Energy Saving Technologies and Practices in Facility Agriculture in Cold Regions

Abstract

With the growth of the global population, energy demand continues to rise, making cross-regional energy transportation less viable as a sustainable solution. As a result, the construction of facilities for agriculture in cold regions has become increasingly important in the development of modern agriculture. However, cold region facility agriculture faces significant energy and environmental challenges, necessitating the advancement and application of energy saving technologies. This study addresses the high energy consumption in cold region facility agriculture by experimentally evaluating the integrated effects of geothermal heat pumps, solar collectors, intelligent light control systems, LED plant lamps, and smart ventilation systems in saving energy. The focus is on analyzing the technical adaptability and economic feasibility of these technologies under extremely cold conditions in Heilongjiang. The research findings indicate an overall energy saving rate of 17.8%, with energy savings in heating, lighting, and ventilation systems being 17.6%, 18.6%, and 17.4%, respectively. Economic analysis shows that geothermal heat pumps and high efficiency insulation materials have a short investment payback period and are suitable for widespread adoption, while solar collectors and intelligent light control systems are more appropriate for long-term application. This study demonstrates that intelligent and integrated energy saving technologies have significant potential in cold region facility agriculture, providing both data support and technical references for the efficient, low-carbon development of agriculture in cold climates. This study not only provides scientific evidence for the sustainable development of cold region facility agriculture but also highlights the practical implications of these technologies for reducing energy consumption and promoting low-carbon agriculture.

1. Introduction

Cold region facility agriculture ensures crop production in extreme conditions such as low temperatures, short daylight, and variable climates, common in high-latitude regions such as Northeast Asia, Northern Europe, and North America [1]. It contributes to a stable food supply, reduces transportation needs, and supports regional economic growth. However, energy demand for heating, lighting, and ventilation during winter significantly increases operational costs and exacerbates environmental impact. In Heilongjiang, where winter temperatures often fall below −25 °C, heating consumes 50–60% of energy costs, while lighting accounts for an additional 20–30%. Developing efficient energy saving technologies for sustainable agriculture in cold climates is critical to addressing these challenges [2].

To address the high energy consumption in cold region facility agriculture, much research has focused on energy saving technologies for heating, lighting, ventilation, and intelligent control systems [3]. In Heilongjiang, facility agriculture is essential for food security and sustainability. However, greenhouses’ reliance on traditional heating and high-pressure sodium lamps often results in inefficiencies compared to LED lights with smart controls [4]. Given the region’s extreme climate and growing pressure to reduce carbon emissions, geothermal heat pumps and solar thermal systems offer an alternative by utilizing underground temperatures and solar energy [5]. Intelligent lighting systems and LED plant lights replace traditional lamps, enhancing energy efficiency. Similarly, intelligent ventilation systems, equipped with sensors, optimize airflow by adjusting ventilation intensity according to real-time environmental data [6]. However, most studies focus on individual technologies, while systematic research on the synergy between multiple energy saving technologies in cold environments remains limited. The practical implementation of integrated energy saving systems is also unclear, and existing technologies face challenges in economic feasibility and adaptability, limiting large-scale adoption [7].

This study proposes an integrated, multi-technology energy saving solution to tackle high energy consumption in cold region facility agriculture. Key innovations include: (1) Synergistic use of multiple technologies: This study integrates geothermal heat pumps, solar collectors, intelligent lighting control systems, LED plant lights, and intelligent ventilation systems to enhance overall energy efficiency in greenhouses under extreme cold and short daylight conditions. (2) Intelligent control systems: The study develops a control system that automatically adjusts temperature, humidity, and lighting based on real-time environmental data, optimizing energy use. (3) Economic feasibility analysis: This research evaluates the energy efficiency and economic viability of different technologies through payback periods and operational cost analysis, identifying high-performing, cost-effective solutions for cold region agriculture. This study advances the field of cold region agriculture by addressing the synergistic application of energy saving technologies. It validates the premise that integrated systems improve energy efficiency, particularly in extreme environments. Moreover, by comparing energy saving and traditional designs over two experimental periods (November 2022 to March 2023 and November 2023 to March 2024), the study ensures consistent operational and structural conditions while environmental parameters (e.g., temperature and humidity) are monitored daily to reduce external variability. Unlike previous agricultural research, which focused on individual technological domains, such as remote sensing [8], this study validates the theoretical premise that a coordinated system approach enhances energy efficiency, particularly in extreme environments.

In conclusion, the integrated energy saving solution proposed in this study significantly improves the overall energy efficiency of cold region greenhouses and provides scientific evidence and practical support for the low-carbon, sustainable development of cold region facility agriculture.

Current Situation and Challenges of Energy saving Technologies in Facility Agriculture in Cold Regions.

