Economic Feasibility Analysis of Greenhouse–Fuel Cell Convergence Systems
1
Rural Research Institute, Korea Rural Community Corporation, 870, Haean-ro, Sangnok-gu, Ansan-si 15634, Gyeonggi-do, Republic of Korea
2
Department of Rural Construction Engineering, Kongju National University, 56, Gongjudaehak-ro, Gongju-si 32588, Chungcheongnam-do, Republic of Korea
3
Smart Farm & Architecture Project Department, Korea Rural Community Corporation, Naju-si 58327, Jeollanam-do, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(1), 74; https://doi.org/10.3390/su16010074
Submission received: 21 November 2023
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Revised: 13 December 2023
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Accepted: 14 December 2023
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Published: 20 December 2023
(This article belongs to the Section Energy Sustainability)
Abstract
:This study investigated the economic feasibility of introducing a new energy system, the greenhouse–fuel cell convergence system (GFCS), to a greenhouse that consumes a lot of energy. The GFCS is a concept that uses the heat generated during the power generation process to cool and heat the greenhouse, uses the emitted CO2 as fertilizer inside the greenhouse, and sells the generated electricity. For economic evaluation, the annual energy consumption of the greenhouse was first calculated through simulation, and then the appropriate fuel cell capacity was determined. Next, a farmer-led business model and a utility-led business model were presented, and the economic feasibility of these models was evaluated for tomatoes and mangoes. The economic evaluation of the GFCS confirmed the economic feasibility by comparing it with a greenhouse equipped with a geothermal heat pump. The results of the economic evaluation revealed that the farmer-led model had a benefit–cost ratio (B/C) ranging from 0.62 to 0.65 even with government support for heat utilization facilities, which was lower than that of a typical greenhouse (1.03 to 1.06). On the other hand, the utility-led model showed high B/C ranging from 1.19 to 1.86. If the initial investment cost of the fuel cells is reduced and a government policy is appropriately supported, the GFCS can be economically applied to greenhouses.
1. Introduction
Protected agriculture is one of the most energy-intensive fields in the agricultural sector. This high energy demand is required due to the need for year-round environmental control to support crop growth, irrespective of the season. Therefore, production revenue in protected agriculture should ideally surpass that of open-field crops. However, income has been steadily declining due to rising operating costs resulting from recent increases in energy prices.
Previous research aiming to reduce energy consumption in greenhouse design and operations has been steadily progressing. In order to achieve this goal, various studies have been conducted, including studies on optimizing design for energy efficiency [1,2,3], maximizing ventilation efficiency [4,5,6], reducing lighting energy consumption [7,8,9], and applying high-performance systems [10,11,12]. In addition to these technological advancements, the introduction of renewable energy sources is essential for further reducing energy consumption in greenhouses and ultimately achieving net-zero energy use.
Renewable energy systems are technologies that harness natural energy sources, such as solar, wind power, and geothermal sources. Numerous studies have been conducted to implement renewable energy systems in greenhouses, with a particular focus on photovoltaic (PV), solar thermal, and geothermal applications [13].
Transparent photovoltaics (TPVs) can be installed integrally with greenhouses, and these are known as building-integrated photovoltaics (BIPVs). TPVs have the advantage of being able to grow crops and produce electricity at the same time because they are partially transparent. Reda et al. [14] investigated the power generation performance and payback period of semi-transparent BIPVs installed on 20% of a greenhouse roof. The results of the study revealed that the electricity generated through PVs was 637 kWh per year, and the crop production did not significantly differ from that of an unshaded greenhouse. The payback period was nine years. James et al. [15] investigated the performance of semi-transparent photovoltaics (STPVs) installed on the roof and their impact on greenhouses. STPVs increased lighting energy consumption by 84%, but as a result, heating energy consumption decreased by 12% in winter. Instead of increasing the lighting energy consumption, STPVs reduced the supplemental lighting energy consumption by 43.7%. The study concluded that STPVs are not currently economical according to life cycle cost (LCC) analysis. Angeliki et al. [16] analyzed the effect of partial shading caused by PVs installed on 20% of a roof’s area. It was found that even with the installation of PVs, there was no significant effect on the temperature of the greenhouse or on crop growth and quality.
