensuring a continuous energy supply. This synergy between both systems not only enhanced generation capacity but also provided stability and reliability to the PtG plant’s energy supply.

Figure 9 shows the energy production in kW from various energy sources from October 2022 to April 2023, demonstrating that the hybrid system (gray bars) had the highest monthly production compared to the photovoltaic system (orange bars), the wind system (blue bars), and the electrical grid (yellow bars). The photovoltaic system consistently produced 4–5 kW, while the wind system had a lower output, with a slight increase in March and April 2023. The contribution from the electrical grid was minimal, highlighting the self-sufficiency of the renewable systems. The hybrid system’s surpluses (darker blue bars) fluctuated monthly, peaking in December 2022 and March 2023, which demonstrated the efficiency and capacity of these systems to generate additional energy. This underscores the potential of hybrid systems for achieving energy self-sufficiency and reducing carbon emissions.

In Figure 10, the simultaneous contribution of the wind and solar sources to the electrolyzer system is observed to be more stable than their separate performance. This stability promoted consistent hydrogen production and minimized the need for support from the university’s electrical grid.

Figure 11 clearly shows that in November, there was a necessity for backup energy from the grid, even though the system utilized two renewable energy sources. This indicates that these sources are intermittent and may occasionally experience a simultaneous decrease in electricity production [4,17].

Based on the analysis conducted in this section, it can be inferred that it is crucial to consider the climatic conditions of the study site where these technologies will be implemented, particularly the impact of temperature on the air properties and the performance of wind and photovoltaic solar generation technologies.

4. Conclusions

The analysis of the 15 kW hybrid wind–solar photovoltaic system revealed its capacity to adapt to variations in wind and solar photovoltaic energy flows, maintaining a constant supply to the electrolyzers and thereby ensuring a continuous production of green hydrogen, except for a few days in November 2022 and some days in February and March 2023, generating surpluses during other measured periods. Additionally, the systems complemented each other well to supply the demand of the PtG pilot plant, and in situations where the system could not efficiently supply the demand, the university’s grid acted as a backup, mitigating the consumption of the PtG pilot plant and ensuring its continuous operation.

On the other hand, it is evident that the solar photovoltaic source supplied the highest electrical power to the PtG pilot plant, with support from the wind source and occasionally the conventional electrical grid when renewable sources were insufficient. Finally, the ambient temperature at the system’s location was an important variable in the efficiency of the use of wind and solar photovoltaic energy resources.