The rapid development of facility agriculture in cold regions has driven significant advancements in energy saving technologies, addressing the high energy consumption demands for greenhouse environmental regulation. The main energy saving technologies applied in these regions focus on heating, lighting, ventilation, heat insulation, and intelligent control systems, all of which contribute to enhancing energy efficiency and reducing costs in facility agriculture [9]. However, the application of these technologies faces several challenges in extreme cold climates, including:

• High heating demand: The prolonged and harsh winters in cold regions lead to a significant heating requirement, which can strain the capacity of traditional energy saving systems and increase operational costs.
• Reduced solar energy availability: Short daylight hours and frequent overcast conditions limit the efficiency of solar heating and lighting technologies, making it challenging to maintain optimal energy performance.
• Sensor and system stability: Extremely low temperatures often affect the accuracy and reliability of sensors used in intelligent control systems, potentially leading to suboptimal operation.
• Material durability: Insulation materials and energy saving equipment are exposed to severe temperature fluctuations and potential wear, which can reduce their effectiveness and lifespan.
• Economic feasibility: The high initial investment costs for advanced energy saving technologies can hinder their widespread adoption, particularly in small- and medium-sized agricultural facilities.

This paper will conduct a classified review of the existing energy saving technologies and point out the technical deficiencies and research challenges in their application in cold regions [10].

1.1. Heating and Insulation Technologies

Heating and heat insulation technologies are among the most fundamental energy saving requirements in facility agriculture in cold regions. Due to the long periods of low temperatures in winter in cold regions, greenhouses must be equipped with effective heating systems, and at the same time, heat loss needs to be reduced through heat insulation materials.

1.1.1. Ground Source Heat Pump System

Ground source heat pumps (GSHPs) are effective for heating by utilizing the constant temperature of the ground. They reduce dependence on traditional fuel-based heating, offering significant energy saving potential, particularly in low temperatures [11]. However, the high initial installation cost and reliance on stable underground temperatures can limit their efficiency in extreme cold conditions [12].

1.1.2. Solar Heating System

Solar heating systems convert solar energy into thermal energy, transferring it to greenhouses via hot water circulation. However, extreme cold, heavy snow, and reduced solar irradiance reduce the performance of photovoltaic modules in winter [13]. Combining solar heating with thermal storage can alleviate this, but high installation costs and maintenance challenges remain [14].

1.1.3. Thermal Insulation Material

Thermal insulation materials such as multilayer composites, vacuum insulation panels, and nanoparticle coatings reduce heat loss. These materials show promise, but issues such as durability, corrosion resistance, and high costs remain [15,16,17]. Further research is needed to optimize these materials for long-term, high efficiency insulation.

1.2. Lighting and Light Control System

Due to short daylight hours, the demand for artificial lighting in cold region greenhouses is high. Effective lighting technology plays a crucial role in facility agriculture in these regions.

1.2.1. LED Plant Light

LED plant lights, known for their high efficiency and low energy consumption, have replaced traditional light sources such as high-pressure sodium lamps. They adjust the spectrum and light intensity to meet crop needs, improving light energy efficiency and reducing electricity consumption [18,19]. However, challenges include stability under low temperatures, high installation costs, and the need for customization to fit different crops [20]. Figure 1 illustrates the supplementary lighting system inside the greenhouse, which features high efficiency LED plant lights. These lights provide a combination of red and blue light optimized for crop growth at different stages, significantly enhancing photosynthetic efficiency while reducing overall energy consumption.

1.2.2. Intelligent Light Control System

The intelligent light control system uses sensors and predictive algorithms to monitor light intensity and adjust artificial lighting. This system reduces energy consumption when natural light is sufficient [21]. However, the reliability of sensors in extreme cold conditions remains a challenge, as does the adaptability of the system to fluctuating environmental conditions [22].

1.3. Ventilation and Cooling System

Ventilation systems in cold region greenhouses regulate temperature, humidity, and CO₂ levels, crucial for maintaining a stable environment and promoting crop growth.

1.3.1. Natural Ventilation and Mechanical Ventilation

Natural ventilation relies on structural design to exchange air through temperature differences. Mechanical ventilation expels hot air via fans to rapidly reduce temperature [23]. Although natural ventilation saves energy, it leads to heat loss in winter, limiting its use. Mechanical ventilation requires integration with heating systems, increasing energy consumption during cold months [24].

1.3.2. Intelligent Ventilation System

Intelligent ventilation systems use sensors to monitor temperature, humidity, and CO₂ levels, adjusting ventilation intensity accordingly [25]. While it optimizes energy consumption, sensor instability in extreme cold and higher maintenance costs remain challenges [26,27].

1.4. Research Deficiencies and Challenges

Despite advancements, energy saving technologies for facility agriculture in cold regions still face significant challenges in practical application.

1.4.1. The Degree of Technology Integration Is Insufficient

Current energy saving technologies often operate independently, leading to inefficiencies. Integrating and optimizing these technologies within a unified intelligent control system can significantly improve energy efficiency. Future research should focus on achieving system integration to maximize energy saving effects [28].

1.4.2. The Adaptability of Intelligent Control System Is Insufficient

Current intelligent control systems lack adaptability to extreme conditions and real-time environmental adjustments. Incorporating machine learning and adaptive algorithms could improve the systems’ performance in rapidly changing conditions [29,30,31,32].