Meanwhile, geothermal energy is the most widely applied clean energy system in greenhouses. Geothermal source heat pumps (GSHPs) are more efficient than conventional air source heat pumps (ASHPs) and consume less energy. According to the research results of Laila et al. [17], GSHPs can save 21% (50.1 kWh/m2) more energy than ASHPs. Hüseyin [18] compared the performance of horizontal ground source heat pumps (HGSHPs) and vertical source heat pumps (VGSHPs) applied to greenhouses. As a result of applying pebbles to HGSHPs, the heat transfer coefficient increased from 1.7 W/mK to 1.75 W/mK. Comparing the two systems, the coefficients of performance (COPs) for HGSHPs and VGSHPs were 3.3 and 3.5, respectively. However, VGSHPs had a higher installation cost than HGSHPs, making HGSHPs more economical.
Solar-assisted heat pumps (SAHPs) are systems that enhance the performance of heat pumps by utilizing solar energy. According to the findings of Francesco et al. [19], the introduction of a SAHP combined with solar collectors could reduce heating energy consumption in greenhouses by 20% and lower heating costs by 40%. Giorgio et al. [20] evaluated the performance of a dual-source multifunctional heat pump combined with hybrid photovoltaic/thermal (PVT) panels as a new high-performance system. The results of the study showed that the proposed system demonstrated high annual efficiency and achieved a 15% reduction in the average daily energy consumption.
Fuel cells are attracting attention as new and clean energy sources. Fuel cells produce electricity cleanly and efficiently using the chemical energy of hydrogen or other fuels. If hydrogen is the fuel, the products are electricity and heat, and thus energy efficiency can be further improved by utilizing them. Therefore, fuel cell-based micro-combined heat and power (CHP) technology has received significant attention [21]. The heat produced during the power generation process is recovered and used for applications such as space heating and domestic hot water. Consuming this heat can increase system efficiency from 20% to over 90%, depending on the prime mover technology and the extent to which waste heat is utilized [22]. Huangfu et al. [23] analyzed the economic feasibility of micro-CHP. The study showed that micro-CHP has excellent economic viability, with a payback period of 2.97 years. Deepesh et al. [24] investigated the performance of fuel cells as micro-trigeneration, utilizing waste heat from prime movers to generate heating and cooling along with electrical power. It is estimated that in small-scale (<15 kWe) trigeneration systems, more than 80% of the fuel energy is converted to usable energy, increasing the potential for cost and energy savings from adopting CHP systems.
Only one study has assessed fuel cell systems in greenhouses in terms of energy savings. Amir et al. [25] investigated the feasibility of proton exchange membrane fuel cells (PEMFCs) in a commercial greenhouse. The study showed that a 3 kW fuel cell system was capable of covering approximately 25% and 10% of the usual electricity and heat demands of a 1000 m2 commercial greenhouse in a year.
The results of the literature review showed that various efforts are being made to achieve net-zero or carbon neutrality by utilizing new and renewable energy systems in greenhouses. As a new energy system, fuel cells can be introduced to greenhouses by advancing previous research [25]. If the heat and CO2 generated in the power generation process are utilized in greenhouses, it can not only save energy but also increase crop production. Therefore, this study aimed to explore the potential for greenhouse energy savings and assess the economic feasibility of using greenhouse–fuel cell convergence systems (GFCSs). The novelties and contributions of this paper are as follows:
- The concept of introducing fuel cells, a new energy system, into greenhouses is presented.
- In addition to the existing combined heat and power generation method, increased crop production using carbon dioxide was considered.
- An economic evaluation was conducted using government energy policies.