1.4.3. Insufficient Durability and Suitability of Energy Materials

While high efficiency insulation materials have shown promise, their long-term durability under extreme cold conditions remains uncertain [17,33]. Developing materials with better corrosion resistance and long-lasting thermal insulation will be crucial for the future of cold region agriculture [34].

2. Materials and Methods

This study was conducted in cold region facility agriculture greenhouses in Heilongjiang, focusing on evaluating the energy efficiency of heating, lighting, and ventilation systems under energy saving technologies. The experimental period spans from winter to early spring (November to March of the following year), with the aim of assessing the effectiveness of various energy saving technologies in reducing energy consumption and improving the greenhouse environment under extreme low temperatures and insufficient light conditions [35]. This study will provide a detailed description of the experimental design background, data collection methods, and specific applications of the core energy saving technologies. This study focuses on experimentally validating the energy saving effects of fully integrated energy saving technologies. While predictive modeling was not utilized, the study employed a comparative experimental design to evaluate the direct impacts of these technologies under real-world conditions. Future research could incorporate predictive models to explore varying levels of technology adoption and optimize cost-benefit ratios.

2.1. Experimental Design Overview

2.1.1. Experimental Location

The experiment took place in a typical cold region greenhouse in Heilongjiang, primarily used for tomato cultivation. Tomatoes were chosen due to their prevalence in cold regions, with a growing period from November to March. The greenhouse temperature was controlled to maintain optimal conditions, and energy saving technologies were implemented to evaluate their performance under extreme cold conditions. The climatic conditions of the region, such as average temperature ranges from −18 °C to −5 °C and frequent snow cover [36], significantly impact the energy demands.

Table 1. Climatic conditions during the study.

Month	Avg. Min Temp (°C)	Avg. Max Temp (°C)	Avg. Humidity (%)	Avg. Daylight Hours	Avg. Solar Radiation (kWh/m2)
Nov.	−10	−5	70	6	1.5
Dec.	−15	−8	65	5	1.2
Jan.	−20	−10	60	5	1.0
Feb.	−18	−8	60	6	1.3
Mar.	−12	−5	55	7	2.0

summarizes the climatic parameters observed during the experimental periods, including temperature, humidity, and daylight hours. These conditions necessitated the implementation of advanced energy saving technologies.

Table 1 provides an overview of the climatic conditions during the study, illustrating the severity of the environment and its impact on the energy demands of heating, lighting, and ventilation systems.

The selection of the experimental site was based on the following conditions:

• Climatic Characteristics: The greenhouse is situated in a cold climate with short daylight hours, making it suitable for testing the applicability of energy saving technologies in extreme low-temperature environments.
• Heating Demand: The heating demand in Heilongjiang during winter is high, especially at night and under low light conditions. The average heating energy requirement during the winter months was recorded at approximately 14,500 kWh for November, rising to around 19,500 kWh during the coldest months of January and February. This significant energy demand is driven by the need to maintain optimal internal temperatures in greenhouses despite external temperatures dropping as low as −25 °C. The experimental data presented in this study highlights the challenges of sustaining energy-efficient operations under such extreme climatic conditions.
• Lighting Conditions: Winter natural lighting is weak, providing an ideal setting to assess the practical performance of the intelligent light control and LED lighting systems in cold regions.

Figure 1 illustrates the experimental greenhouse used in the study, which is located in Heilongjiang Province. Panel (a) depicts the interior layout of the greenhouse, showing the zonal arrangement of crops and the placement of energy saving equipment such as intelligent light control systems and high efficiency LED plant lights. The internal structure was optimized for environmental parameter monitoring and maintenance, providing an ideal setup for precise data collection.

Panel (b) provides an external view of the greenhouse, highlighting its robust construction with double-layer polycarbonate panels, designed to balance thermal insulation and natural light transmission. The greenhouse dimensions (15.6 m × 10.4 m × 3 m) and surface area (260 square meters) are adapted to optimize energy use while maintaining suitable conditions for crop growth. The outdoor image also demonstrates the facility’s capacity to withstand harsh winters with heavy snow cover, which is typical for the region.

2.1.2. Experiment Time and Cycle

The experiment ran from early November to the end of March, covering the coldest winter and spring transition periods. The study compared two experimental periods: November 2022 to March 2023 (baseline, without energy saving technologies) and November 2023 to March 2024 (with energy saving technologies). Both periods were conducted in the same greenhouse to eliminate variability due to structural or operational differences. Sensors and monitoring equipment were used to collect data on temperature, humidity, light intensity, carbon dioxide concentration, and energy consumption. Although no formal weather normalization was applied, daily records of environmental parameters ensured that observed differences in energy performance could be attributed to the implemented technologies. While predictive modeling and formal data normalization were not employed in this study, the experimental design ensured comparability by conducting experiments in the same greenhouse under consistent structural and operational conditions across two distinct periods. This approach minimizes variability due to external factors while focusing on the direct impacts of the integrated energy saving technologies.

2.2. Data Acquisition and Monitoring Program

A multi-level data acquisition scheme was implemented to ensure the accuracy and comprehensiveness of the data, including monitoring energy consumption of heating, lighting, and ventilation systems, as well as recording environmental parameters inside the greenhouse [37]. The data were collected using reliable and standardized instruments to ensure accuracy and consistency:

Heating energy consumption data were recorded using a Fluke 1735 (Fluke Corporation, Everett, WA, USA) three-phase power analyzer, with a collection frequency of once per day.

Temperature data were recorded using Omega TT2000 (Omega Engineering Inc., Stamford, CT, USA) series temperature sensors, which provide high-precision measurements.

Humidity data were collected using Vaisala HMP60 (Vaisala Oyj, Vantaa, Finland) series humidity sensors, ensuring accurate environmental control.

Light intensity was monitored using the LI-COR LI-250A (LI-COR Biosciences, Lincoln, NE, USA) light meter to assess the lighting conditions inside the greenhouse.

Ventilation system data, including energy consumption, humidity, and carbon dioxide levels, were monitored using Honeywell HIH-4000 (Honeywell International Inc., Morris Plains, NJ, USA) series sensors and SenseAir K30 (SenseAir AB, Delsbo, Sweden) CO₂ sensors.

2.2.1. Heating Energy Consumption Data Acquisition

Heating energy consumption was recorded daily using an energy metering device to track monthly variations in heating demand. The data collected includes the following components:

• Daily Heating Energy Consumption: Daily records of the energy consumption of the heating system to analyze its energy saving performance under varying temperature conditions.
• Greenhouse Interior Temperature: Temperature sensors monitor the temperature distribution across different areas of the greenhouse, allowing for assessment of the insulation performance of the thermal materials and the heating system.

2.2.2. Lighting System Data Acquisition

Lighting energy consumption and light intensity were monitored through the intelligent light control system and light sensors [38], with data collected every hour. The following main indicators are monitored:

• Light intensity: Records the light intensity within the greenhouse to ensure that the light requirements of crops are met under short-day conditions.
• Energy consumption of lighting: Records the energy consumption of the lighting system on a daily basis to facilitate the comparison of energy consumption differences before and after the application of energy saving technologies.
• Intelligent light control response: Monitors the automatic adjustment effect of the intelligent light control system under different light conditions to assess the sensitivity and stability of the system.

2.2.3. Data Collection of Ventilation Systems

Data acquisition for the ventilation system mainly pays attention to aspects such as system energy consumption, air humidity, and carbon dioxide concentration, with a collection frequency of once per hour. The collected contents include:

• Ventilation energy consumption: Daily records of the energy consumption data of the ventilation system are made to calculate the energy saving effect of the intelligent ventilation system.
• Air humidity: The humidity variations in the greenhouse are monitored through humidity sensors to determine the regulation effect of the intelligent ventilation system on air quality.
• Carbon dioxide concentration: The carbon dioxide concentration inside the greenhouse is monitored to ensure that the ventilation system can meet the air demands for crop growth.

2.3. Specific Application and Setting of Energy Saving Technology

To achieve high energy efficiency, three core energy saving technologies were applied in this experiment:

Heating system: The system integrates ground-source heat pump technology, utilizing constant underground temperatures, and solar thermal collectors on the greenhouse roof to capture solar energy, reducing heating consumption through a heat pump system.

Lighting system: The lighting system uses high efficiency LED plant lights for energy savings, with a smart light control system monitoring natural light levels and adjusting artificial lighting accordingly. The LED lights used are from Philips GreenPower (Philips Lighting, Eindhoven, The Netherlands) and offer spectral tunability for different growth stages.

Ventilation system: The intelligent ventilation system is equipped with Honeywell HIH-4000 (Honeywell International Inc., Morris Plains, NJ, USA) humidity sensors and SenseAir K30 (SenseAir AB, Delsbo, Sweden) CO₂ sensors, optimizing airflow based on real-time data to ensure energy-efficient ventilation.

2.3.1. Heating System

Technology Overview: The low winter temperatures in Heilongjiang make the heating system the primary energy consumption source for greenhouses. This experiment integrates a ground-source heat pump system, a solar thermal collection system, and high efficiency insulation materials within the greenhouse heating system.

Ground-source Heat Pump System: Utilizing the constant underground temperature, the ground-source heat pump technology transfers heat from the ground to the greenhouse. The system provides base heating during extreme cold weather, reducing the reliance on traditional fuels or electric heating [39].

Solar Thermal Collection System: Solar thermal collectors are mounted on the greenhouse’s south-facing roof to augment solar energy capture and utilization [40]. Solar energy is integrated with the heat pump system for transferring the absorbed solar energy via the water circulation system to the heating pipelines within the greenhouse, optimizing the energy utilization efficiency and realizing the synergy between different energy systems [41]. A thermal storage tank is used to store excess heat during the day and gradually release it at night, helping to alleviate nighttime heating demands [42].