- Government support methods for the expansion of the GFCS were presented.
2. Concept of Greenhouse–Fuel Cell Convergence Systems
This section introduces the concept of the greenhouse–fuel cell convergence system (GFCS), which increases production by supplying carbon dioxide while providing cooling and heating through the utilization of heat generated during power generation.
Fuel cell power generation is a high-efficiency power generation system that produces electricity and heat through chemical reactions between hydrogen and electricity. Unlike conventional power generation systems, it generates electricity directly without the need for fuel combustion, resulting in high power generation efficiency and minimal energy loss.
Additionally, the fuel cell power generation system is recognized for creating less pollution and being an eco-friendly energy production system with an energy utilization rate of up to 95% when electricity and heat are used. In addition, the fuel cell power generation system offers the advantage of requiring a small installation area while significantly improving energy utilization efficiency through the simultaneous production of electricity and heat.
Meanwhile, among fuel cell types, solid oxide fuel cells (SOFCs) operate at higher temperatures than other fuel cells, resulting in the generation of high-temperature heat, carbon dioxide, and electricity during the power generation process. Therefore, SOFCs are advantageous for cogeneration, and their integration with greenhouses, along with carbon dioxide utilization, offers numerous benefits (see Figure 1).
Taking advantage of this fuel cell power generation, the concept of the GFCS presented in this study is as follows: carbon dioxide generated during the fuel cell power generation process is captured and used for facility horticulture, the emitted heat is used to heat the greenhouse, and the generated electricity is sold. The advantages of this convergence system are presented in Table 1.
In South Korea, when farmers engage in renewable energy generation projects using fuel cells, they can obtain additional income by utilizing the renewable portfolio standard (RPS) system. This allows them to earn income through power sales at the system marginal price (SMP) and sales of renewable energy certificates (RECs). Additionally, by supplying the heat and carbon dioxide produced during the fuel cell power generation process to greenhouses, they can reduce farm operating costs (cooling and heating expenses as well as carbon dioxide supply costs) and enhance crop productivity.
Currently, there are no installation or operational cases for such integrated systems with these benefits. Therefore, an evaluation is needed to determine the economic feasibility of introducing the GFCS. Consequently, this study conducted an economic assessment of the GFCS using a simulation model.
3. GFCS Energy Simulation Model and Calculation of Energy Consumption
3.1. Calibration and Establishment of the Energy Simulation Model
In order to investigate the impact of GFCS implementation, we calculated the greenhouse’s energy consumption using a theoretical simulation model. To accurately determine the annual energy consumption of the greenhouse, it is crucial to precisely calculate the mechanisms of heat transfer within the greenhouse and faithfully simulate its actual operational methods. Therefore, in this study, we employed the modified ESP-r, a precise energy simulation and analysis tool capable of predicting thermal behavior on the basis of greenhouse operational methods. This tool allowed us to calculate both energy demand and total energy consumption accurately. The modified ESP-r was developed through code modifications to accurately simulate the greenhouse operation method, and research results on the development content and effectiveness of the simulation tool can be found in existing research [26].
To ensure the reliability of the energy analysis model, we initially developed an energy analysis model that simulates real operational greenhouses. Subsequently, we utilized this model for the economic evaluation of the GFCS. The calibration of the energy analysis model was conducted following Guideline 14 of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE).
To ensure the reliability of the simulation analysis model, the following calibration and establishment methods were employed. Initially, data were collected by visiting and interviewing actual greenhouse facilities for a specific year. These data included structural details, equipment capacities, operational methods, actual energy consumption, and external weather data. The collected data were processed to fit the energy simulation input values, and an energy analysis model was established on the basis of the processed data. The model underwent adjustments by comparing the actual energy consumption of the greenhouse with the predictions made by the simulation model, ensuring that the simulation input values were accurate. Finally, the simulation model’s prediction accuracy was verified against the ASHRAE Guideline 14 standard [27], completing the establishment of the analysis model.