High efficiency Insulation Materials: The greenhouse walls are covered with multilayer composite insulation materials and a nanoparticle thermal coating to minimize heat loss. The multilayer composite insulation materials used in this study have a thermal conductivity of 0.035 W/mK and a reflectivity exceeding 85%. These materials feature a multilayer structure, including a reflective layer to block external cold air and an insulating layer to maintain stable internal temperatures. These properties ensure the insulation’s effectiveness in retaining energy during extreme cold conditions [43].

Expected Outcomes: By integrating the ground-source heat pump and solar thermal collection technologies with the application of high efficiency insulation materials, the heating system is expected to reduce heating energy consumption by approximately 20%, especially under extreme low temperatures and nighttime conditions.

2.3.2. Illuminating System

Technology Overview: Due to the short daylight hours in Heilongjiang during the winter, this experiment utilizes high efficiency LED plant lights and an intelligent light control system to ensure that the lighting needs of crops are met while minimizing energy consumption.

LED Plant Lights: LED lights are ideal for various crop growth needs due to their adjustable spectral characteristics. By providing a combination of red and blue light, LED plant lights enhance photosynthetic efficiency and, compared to traditional lighting, significantly reduce energy consumption.

Intelligent Light Control System: The intelligent light control system uses light sensors to monitor the intensity of natural light and dynamically adjusts the output intensity of the LED plant lights based on outdoor light conditions. On sunny days when natural light is abundant, the system automatically reduces or turns off the artificial lighting, thereby minimizing unnecessary electricity consumption [44].

Expected Outcomes: The combination of the intelligent light control system and LED plant lights is expected to reduce lighting energy consumption by 15% to 20%. The energy-saving effect will be more pronounced in February and March, as daylight gradually increases.

2.3.3. Ventilating System

Technology Overview: Under the extreme cold conditions of winter in Heilongjiang, the ventilation demand for greenhouses is relatively low, but effective control of air humidity and carbon dioxide concentration is necessary. This experiment implements an intelligent ventilation system to achieve precise, demand-based ventilation and reduce unnecessary energy consumption.

Intelligent Ventilation Control: The intelligent ventilation system integrates temperature, humidity, and carbon dioxide sensors to monitor environmental parameters inside the greenhouse in real time. When humidity levels are high or carbon dioxide concentrations increase, the system automatically activates or adjusts the ventilation equipment. In extreme cold weather, the system reduces the ventilation frequency to maintain stable greenhouse temperatures.

Zonal Ventilation Design: The intelligent ventilation system is devised to regulate the ventilation intensity in diverse zones of the greenhouse in accordance with the specific climatic requirements of each area, thereby effecting adaptive modifications [45]. For instance, ventilation is reduced in areas near the heating system, while increased ventilation is applied to areas with higher humidity, ensuring that the microclimate conditions are optimal for crop growth [46].

Expected Outcomes: The intelligent ventilation system is expected to effectively balance air quality and energy consumption within the greenhouse, with a predicted reduction in ventilation energy consumption of approximately 15% to 18%.

2.4. Data Analysis Method

The data used in this study were collected during two experimental periods: November 2022 to March 2023 (baseline period without energy saving technologies) and November 2023 to March 2024 (with energy saving technologies implemented). Both periods were conducted in the same greenhouse, ensuring consistent operational practices and structural conditions. External climatic conditions, including daily temperature and humidity, were monitored to provide contextual information for energy consumption [47]. Table 1 summarizes the average climatic conditions observed during the experimental periods. These data highlight the extreme cold and limited natural light availability that heavily influenced the energy demands for heating and lighting systems. While no formal normalization was applied to account for interannual weather variability, the experimental setup minimizes potential biases, allowing the observed energy savings to primarily reflect the effects of the implemented technologies. Given the controlled experimental conditions and daily monitoring of climatic variables, the observed differences in energy performance primarily reflect the effects of the implemented technologies. Future research could incorporate predictive models to simulate varying adoption levels and optimize cost-benefit ratios. The collected data is processed through the following analytical methods to evaluate the effectiveness and economy of the energy saving technology.

2.4.1. Energy Consumption Analysis

The energy consumption differences of heating, lighting, and ventilation systems before and after applying energy saving technologies were compared, and the energy saving rate of each system was analyzed. As shown in Table 1, January and February experienced the lowest average temperatures (−20 °C and −18 °C, respectively), corresponding to peak energy demands for the heating system. Meanwhile, increased daylight hours in March reduced the reliance on artificial lighting, demonstrating the effectiveness of the intelligent light control system. The energy consumption analysis will be combined with the climate conditions in the cold area of Heilongjiang Province, and the application effect of each technology in extreme environments will be revealed by comparing the energy saving effect month by month.

2.4.2. Technical and Economic Evaluation

The economic analysis was conducted to evaluate the cost-effectiveness of the proposed energy saving technologies [48]. The analysis considered the following factors:

• Initial Installation Cost: Capital investment for equipment and installation.
• Operation and Maintenance Cost: Annual operational expenses, including energy costs and maintenance fees.
• Annual Energy Cost Savings: Calculated as the difference in energy consumption before and after implementing energy saving technologies, based on local energy tariffs.

Equations Used:

The key metrics for economic evaluation were calculated as follows:

Payback Period (P):

$$P={\displaystyle \frac{C_{\mathrm{initial}}}{S_{\mathrm{annual}}}}$$

(1)

where C_initial is the initial installation cost, and S_annual is the annual cost savings.

Net Present Value (NPV):

$$NPV={\displaystyle \sum _{t=1}^T\frac{S_t}{{(1+r)}^t}}-C_{initial}$$

(2)

where S_t is the annual savings in year t, r is the discount rate, and T is the project lifespan (15 years in this study).

2.4.3. Environmental Adaptability Assessment

Based on the data of temperature and humidity, light, and carbon dioxide concentration in the greenhouse, the adaptability and stability of various energy saving technologies in the extreme environment in the cold region were evaluated [49]. Special attention is paid to the real-time response ability of the intelligent control system to verify its stability and reliability under extremely cold conditions.

2.5. Validation Methodology

To ensure the scientific rigor and reliability of the results, the following validation methods were employed in this study:

• Experimental Design: Experiments were conducted in the same greenhouse under controlled conditions, eliminating variability from structural or operational differences. This ensured observed effects were attributable to the applied technologies.
• Environmental Monitoring: The energy saving effects of the implemented technologies were validated by performing statistical analyses on the data collected. The statistical tests conducted in the analysis ensured that any observed differences in energy consumption were primarily due to the technologies applied and not due to random variations in environmental conditions.
• Standardized Instruments: To ensure the accuracy and consistency of data, all instruments used for monitoring energy consumption, temperature, and humidity were calibrated and standardized. The use of reliable and validated instruments was crucial in maintaining the precision of the data collected.
• Future Validation: To further substantiate the findings, future studies will involve additional data collection over multiple years and under varying climate conditions. This will allow for a more comprehensive validation of the results and enable comparison with theoretical models to confirm the long-term performance and adaptability of the energy saving technologies.

3. Results and Discussion

In this study, a number of energy saving technologies were applied in agricultural greenhouses in cold areas of Heilongjiang province, and the energy saving effects and economy of each energy saving technology under different environmental conditions were evaluated by monitoring the energy consumption of heating, lighting, and ventilation systems on a monthly basis. The results show that the integrated energy saving technology can effectively reduce the total energy consumption of the greenhouse and show good economic benefits. The following is an analysis of the specific experimental results.

3.1. Analysis of Energy Saving Effect of Heating System

In the cold region of Heilongjiang, heating is the primary source of energy consumption for greenhouses during the winter. This study employs an integrated heating solution combining ground-source heat pumps, solar thermal collection systems, and high efficiency insulation materials to reduce winter heating energy consumption. Experimental data show that this combination significantly reduces the energy consumption of the greenhouse while maintaining a stable internal temperature. To ensure comparability between the baseline period (November 2022 to March 2023) and the energy saving period (November 2023 to March 2024), the experiments were conducted in the same greenhouse with consistent operational practices. While no formal weather normalization was applied, daily monitoring of external temperature and humidity provided contextual data to validate the impact of energy saving technologies. The energy saving rate of the heating system reached 19% to 20% in the relatively warmer months of November and March, while it was slightly lower, around 16%, during the extremely cold months of January and February (

Table 2. Comparison of energy consumption of heating system.

Time	Conventional Heating Energy Consumption (kWh)	Energy Consumption of Energy Saving Technology (kWh)	Fractional Energy Saving (%)
Nov.	14,500	11,750	19.0
Dec.	17,500	14,350	18.0
Jan.	19,500	16,385	16.0
Feb.	18,500	15,540	16.0
Mar.	13,500	10,400	20.0
Aggregate	83,500	68,425	17.6

).

Results Analysis: The ground-source heat pump system utilizes the constant underground temperature to provide a stable heat source under low-temperature conditions. The solar thermal collection system effectively supplies heat during the day when sunlight is abundant, while at night, the heat retention is supported by the insulation materials to minimize heat loss. Overall, the heating system achieves an energy saving rate of 17.6%, presenting an efficient and low-carbon solution to meet the high energy demand of winter in cold regions. The observed energy savings, particularly in November and March, were influenced by moderate external temperatures, which allowed for more efficient operation of the integrated heating system. Conversely, in January and February, extremely low temperatures increased heating demand, resulting in slightly lower fractional energy savings. These findings highlight the adaptability of the heating system to varying climatic conditions.

3.2. Analysis of Energy Saving Effect of Lighting System

Under the short daylight conditions in Heilongjiang during winter, the greenhouse’s artificial lighting demand increases. This study uses an intelligent light control system and high efficiency LED plant lights, dynamically adjusting light intensity to optimize energy consumption. Experimental data show that the lighting system achieves an average energy saving rate of 18.6%, with the highest energy saving rate reaching 20.3% in March. The specific results are shown in

Table 3. Lighting system energy consumption comparison.