In this study, the focus was on establishing a simulation analysis model for tomato greenhouses. Detailed architectural plans, meteorological data, operational protocols, and actual energy consumption records for the tomato greenhouses were provided, covering approximately one year (from January to December 2021). Figure 2 shows the external weather environment record, and ‘Measured’ in Figure 3 indicates the monthly energy usage for one year in 2021. The energy analysis model was crafted using this dataset.
The calibration of the simulation analysis model was performed with a focus on monthly energy consumption. In Figure 3, ‘measured’ and ‘simulated’ represent actual energy consumption and predicted values of the simulation model, respectively, and the simulation model showed an error of the CV(RMSE) of 112% and an NMBE of 5%. It is important to note that ASHRAE Guideline 14 sets rigorous monthly calibration standards, with the NMBE ideally within ±5% and the CV(RMSE) within 15%. Meeting these standards demands a significant investment of time and effort. Given the challenges of aligning with the proposed ASHRAE standards, this study proceeded with the calibrated simulation model at its current level.
3.2. Calculation of Greenhouse Energy Consumption and Fuel Cell Capacity
Using the calibrated greenhouse analysis model and typical meteorological year (TMY) weather data for the Jinju [28] region in South Korea, the energy consumption of the greenhouse was calculated, as shown in Figure 4. It was assumed that the cooling and heating of the greenhouse were performed annually. For the tomato greenhouse, the annual cooling and heating energy demand, calculated using standard weather data, was found to be 149.3 kWh/m2 for cooling and 259.98 kWh/m2 for heating.
As shown in Figure 5, we calculated the fuel cell capacity for installation on the basis of the cooling and heating energy demands (see Figure 6), assuming a heat production rate of 45% relative to the supplied gas. When determining the capacity, we assumed that 100% of the energy consumption was processed by the fuel cell to maximize heat utilization efficiency. However, we did not account for energy losses during heat storage. Additionally, in cases in which the fuel cell waste heat supply capacity was exceeded, we assumed the use of auxiliary heat sources, such as boilers.
Meanwhile, it was found that a 1 MW fuel cell installed in a 1 ha greenhouse could supply CO2 levels of 800 ppm or more for four hours in the morning. In other words, an increase in greenhouse CO2 concentration can be expected to increase crop yields.
To evaluate the economic feasibility of GFCS implementation, we selected two types of crops: tomatoes, a common crop grown in Korean greenhouses, and mangoes, a high-temperature crop. Tomatoes are one of the most widely cultivated crops in Korean greenhouses, while mangoes, a high-temperature crop, allow for the maximization of fuel cell installation capacity and advantages. For the two selected crops, we calculated the cooling and heating energy requirements and determined the required fuel cell installation capacity. The calculated fuel cell capacities were 1183 kW/ha for tomatoes and 1632 kW/ha for mangoes. Since the fuel cell installation capacity varies depending on the cooling and heating energy requirements, the high-temperature conditions required for mango growth resulted in a higher fuel cell installation capacity.
4. Economic Evaluation of Business Model
4.1. Development of Business Models
To assess the economic feasibility of GFCS implementation for the two types of crops (tomatoes and mangoes), we established business models. The characteristics and concepts of each business model are summarized in Table 2.
The farmer-led model was tailored to small-scale greenhouse facilities of approximately 1–2 hectares. It is a business model in which farmers install fuel cell power generation facilities and utilize CO2 fertilization and waste heat to increase agricultural income and non-agricultural income (SMP and REC).
The utility-led model targeted large-scale greenhouse facilities covering approximately 50 hectares. Companies can gain recognition for greenhouse gas reduction, offering a solution to the challenge of site acquisition related to the NIMBY phenomenon associated with fuel cells. In this model, farmers can benefit from the free use of the heat and carbon dioxide generated during the power generation process to enhance income and productivity in agriculture.