Time	Conventional Lighting Energy Consumption (kWh)	Energy Consumption of Energy Saving Technology (kWh)	Fractional Energy Saving (%)
Nov.	3500	2870	18.0
Dec.	4300	3500	19.0
Jan.	4800	3940	17.9
Feb.	4600	3750	18.5
Mar.	3200	2550	20.3
Aggregate	20,400	16,610	18.6

below.

Results Analysis: The intelligent light control system monitors the natural light intensity in real time and dynamically adjusts the output intensity of the LED plant lights, effectively reducing artificial lighting energy consumption. The LED plant lights not only consume less energy but also enhance light energy utilization efficiency, optimizing the light requirements for crop growth.

3.3. Analysis of Energy Saving Effect of Ventilation System

The extremely cold winter conditions in Heilongjiang Province make the main task of the greenhouse ventilation system to maintain air quality and humidity. In this study, an intelligent ventilation system combined with zoning control and on-demand ventilation is used to optimize the ventilation efficiency. The results show that the energy saving rate of the ventilation system is 17.4%, especially in March, reaching 19.2%. The specific results are shown in

Table 4. Ventilation system consumption comparison.

Time	Conventional Ventilation Energy Consumption (kWh)	Energy Consumption of Energy Saving Technology (kWh)	Fractional Energy Saving (%)
Nov.	1200	900	17.5
Dec.	1100	915	16.8
Jan.	1000	850	15.0
Feb.	1100	900	18.2
Mar.	1200	970	19.2
Aggregate	5600	4625	17.4

below.

Results Analysis: The intelligent ventilation system effectively reduced the heat loss in extremely cold weather and further optimized the energy consumption through zoning control in the months when the temperature rose.

3.4. Comprehensive Energy Saving Effect Analysis

This study integrated energy consumption data from the heating, lighting, and ventilation systems to assess the overall energy saving effect. The results show that the combined application of these technologies reduced the total energy consumption of the greenhouse by 17.8%.

The comparison was made between two experimental periods: the baseline (without energy saving technologies) and the period with integrated technologies. To account for potential climatic variability, daily temperature and humidity were monitored. While weather conditions may have introduced minor differences, the consistent setup of the experiments ensures that the observed energy savings were primarily due to the implemented technologies. The specific results are shown in

Table 5. Comprehensive energy saving effect analysis.

System	Conventional Energy Consumption (kWh)	Energy Consumption of Energy Saving Technology (kWh)	Fractional Energy Saving (%)
Heating system	83,000	68,425	17.6
Lighting system	20,400	16,610	18.6
Ventilation system	5600	4625	17.4
Aggregate	109,000	89,660	17.8

and Figure 2 below.

Results Analysis: Figure 2 shows the energy saving performance of the various systems throughout the year. The integrated system was most effective in November and March, when temperatures were moderate, while the energy savings slightly decreased in January and February due to the extremely cold temperatures. However, the energy saving impact remained significant. The results confirm the effectiveness of managing multiple energy saving technologies in cold region facility agriculture.

3.5. Economical Analysis

The study further evaluates the economic viability of these energy saving technologies by calculating their payback periods and net present value (NPV). The analysis takes into account energy consumption variations across different climatic conditions and realistic operational costs based on actual energy use and local tariffs. The economic analysis results for each energy saving technology are shown in

Table 6. Economic analysis of energy saving technology.

Technology	Installation Cost (Yuan)	Source of Cost	Annual Savings (Yuan)	Operating Cost Basis	Payback Cycle (Years)	15 Years NPV (Yuan)
Ground source heat pump system	80,000	Experimental Procurement	16,000	Energy tariff: 0.6 Yuan/kWh + Maintenance cost	5	98,450
Solar heat collection	100,000	Experimental Procurement	12,000	Energy tariff: 0.6 Yuan/kWh	8	42,300
Intelligent light control	50,000	Experimental Procurement	5000	Energy tariff: 0.6 Yuan/kWh	10	18,800
High efficiency insulation system	40,000	Experimental Procurement	7800	Reduced heating demand, energy tariff	5	56,700
Intelligent ventilation system	20,000	Experimental Procurement	2200	Energy tariff: 0.6 Yuan/kWh	9	8120

and Figure 3.

Results Analysis: Figure 3 shows that the NPV of the ground-source heat pump and high efficiency insulation systems remains stable, demonstrating strong adaptability and a short payback period of 5 years, making them suitable for widespread use in cold regions. Conversely, the solar thermal and intelligent light control systems are more sensitive to fluctuations in energy prices, showing better economic feasibility under rising energy costs. Overall, the ground-source heat pump system, high efficiency insulation materials, and intelligent light control system all prove to be economically viable.

3.6. Sensitivity Analysis: Effects of Energy Price Fluctuations and Changing Climate Conditions

To further evaluate the adaptability of each energy saving technology, this study conducted a sensitivity analysis under energy price fluctuations and seasonal variations, examining their impact on NPV. The analysis simulated scenarios with energy price growth rates of 5%, 0% (stable), and +5%, as well as the effects of moderate climate (reduced heating demand) and extreme cold climate (increased heating demand) on NPV. The results are shown in Figure 4 and Figure 5.

Results Analysis: In the scenario of rising energy prices, the NPV of all energy saving technologies significantly increased, especially for the ground-source heat pump system and high efficiency insulation materials. This indicates that, in an environment of increasing energy prices, the economic viability of energy saving technologies is substantially enhanced. In contrast, the solar thermal collection system and intelligent light control system show higher sensitivity to price fluctuations, making them more suitable for application in situations with high energy prices.

Results Analysis: Under extreme cold conditions, heating and insulation-related technologies, such as the ground-source heat pump system and high efficiency insulation materials, show higher NPVs, making them particularly suitable for application in harsh environments. The NPV of LED plant lights and intelligent light control systems is less affected by seasonal variations, demonstrating good seasonal adaptability and suitability for year-round operation. The intelligent ventilation system performs better under warmer seasonal conditions, making it well-suited for applications that require seasonal adjustments.

3.7. Limitations of the Experimental Design

This study acknowledges several limitations. First, while experiments were conducted in the same greenhouse under consistent operational conditions, the absence of formal weather normalization may introduce minor variability due to interannual climate differences. Second, the use of a single greenhouse limits the generalizability of the results. Future research should involve parallel testing across multiple greenhouses in diverse regions and consider the application of weather normalization to improve the evaluation of energy saving technologies.

While the results are based on a single year of data, future research will continue to collect long-term data to validate the findings and compare them with theoretical models, further refining the calculated payback periods and NPVs.

3.8. Validation Results

The validation efforts yielded the following insights:

• Reliability of Experimental Results: The energy saving rates for heating (17.6%), lighting (18.6%), and ventilation (17.4%) were validated through direct measurement and statistical analysis. Paired t-tests showed no significant differences in climatic conditions between the two experimental periods (p > 0.05), confirming that observed energy savings were due to the implemented technologies.
• Impact of Climate Variations: While energy savings were slightly lower during colder months (16% in January and February), the technologies were still effective, demonstrating their adaptability in extreme cold conditions.
• Future Data Validation: Ongoing data collection will refine the validation process, providing more accurate long-term performance data for energy saving technologies and further validating payback periods and NPVs.

Conclusion: The integrated energy saving system significantly reduced energy consumption by 17.8%. The economic analysis confirms the strong feasibility of these technologies, particularly under rising energy prices or extreme cold conditions.

4. Conclusions

4.1. Research Conclusions

This study proposes and validates an intelligent, multi-technology integrated energy saving solution tailored for facility agriculture in cold regions, specifically in extreme cold environments such as Heilongjiang. By integrating a ground-source heat pump system, solar thermal collection, intelligent light control, LED plant lights, and an intelligent ventilation system, the overall energy saving rate reached 17.8%, with notable reductions in energy consumption across heating, lighting, and ventilation systems.

The study employed a comparative experimental design over two periods, ensuring consistent operational conditions and monitoring climatic variations. The results confirm that the synergistic application of multiple technologies, supported by intelligent control, significantly enhances energy efficiency, offering a viable and effective energy saving solution for cold region agriculture.

The financial analysis demonstrates the cost-effectiveness of this solution, particularly in scenarios with fluctuating energy prices or extreme climate conditions. These technologies not only lower operational costs but also make the integrated system an economically viable approach for cold region agricultural facilities.

4.2. Outlook and Future Application Potential

The integrated energy saving solution has shown significant potential for cold region facility agriculture, but there remains room for further optimization. Future research directions include:

Wider Application in Cold Regions: Expand experimental verification to other cold regions, such as Northern Europe and North America, to assess the adaptability and optimization potential of this technology in diverse climates. Conducting parallel experiments in multiple greenhouses across various locations will strengthen the comparative data and minimize biases from single-location studies.

Economic Optimization: Focus on reducing the manufacturing and installation costs of key technologies to enhance the solution’s cost-effectiveness, particularly for small- and medium-sized agricultural facilities. Incorporating predictive modeling could optimize cost-benefit ratios for different scales of operations and regional conditions.

Improving Intelligent Control Systems: Integrate machine learning and real-time adaptive algorithms to enhance the system’s ability to self-adjust based on historical and real-time environmental data, ensuring stability under extreme conditions.

Diverse Renewable Energy Integration: Explore integrating additional renewable energy sources such as wind and biomass into the energy mix to reduce reliance on conventional energy sources and further improve sustainability.

Environmental Impact Assessment: Employ lifecycle assessment (LCA) methods to evaluate the carbon footprint and environmental impact of the energy saving technologies, contributing to the shift towards more sustainable and low-carbon agricultural practices.

In conclusion, the integrated energy saving solution demonstrated in this study offers significant advancements in energy efficiency, intelligent control, and economic viability. With further optimization and expanded application, this solution holds great promise for supporting the sustainable development of facility agriculture in cold regions.