4.2. Economic Evaluation
An economic evaluation of both farmer-led and utility-led business models for two crops, tomatoes and mangoes, was conducted. Additionally, the economic benefits of GFCS adoption were assessed by comparing it with conventional geothermal heat pump (HP)-equipped greenhouses were quantitatively assessed. The cost items and contents applied in the cost–benefit analysis for economic evaluation are detailed in Table 3.
The input values for the economic analysis of the selected business models for the two crops are provided in Table 4. The numerical data used in the study were obtained from interviews with farmers and advice from fuel cell installers. The farmer-led model assumed a 30% increase in production due to the carbon dioxide supply. In the utility-led model, in which the utility company leads the fuel cell power generation business and farmers receive carbon dioxide and waste heat for free during the power generation process, the initial investment and maintenance costs for heating and cooling facilities were relatively low.
We have analyzed the economic indicator, B/C ratio, for each business model, and the results are shown in Figure 7. The economic analysis was performed assuming government support for heat utilization facilities at 0%, 45%, and 90% for each business model. In addition, to compare the economic feasibility with a conventional greenhouse, we also evaluated the economic feasibility of a greenhouse equipped with geothermal heat pumps.
The analysis results showed that the farmer-led model in agriculture had low economic feasibility, primarily due to the high initial investment costs of fuel cells and the recent increase in gas prices. The B/C was found to be 0.61 to 0.65 for both crops despite government support, which is because the high initial investment and maintenance costs of fuel cells had a significant impact on economic feasibility in this model. Therefore, to promote the activation of the farmer-led model in agriculture, alternative support methods need to be considered. Alternative methods were derived in Chapter 5 using statistical methods.
In the case of the utility-led model, the B/C appeared to be high because the farmers had no fuel cost burden, and the crop productivity increased due to CO2 fertilization. Even without government support for fuel cell heat utilization facilities, the economic feasibility was higher than that of conventional greenhouses. When the government provides subsidies for heat utilization facilities up to 90%, the B/C exceeds 1.58, indicating very high feasibility. The utility-led business model provides farmers with free waste heat, so it is advantageous to grow crops with high profitability, regardless of energy costs.
5. Strategies for Ensuring the Economic Feasibility of the Farmer-Led Model
In this section, we explore potential strategies for securing the economic feasibility of the farmer-led model with a low B/C ratio. To begin, we selected six variables, as shown in Table 5, and analyzed their impact on the economic feasibility of the GFCS and how each variable affects the B/C ratio.
For the sensitivity analysis, each variable was constructed into 1000 input sets using the Latin hypercube sampling (LHS) method in Python. These input sets were then applied as input values for the farmer-led business model, and the B/C was analyzed as an economic feasibility indicator. Sensitivity analysis results from sampling can provide sensitivity coefficients to quantify their magnitudes. Standardized regression coefficients, representing the sensitivity of the input variables to the B/C, were calculated, and the results are presented in Figure 8.
The results of the analysis showed that in order to secure the economic feasibility of the farmer-led model, increasing incentives (SMP and REC) for the two crops to support them had the greatest impact. This was followed by a method of lowering the price of gas used in fuel cell power generation and a method of reducing initial investment costs by supporting fuel cell installation costs. On the other hand, measures to support fuel cell maintenance expenses, heat utilization facility costs, and heat utilization facility maintenance expenses had a smaller impact on ensuring the economic feasibility of the business model.
Focusing on the sensitivity analysis results, we investigated the government support ratio for the SMP + REC price, gas price, and fuel cell installation cost to ensure economic feasibility for the three input variables that had the greatest impact on the B/C. Figure 9 illustrates how the three input variables need to change to achieve a B/C between 0.5 and 1.5. Then, we identified the minimum values required to ensure economic feasibility when the B/C reaches 1.0. In Figure 9, it can be seen that economic feasibility is ensured when price or ratio is applied to the red area on the right.
According to the analysis results, the following measures are proposed to ensure the economic feasibility of the farmer-led business model:
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- SMP + REC: The current price is 218 KRW, and to secure the economic feasibility of each crop, SMP + REC prices need to increase by over two times, reaching 438–515 KRW.
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- LNG price: The gas price for B/C to become 1.0 was found to be −34 to −100 KRW/Nm3, and a negative number means that when using gas for power generation, the government provides an additional subsidy of 34~100 KRW/Nm3.
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- Fuel cell subsidy: This refers to the government support rate of the initial installation cost of fuel cells, and it was found to be 111~120%, which means that 100% of the initial installation cost of the fuel cell should be supported and an additional amount equivalent to 11~20% should be subsidized.
The analysis results suggest that achieving economic feasibility for the farmer-led power generation project in agriculture is challenging due to high fuel prices and initial investment costs. Supporting costs on individual items is not practical. Therefore, the economic feasibility of the farmer-led model can be secured through a combination of raising incentives (SMP + REC), lowering gas prices, and providing appropriate government support for initial fuel cell installation costs.
6. Discussion and Conclusions
6.1. Discussion
Hydrogen is an ideal energy source to replace fossil fuels such as oil and gas, and it is attracting attention as an energy source that can achieve decarbonization. Fuel cells are a power generation system that uses hydrogen, and the government is making various efforts to promote the distribution of fuel cells. RPS was enacted for the purpose of expanding the supply of new and renewable energy and fostering related industries by mandating power generation businesses to supply a certain percentage of electricity. However, if the high LNG supply prices and fuel cell power generation facility installation costs persist, power generation companies may not undertake utility-led fuel cell power generation projects near greenhouses. Therefore, government policies, such as providing incentives to power generation companies, are necessary when implementing fuel cell power generation projects integrated with greenhouses. It is believed that the GFCS can be spread by using the results of this study, which determines which incentives the government should provide and how many.
Through this study, it was found that the introduction of the GFCS can achieve high economic feasibility only under a utility-led business model. However, there is a limitation in that the GFCS assessment was performed on the basis of theoretical performance rather than performance verified through experiments. Therefore, it is possible that the results of the economic evaluation seemed more positive than they actually were. In the future, it will be necessary to verify the performance of the convergence system and conduct an economic evaluation through empirical research.
In future research, when introducing the GFCS, it will be crucial to seek cost-effective alternative fuels to replace expensive LNG. Options such as green hydrogen from renewable energy sources or biogas derived from livestock manure and food waste can serve as viable alternatives. If these technologies are commercialized, it would be possible to implement eco-friendly GFCSs that do not emit greenhouse gases.
6.2. Conclusions
In South Korea, the majority of greenhouse heating and cooling systems rely on fossil energy, with heating costs comprising 30% to 40% of the total operating costs. Consequently, fluctuations in international oil prices significantly impact farmers’ incomes.
This study proposed the integration of the greenhouse–fuel cell convergence system (GFCS), a new energy solution, into greenhouses as a strategy to reduce energy consumption and enhance competitiveness. The introduction of the GFCS is expected to decrease heating and cooling energy expenses, increase productivity, and secure non-agricultural income through the utilization of the government’s RPS system.
The primary results of this study were as follows:
- The energy consumption of a 1 ha greenhouse was calculated using the corrected simulation analysis model. When covering 100% of the energy requirement with the fuel cell, the appropriate installation capacity of the fuel cell was determined to be 520 kW/ha for tomatoes and 820 kW/ha for mangoes.
- Farmer-led and utility-led business models were proposed to evaluate the economic feasibility of introducing GFCS.
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- In the farmer-led model, farmers install fuel cell power generation facilities in small-scale greenhouses within their own ownership, typically ranging from 1 to 2 hectares. They then generate agricultural and non-agricultural income through electricity sales, CO2 fertilization, and waste heat utilization.
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- In the utility-led model, power generation companies install fuel cell power generation facilities near large greenhouses, typically around 50 hectares, or in unused land, such as reclaimed land. Farmers then increase agricultural income by utilizing CO2 fertilization and waste heat.
- The economic evaluation results of the two proposed business models are as follows:
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- The farmer-led model is not yet economical due to the high initial investment cost of fuel cells and the recent rise in gas prices. Even with government support for heat utilization facilities, the B/C ranged from 0.62 to 0.65, lower than the general greenhouse range of 1.03 to 1.06.
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- The utility-led model showed a high B/C of 1.19 to 1.86 because there was no burden on farmers’ fuel costs, and crop productivity increased because of CO2 fertilization.
- Support for SMP + REC, gas prices, and fuel cell installation costs is needed to secure the economic feasibility of the farmer-led model.
Author Contributions
Conceptualization, C.-s.L. and H.S.; methodology, C.-s.L.; software, C.-s.L.; validation, H.S., M.-L.P., and Y.C.; formal analysis, Y.C.; investigation, C.P.; resources, C.P.; data curation, H.S.; writing—original draft preparation, C.-s.L. and H.S.; writing—review and editing, C.P. and M.-L.P.; visualization, Y.C.; supervision, C.P.; project administration, H.S.; funding acquisition, H.S. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the Korea Environment Industry and Technology Institute (KEITI) through the Water Management Program for Drought Project, funded by the Korea Ministry of Environment (MOE) (2022003610002); This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (120095031HD020).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Conflicts of Interest
The authors declare no conflict of interest.
Nomenclature
| ASHP | Air source heat pump |
| B/C | Benefit–cost ratio |
| BIPV | Building-integrated photovoltaics |
| CHP | Combined heat and power |
| COP | Coefficient of performance |
| GSHP | Geothermal source heat pump |
| GFCS | Greenhouse–fuel cell convergence systems |
| HGSHP | Horizontal source heat pumps |
| LCC | Life cycle cost |
| LHS | Latin hypercube sampling |
| PEMFC | Proton exchange membrane fuel cell |
| REC | Renewable energy certificate |
| RPS | Renewable portfolio standard |
| SAHP | Solar-assisted heat pump |
| SMP | System marginal price |
| SOFC | Solid oxide fuel cell |
| STPV | Semi-transparent photovoltaic |
| TMY | Typical monthly year |
| TPV | Transparent photovoltaic |
| VGSHP | Vertical source heat pumps |
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Figure 1.
Concept of greenhouse–fuel cell convergence systems.
Figure 2.
Internal and external weather conditions in 2021.
Figure 3.
Comparison of measured energy consumption with simulation predictions.
Figure 4.
Energy consumption per hour in the greenhouse.
Figure 5.
Fuel cell installation capacity to meet energy requirements.
Figure 6.
Energy requirements and fuel cell capacity of tomato and mango greenhouses.
Figure 7.
Economic feasibility evaluation results depending on business model and subsidy ratio for tomatoes and mangoes.
Figure 7.
Economic feasibility evaluation results depending on business model and subsidy ratio for tomatoes and mangoes.
Figure 8.
Sensitivity analysis results for each input variable for tomato and mango.
Figure 9.
Cost or subsidy for B/C to be greater than 1.0 for tomato and mango.
Table 1.
Advantages of GFCS implementation.
| Action | Advantages |
|---|---|
| Use of captured CO2 for greenhouse enrichment | Higher CO2 levels (from 600 ppm to 1000 ppm) in greenhouses boost fruit and vegetable yield and quality, leading to increased farm profits. |
| Use of waste heat for greenhouse heating | Using wasted heat from power generation to save on heating costs in the greenhouse |
| Selling generated electricity | Selling electricity and renewable energy supply certificates to secure additional agricultural income |
Table 2.
Concept and characteristics of business models.
| Category | Farmer-Led Model | Utility-Led Model |
|---|---|---|
| Concept |
|
|
| Scale |
|
|
| Operator |
|
|
| Advantages |
|
|
Table 3.
Assumptions of business models for economic analysis.
| Business Model | General Greenhouse | Farmer-Led | Utility-Led | |
|---|---|---|---|---|
| Crops | Cucumbers, Mangoes. | |||
| Features |
|
|
| |
| Heat Source |
|
|
| |
| Costs | Direct Costs |
|
|
|
| Indirect Costs |
|
|
| |
| Benefits |
|
|
| |
Table 4.
Direct costs, indirect costs, and profits for economic analysis.
| (Unit: Million KRW) | General | Farmer-Led Model | Utility-Led Model | |||||
|---|---|---|---|---|---|---|---|---|
| Tomatoes | Mangoes | Tomatoes | Mangoes | Tomatoes | Mangoes | |||
| Costs | Direct Costs | Greenhouse construction costs | 1500.0 | 1500.0 | 1500.0 | 1500.0 | 1500.0 | 1500.0 |
| Heat utilization facility construction costs | - | - | 1500.0 | 1500.0 | 1500.0 | 1500.0 | ||
| Fuel cell installation costs | - | - | 6351.3 | 10,196.9 | - | - | ||
| HP (geothermal) installation costs | 107.8 | 173.1 | - | - | - | - | ||
| Total | 1607.8 | 1673.1 | 9351.3 | 13,196.9 | 3000.0 | 3000.0 | ||
| Indirect Costs | Operating expenses | 68.3 | 66.7 | 43.3 | 41.7 | 43.3 | 41.7 | |
| Heat utilization facility maintenance costs | - | - | 15.0 | 15.0 | 15.0 | 15.0 | ||
| Fuel cell maintenance costs | - | - | 236.1 | 379.1 | - | - | ||
| HP maintenance costs | 9.0 | 14.4 | - | - | ||||
| Fuel costs (electricity/gas) | 35.6 | 57.2 | 1131.3 | 1816.2 | - | - | ||
| Total | 112.9 | 138.3 | 1425.7 | 2252.0 | 58.3 | 56.7 | ||
| Benefit | Crop sales | 243.2 | 283.9 | 243.2 | 283.9 | 243.2 | 283.9 | |
| Power sales | - | - | 530.5 | 851.6 | - | - | ||
| REC sales | - | - | 507.4 | 814.6 | - | - | ||
| Yield increase | - | - | 73.0 | 85.2 | 73.0 | 85.2 | ||
| Total | 243.2 | 283.9 | 2800.2 | 4352.1 | 58.3 | 56.7 | ||
Table 5.
Variable and ranges for sensitivity analysis.
| Variable | Input Range |
|---|---|
| SMP + REC (KRW/kWh) | 100~500 |
| Gas supply price (KRW/Nm³) | 500~1000 |
| Subsidy for fuel cell installation cost (%) | 10~90 |
| Subsidy for fuel cell maintenance cost (%) | 10~90 |
| Subsidy for heat utilization facility cost (%) | 10~90 |
| Subsidy for heat utilization facility maintenance cost (%) | 10~90 |
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MDPI and ACS Style
Lee, C.-s.; Shin, H.; Park, C.; Park, M.-L.; Choi, Y. Economic Feasibility Analysis of Greenhouse–Fuel Cell Convergence Systems. Sustainability 2024, 16, 74. https://doi.org/10.3390/su16010074
AMA Style
Lee C-s, Shin H, Park C, Park M-L, Choi Y. Economic Feasibility Analysis of Greenhouse–Fuel Cell Convergence Systems. Sustainability. 2024; 16(1):74. https://doi.org/10.3390/su16010074
Chicago/Turabian StyleLee, Chul-sung, Hyungjin Shin, Changi Park, Mi-Lan Park, and Young Choi. 2024. "Economic Feasibility Analysis of Greenhouse–Fuel Cell Convergence Systems" Sustainability 16, no. 1: 74. https://doi.org/10.3390/su16010074
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